Mexico: Financial Sector Assessment Program-Financial System Stability Assessment

International Monetary Fund. Monetary and Capital Markets Department

doi:10.5089/9798400223686.002.A001

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International Monetary Fund. Monetary and Capital Markets Department

International Monetary Fund. Monetary and Capital Markets Department
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Publication Date:: 04 Nov 2022

eISBN:: 9798400223686

ISBN:: 9798400223686

Language:: English

Keywords:: cash flow; development bank; Mexican peso; risk management practice; due diligence; Loans; Liquidity requirements

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Mexico has had a robust financial system for many years. Banks have maintained high capital and liquidity buffers. However, the system provides less finance to the real economy than in peers. Mexico has experienced significant real GDP fluctuations since the Peso crisis but no major credit boom-bust cycles, given strong policy frameworks that have been further enhanced since the 2016 FSAP. The economy has strong external trade and financial linkages. These have been an important channel for transmitting global shocks. The financial system has been resilient to the COVID-19 pandemic, reflecting a mix of resumption in mobility and support from domestic and global policies. Buffers in the financial system have increased further during the pandemic. The key risk confronting Mexico is the first sustained and ongoing tightening of global liquidity conditions since the Global Financial Crisis.

Abstract

Background

6. Mexico is gradually recovering from the economic effects of the pandemic (Table 2). The economy contracted by 8.1 percent in 2020 (Figure 1). While growth bounced back to 4.8 percent in 2021, cumulative output growth and credit growth during 2020-2021 were weaker than other emerging markets (EMs) (Text Chart).

7. The impact of the pandemic on the financial system has been contained. Mexico experienced capital outflows and a sharp exchange rate depreciation during the pandemic (Figure 2). But the overall spreads of risky financial assets have been low and market functioning has been orderly, reflecting also the authorities’ effective policy responses (Table 3). Banxico cut interest rates by 300 basis points to aid the economy and established facilities to support market functioning. CNBV issued regulatory support measures, encouraging loan payment deferral and dividend payout restrictions.¹ Fiscal stimulus was modest, but Mexico benefited from sizable fiscal policy spillovers from the U.S. (Gourinchas and others, 2021).

8. Private leverage remains low, but some concerns emerge. Mexico has experienced no prominent credit boom-bust cycle since the Peso crisis (Text Chart and Figure 3). Private sector leverage and debt service burden remain low, compared to EM peers. However, investor sentiment towards Mexico has softened since 2016.

9. Downside risks loom large. Although Mexico has limited direct exposure to Russia and Ukraine, rising commodity prices has pushed inflation up, well above Banxico’s target (Figure 1). Banxico has raised the policy rate by 525 basis points since June 2021. Amid the rising inflation and worse-than-anticipated slowdown in the U.S. and globally, Mexico, like other EMs, faces the first sustained tightening of global financial conditions since the GFC and a difficult trade-off in managing risks to inflation and growth (i.e., stagflation) (see the accompanying Article IV staff report). New COVID-19 variants remain a wildcard.

10. Mexico faces two structural transitions, raising risks and opportunities. The use of digital financial services, though still embryonic, is picking up and holds the promise of increasing financial access.² But this could generate new risks from cyberattacks and new forms of foreign and domestic digital monies. Policies to support the transition to a lower carbon economy could affect earnings in carbon-intensive industries and banks that lend to them. Rising climate physical risk could impact the financial sector. Opportunities also arise from green finance.

Financial System Structure

11. Mexico’s financial system is relatively small, with banks playing a leading role. The system, with assets of about 100 percent of GDP, is smaller than EM peers (Text Chart) and has not grown much in size and complexity since the 2016 FSAP (Table 4). The banking sector accounts for more than half of the system, while pension funds and insurers account for about 20 and 8 percent, respectively. The financial system is structured around financial holding companies (FHCs). All six D-SIBs are fully owned by FHCs and play a leading role within the conglomerates.

12. The banking sector is highly concentrated with a strong presence of foreign subsidiaries. Mexico has 50 commercial banks. Six D-SIBs comprise ¾ of total banking sector assets (Figure 4). Five D-SIBs are foreign subsidiaries, generating a large share of the parent groups’ profits (Table 5). Six development banks (DBs) (9 percent of financial system assets) fill market gaps by providing finance to long-term projects (e.g., infrastructures), small and medium-sized enterprises (SMEs), exporters, housing, and low-income populations. DBs generally depend on wholesale funding with only two small DBs accepting some deposits.

13. Non-bank financial institutions (NBFIs) are typically long-term investors. Pension funds are the main institutional investors, followed by investment funds and insurers (Table 4). Their assets have increased since the last FSAP, with investments mostly concentrated in sovereign debt securities.

14. Mexico is highly integrated with global financial markets. Foreign investors hold about one-sixth of the outstanding local currency government bonds (Text Chart) though their share has been declining in the last years. The Mexican peso (MXN) is widely used as a proxy for EM currencies. Trading volumes of MXN on major exchanges are significantly higher than most other EM currencies.³ This proxy trade gives MXN a high correlation (or beta) with global risk shocks.

15. Capital markets are of modest size, relative to EM peers. Outstanding domestic debt securities and stock market capitalization amounted to 46 and 31 percent of GDP at end-2021. Apart from the sovereign, the use of capital markets for firm financing is limited (Text Chart).

Systemic Vulnerabilities

16. The financial system is emerging from the pandemic with higher capital buffers and no sign of stretched asset values and credit froth. Systemic vulnerability indicators are at generally low and declining levels (Figure 5). However, uncertainty over bank asset quality and other weak pockets exist.

Banks’ capital buffers have risen in recent years. Despite some heterogeneity (Text Chart), the aggregate capital adequacy ratio in the banking sector increased to 19.5 percent at end-2021 (Table 6), comparing well with EM peers (Figure 8). The leverage ratio stood at about 12 percent. The higher capital level reflects high profitability and pandemic-linked suspension of dividend payouts.
Distribution of Total CAR and LCR

(In percent, as of 2021Q3)
Citation: IMF Staff Country Reports 2022, 335; 10.5089/9798400223686.002.A001
Sources: Fitch Analytics; Mexican Authorities; and IMF staff calculation.
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Distribution of Total CAR and LCR

(In percent, as of 2021Q3)
Citation: IMF Staff Country Reports 2022, 335; 10.5089/9798400223686.002.A001
Sources: Fitch Analytics; Mexican Authorities; and IMF staff calculation.
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Distribution of Total CAR and LCR

(In percent, as of 2021Q3)
Citation: IMF Staff Country Reports 2022, 335; 10.5089/9798400223686.002.A001
Sources: Fitch Analytics; Mexican Authorities; and IMF staff calculation.
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Credit risk appears moderate. At about 2 percent since the last FSAP, aggregate NPLs remain low in absolute terms and relative to EM peers (Table 6, Figure 6). Banks’ point-in-time probability of default (PIT PD) suggests that COVID scarring has been contained so far (Text Chart). While most pandemic-affected deferred loans are performing, they need continued close monitoring (Table 7).
Point-in-Time Probability of Defaults by Loan Segment

(In percent)
Citation: IMF Staff Country Reports 2022, 335; 10.5089/9798400223686.002.A001
Sources: Banxico; and IMF staff calculation.
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Point-in-Time Probability of Defaults by Loan Segment

(In percent)
Citation: IMF Staff Country Reports 2022, 335; 10.5089/9798400223686.002.A001
Sources: Banxico; and IMF staff calculation.
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Point-in-Time Probability of Defaults by Loan Segment

(In percent)
Citation: IMF Staff Country Reports 2022, 335; 10.5089/9798400223686.002.A001
Sources: Banxico; and IMF staff calculation.
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The banking sector maintains ample liquidity buffers. The aggregate Liquidity Coverage Ratio (LCR) and Net Stable Funding Ratio (NSFR) were above 200 and 120 percent at end-2021, respectively. But some smaller banks have lower buffers than D-SIBs.⁴
Some NBFIs and DBs depend on wholesale funding, making them susceptible to funding shocks. They use the repo market to manage short-term liquidity and funding operations. DBs have concentrated funding sources, securing more than 30 and 34 percent of their funding from bond issuance and repo operations, respectively (Figure 7). While the sovereign backstops DBs’ capitalization and guarantees their liabilities, market concerns over refinancing and repricing of global debt securities might increase funding pressures on them in tail risk events.
Mexican corporate fundamentals are strong in international comparison with pre-pandemic and pandemic declines recently starting to reverse. The corporate sector has low leverage and debt service burden compared to EM peers. Balance sheets and cash flows had weakened since the last FSAP, with further damage in contact-intensive industries during the pandemic, before rebounding in 2021 (Figure 8). Loans to private NFCs began to pick up late last year in nominal terms but remain below the pre-pandemic levels in real terms (Text Chart).
Commercial Bank Credit to Private Nonfinancial Corporates^1/

(Dec. 2019 = 100)
Citation: IMF Staff Country Reports 2022, 335; 10.5089/9798400223686.002.A001
Sources: Banxico; Have Analytics; and IMF staff calculation.Note: 1/ Corporate FX-denominated credit converted to dollars with the nominal exchange rates.
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Commercial Bank Credit to Private Nonfinancial Corporates^1/

(Dec. 2019 = 100)
Citation: IMF Staff Country Reports 2022, 335; 10.5089/9798400223686.002.A001
Sources: Banxico; Have Analytics; and IMF staff calculation.Note: 1/ Corporate FX-denominated credit converted to dollars with the nominal exchange rates.
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Commercial Bank Credit to Private Nonfinancial Corporates^1/

(Dec. 2019 = 100)
Citation: IMF Staff Country Reports 2022, 335; 10.5089/9798400223686.002.A001
Sources: Banxico; Have Analytics; and IMF staff calculation.Note: 1/ Corporate FX-denominated credit converted to dollars with the nominal exchange rates.
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Households have low leverage, and housing market risks are small. House price growth has been moderate in recent years (Figure 3), and household credit, including mortgage lending, is low in absolute terms and compared to EM peers. The weighted average mortgage loan-to-value and payment-to-income ratios have been stable at around 72 and 28 percent, with a small variance in recent years (Figure 5).

Systemic Risks and Financial Sector Resilience

17. The FSAP assessed systemic resilience, including system-wide liquidity and climate risks. In addition to the standard set of approaches, i.e., bank stress tests, corporate sector exercise, and contagion analysis (Figure 9), novel approaches were developed to probe system-wide liquidity risk and the risks related to climate change and financial digitalization. They are underpinned by a baseline and an adverse scenario. The stress test scenario horizon spans 2022–2024, starting with the data at end-2021. The baseline scenario is aligned with the IMF projections as of June 2022.

18. The adverse scenario entails low growth and high inflation in major economies and significant stress in global financial markets. It considers a combination of the first three external risks in the Risk Assessment Matrix (Appendix II). Shocks that drive inflation up (e.g., supply chain disruptions and commodity price surges, triggered by the war in Ukraine and COVID variants) would lead to a de-anchoring of inflation expectations in the U.S. and Fed policy rate hikes at a faster clip than in the baseline (Figure 10). Investors’ reassessment of market fundamentals would lead to a widespread risk-off event in the global financial markets, causing sharp currency depreciation, a rise in sovereign and corporate spreads, liquidity strains, and negative macrofinancial feedbacks (Table 8).⁵

A. Standard Assessment of Systemic Risks

19. The banking system is broadly resilient to severe external shocks. The solvency stress tests suggest that most banks have ample capital buffers relative to hurdles. Aggregate capital shortfalls in the adverse scenario are relatively small (less than 0.4 percent of GDP). The top 10 banks’ capital adequacy ratio declines by 4.7 percentage points to 14.5 percent by 2022, comfortably above the minimum requirements, despite some dispersion among banks due to the diversity of business models (Figure 11). Two key drivers underpinning capital depletion are market losses due to the pronounced rise in interest rates and credit spreads, and credit losses due to asset quality deterioration.⁶ Net interest income continues to contribute positively to capital given the solid net interest margins of Mexican banks under a higher interest rate environment, although at a more moderate level compared to the baseline. MXN depreciation has limited impact reflecting banks’ very small net open FX positions and insignificant effects on corporate PDs in the credit risk model estimation.

20. However, some risks could arise from exposure to contingent credit lines and from large holdings of debt securities. Contingent credit lines are substantial (about 2.7 trillion pesos and 10 percent of GDP in May 2022) and unevenly distributed among banks. Although about 90 percent of the credit lines are revocable, they could negatively affect banks’ capital positions if contemporaneously triggered in a tail-risk event (Figure 11). A higher-than-anticipated rise in interest rates (+150 bps) would also have considerable effects via mark-to-market losses on debt securities, leading the top-10 banks’ capitalization to decline by 2.4 percentage points by 2022, though the likely effects would be attenuated by hedging that the FSAP is unable to model.

21. Overall liquidity conditions in the banking sector are robust, but some smaller banks could face risks. The aggregate LCR stood at 225 percent in December 2021, with all commercial banks above the 100 percent regulatory minimum. Most systemic banks, starting from high LCRs, are well-positioned to manage short-term liquidity pressures. But institutions with low LCR starting points and large exposure to wholesale deposits, particularly some smaller banks, would breach the threshold under severe stress (Table 9). The cashflow analysis supports these results. Aggregate liquidity shortfalls would occur only in an extreme scenario and amount to about 1 percent of banking sector assets when liquidity shortfalls of some banks are netted out with surpluses of others (Figure 12). Moreover, the shortfalls are manageable, given Banxico’s capacity to support the system during stress events.

22. Two potential problems, related to banks’ short-term liquidity management, should be monitored closely. First, contingent credit lines could be withdrawn quickly or simultaneously under stress. Second, part of the retail deposits from high net-worth individuals in search of higher yields could potentially behave like wholesale deposits and be more prone to outflows, though more granular data would be needed to assess this in depth.

23. The potential for contagion through cross-border bank exposures or domestic networks appears limited. Mexico would face inward spillovers from a hypothetical banking crisis in the U.S. (Figure 13). But Mexican banks play a limited role as shock originators or transmitters to other countries. The domestic interconnectedness analysis with bilateral exposures among banks and NBFIs suggests limited contagion effects. Domestic contagion would result from the failure of development banks, although such failures are very unlikely given DB’s sovereign backstop.

24. Corporate debt-at-risk would rise under the adverse scenario, but the impacts on the financial system are limited due to low leverage. Using conventional econometric modeling, aggregate corporate PIT PDs almost double from a low level during the outer years of the adverse scenario.⁷ Complementary corporate sector analysis substantiates these estimates, using firm-level expected default frequencies (EDFs). The analysis finds that Mexican firms, outside the well-known set of publicly listed firms, would face heightened default risks under the adverse scenario. Firms that are more highly levered and have poorer liquidity conditions would have difficulty in a high-interest rate and low-growth environment (Figure 14). However, they tend to be smaller, so the implications for the banking sector would be limited. The analysis reconfirms that FX depreciation plays an insignificant role in affecting Mexican corporate EDFs.⁸

B. System-Wide Liquidity Analysis

25. A novel approach is developed to examine the risk that multiple financial institutions face liquidity stress simultaneously. As shown in Figure 15, Mexico’s financial intermediaries are closely interconnected to each other via direct lending, debt crossholdings, repo exposures, and exposures to common assets (e.g., government bonds), exposing them to repricing risks associated with fluctuations in interest rates and spreads. The analysis seeks to assess the interconnectedness and resilience of the entire financial system (by contrast with the bank liquidity stress tests discussed in ¶16) from a liquidity perspective to simulated shocks to capital flows, liquidity demand from corporates, and deposits outflows (see Figure 9). The simulations use aggregate institution level data to generate post-shock liquidity positions for banks and investment funds (see Appendix III for details).

26. The aggregate analysis suggests that system-wide liquidity would remain resilient, with commercial banks effectively backstopping the liquidity needs of other entities. Even in the most severe case, commercial banks show only small liquidity shortfalls upon the triggering of contingent credit lines and wholesale deposits’ outflows (Figure 16). They can in principle act as a shock absorber for the system by providing liquidity to other entities through repo transactions, assuming liquidity requirements are lowered (as during the pandemic) and no underlying change in their liquidity preference. However, in the aggregate framework, were commercial banks or entities such as investment funds to change liquidity preference or face binding liquidity constraints during tail-risk events, this could lead to a deterioration in the liquidity positions of other entities and materialization of larger system-wide liquidity stress, absent liquidity provision by the MFAs.

C. Climate-Related Risk Analysis

27. The FSAP has piloted analysis of the potential impact of transition and physical risks for the financial sector. Both analyses rely on scenario-based approaches, as described in Figure 17.

Transition risk. Besides a baseline scenario (so-called “current policies”), two other 5-year scenarios are explored, motivated by the NGFS scenarios: (i) global action (reflecting the notion of orderly transition) and (ii) delayed-uncertain action (reflecting increased uncertainty with delayed, disorderly transition at the global level). Also, a novel stochastic jump-diffusion model of corporate spreads is used to assess the impact of a sudden large shift in the market’s risk assessment under the delayed-uncertain scenario.
Physical risk. The physical risk analysis focuses on floods and tropical cyclones (Text Chart). It also extends the analysis beyond individual climate events to look at extreme season scenarios over a three-year horizon, comprised of a series of severe floods and tropical cyclones, reflecting historical and potential future climate conditions corresponding to representative concentration pathways (RCP) 4.5 and RCP8.5.⁹

28. The transition risk analysis finds heterogeneous impacts across industries and banks. Under the global action scenario, NFCs are modestly affected, except chemicals and non-metallic segments of the manufacturing sector (Figure 18). The cumulative impacts on bank capital ratios would amount to about 0.4 percentage points by 2026. Such impacts would be heterogeneous across banks, depending on their sectoral exposures. Under the global delayed-uncertain scenario, the tail of the distribution of corporate PDs and bank capital ratios gets fatter. This analysis supports the case for an early transition to a low-carbon economy at the global level to mitigate the tail risk of large, sudden, necessary actions in the future.

29. The physical risk analysis is subject to high uncertainty but suggests that climate hazards would not likely generate systemic financial stress in the near term. Floods and tropical cyclones may substantially impact on livelihoods and wellbeing, particularly in the regions hit by the disasters. Data and models are subject to major uncertainty and gaps, but overall, the currently estimated impacts would not generate systemic financial stress despite a substantial impact on growth. Under the extreme RCP8.5 scenario, the estimated physical capital stock damage would translate into two percentage points deviation of GDP growth from the baseline in 2022, with the impact remaining persistent, and the banking sector’s capital ratio would decline by about 1.2 percentage points from the baseline solvency ST results (Figure 19).

D. Fintech-Related Risk Analysis

30. The aggregate impact on financial stability of new forms of digital money currently seems limited, but differences in bank business models suggests heterogeneity of risks. The FSAP team has conducted a hypothetical sensitivity analysis in which banks experience an erosion of net interest income and non-interest income (from payments services) due to the penetration of new forms of digital payments (see Appendix III for methodological details).¹⁰ In the most adverse scenario, the banking sector’s capital ratios would drop by 34 basis points over two years relative to the baseline solvency ST results (Figure 20). Banks that rely more on retail sight deposits and credit card fee income could see their capital ratios decline up to 75 basis points over such a time frame. Were CBDC introduction to become a source of pressure on bank margins, putting a cap on the size of CBDC accounts could mitigate the impact on banks.

E. Recommendations

31. The authorities’ framework to assess systemic liquidity stress is broadly in line with that of many major central banks, but there is scope for enhancement. The ST framework would benefit from adding a comprehensive cash flow analysis and advancing on developing a system-wide liquidity analysis. Banxico could monitor the dynamics of contingent credit lines and assess the relevant risks together with CNBV.

32. Pillar 2 requirements could be deployed to contain potential risks identified by the systemic risk analysis. CNBV could use its authority to impose capital add-ons based on the Internal Capital Adequacy Assessment Process (ICAAP), which has yet to occur, to address issues such as concentration risk, interest rate risk in the banking book, and gaps in risk management practices that are indicated by stress tests. The liquidity analysis could also be used in the Supervisory Review Process (SRP) to inform Pillar 2 requirements for both commercial and development banks.

33. The MFAs collect a wealth of data to support systemic risk analysis; efforts for further improvement should be continued. The current data available to the MFAs are wide-ranging. Further effort could help. Banxico and Tax Service Administration (SAT) could collaborate to share anonymized household and corporate income data. Also, closing data gaps in regulatory reporting—mainly IFRS9 implementation and banks’ internal ratings-based approach parameters— would be useful. A complete set of sectoral financial accounts (e.g., consistent balance sheet breakdown of NBFIs) and bilateral exposures would help conduct the system-wide liquidity analysis. Effort is also needed to improve firm-level disclosure of carbon footprints in both listed and unlisted Mexican firms.

Cross-Cutting Themes

34. There are multiple financial authorities with distinct mandates in Mexico. They include the Ministry of Finance and Public Credit (SHCP), Banxico, IPAB, and four supervisors (CNBV, the National Insurance and Sureties Commission (CNSF), the National Commission for Savings for Retirement (CONSAR), and the National Commission for Financial Services Consumer Protection (CONDUSEF)). Banxico has institutional autonomy defined in the constitution. IPAB and CONDUSEF have some autonomy regarding their finances as decentralized entities. The other supervisors report to SHCP as deconcentrated entities (see Annex II).

35. This institutional architecture offers opportunities for interagency coordination and the flow of information. The authorities collaborated effectively in addressing financial market turmoil during the pandemic—including managing the failure of two small banks—via existing coordination arrangements reflecting interlocking boards across agencies and a variety of coordinating committees and councils (see Annex II).

36. Strengthening further the autonomy of regulatory and supervisory agencies would enhance the credibility and impact of the financial oversight and the financial safety net. Lack of independence is the most common challenge faced by supervisors in many emerging market and other jurisdictions (Dordevic and others, 2021). In Mexico, fundamental advances here would require difficult changes to foundational legislation underpinning government organization (“Parastatal Entities Law”). As such, the FSAP team also suggests considering the following issues:

Progress on strengthening the independence and legal protection of supervisors is needed. Regulatory and supervisory agencies do not have budget autonomy (except Banxico) with their budgets determined by SHCP. The head of CNBV is appointed by the finance minister for an undefined term and can be removed from office for reasons not specified in law. The law does not protect supervisors adequately while discharging their duties in good faith. While lawsuits against supervisors have not been frequent, the lack of legal protection undermines conditions for effective supervision. This protection is critical in the Mexican context, where each supervisory conduct and measure should be described in the law.
Filling the vacancies for independent members on the IPAB Board should be given the highest priority. Four independent members, appointed by the president, hold a majority on the IPAB Board. Three of these positions have been vacant for some time and need to be filled swiftly. The safeguards for the autonomy of IPAB’s executive management should be strengthened by introducing a set term of appointment and more objective grounds for dismissal.

37. The organizational structure and resource needs of individual agencies would benefit from updated evaluation. The urgency is highlighted by the recent significant reduction in their operating budget (except Banxico), resulting in staff turnover and loss of experience. The FSAP recommends a strategic review of the organizational structure and resources of relevant agencies to make necessary adjustments to address existing and emerging challenges. The FSAP welcomes the ongoing evaluation in IPAB as a good example.

38. Interagency collaboration could also be further enhanced especially on emerging risks. The MFAs could regularly conduct table-top crisis simulation exercises with a range of extreme but plausible scenarios, including fast-fail resolutions of systemic and medium-size banks, their concurrent failure, and cyber crises. The authorities could also explore options to pool resources and expertise across institutions to mitigate resource constraints and develop new analysis of cyber and climate-related risks.

39. New risks have emerged on the Financial Market Infrastructure (FMI) landscape since the 2016 FSAP, and it is important to enhance the oversight of the Interbank Electronic Payment System (SPEI). Cyber risk has intensified worldwide. Other challenges include the emergent use of instant payments, the possible interaction with distributed ledger technology, and stablecoin arrangements. This increasingly complex risk landscape accentuates the need for effective, continuous FMI oversight. A full assessment of the FMI oversight is not included in the scope of the 2022 FSAP, but a focused review of the oversight function of the SPEI payment system finds that Banxico could enhance the SPEI oversight approach by establishing a formal oversight function independent from the SPEI operators and addressing any gaps identified through the CPMI-IOSCO PFMI implementation monitoring exercise (see Box 1).

^{Box 1.}

Oversight of the Interbank Electronic Payment System (SPEI)

Mexico’s FMIs have previously been assessed by CPMI-IOSCO and past FSAPs, and a full assessment of these is not included in the scope of the 2022 FSAP. According to the CPMI-IOSCO Level 1 assessment and update in July 2018, measures were fully implemented for adopting legislation, regulations, and policies for the 24 Principles for Financial Market Infrastructures (PFMI) and four of the five authorities’ responsibilities. The authorities observed or broadly observed most of the responsibilities, and partly observed the application of the principles for FMIs for central counterparties, as of November 2015. The systemically important payment system (SPEI) was also assessed during the 2016 and 2006 FSAPs in detail.

However, as new risks have emerged on the FMI landscape, it is important to enhance the oversight of the SPEI payment system relative to the PFMI and cybersecurity. While the SPEI operators in Banxico have taken significant steps in strengthening the cyber resilience of the SPEI, there are improvements that can be made to strengthen the overall oversight approach, including for cybersecurity, to bring it in line with CPMI-IOSCO’s expectations, as set out in its Responsibilities A-E.

Banxico could establish a more thorough oversight function for the SPEI system. It could conduct risk assessments against the PFMIs applicable to payment systems and its supplemental guidance on a continuous basis. The oversight function would benefit from having sufficient resources and independence from the SPEI operators. Banxico could establish a structured oversight approach and methodology after reviewing oversight models and approaches by other central banks to help inform their own optimal model.
Banxico could improve transparency. Banxico disclosed its responses to the CPSS-IOSCO Disclosure framework for FMIs in March 2016. However, it should, at a minimum, review its responses to the disclosure framework and disclose publicly its responses every two years to ensure continued accuracy and usefulness.
Banxico could address the gaps identified through the CPMI-IOSCO PFMI implementation monitoring exercise. This specifically relates to the implementation by Banxico of a timebound work plan for the SPEI payment system to fully observe all the principles of the PFMI.
Banxico could conduct periodic self-assessments of its observance of the responsibilities of the PFMI, i.e., Responsibilities A-E. It should aim to self-assess how effectively authorities fulfill their responsibilities as regulators, supervisors, and overseers.

Financial Sector Oversight

A. Macroprudential Framework

40. The authorities could develop and publish a macroprudential policy strategy. Complementing the Central Bank’s high-quality Financial Stability Report and other guidance issued by the CESF, the strategy can describe policy objectives, a list of instruments, decision-making processes, interagency coordination mechanisms, and the importance of retaining discretion when calibrating instruments based on a set of quantitative indicators and expert judgement. International experience shows that a formal strategy can boost the communication and traction of macroprudential policies, improve accountability, counter potential inaction bias, enhance policy coordination across regulatory and supervisory agencies, and strengthen credibility and effectiveness (IMF, 2014; CGFS, 2016).¹¹

41. A rich set of macroprudential tools has helped build resilience. Capital and liquidity tools and D-SIB buffers were introduced in line with Basel requirements (Table 11). A core funding ratio in FX has been effective for banks to manage FX risks. Measures to reduce vulnerabilities from exposures to related parties or liquidity risks in investment funds (e.g., swing pricing, redemption fees) are in place.

42. The authorities could consider expanding the toolkit and enhancing its time-varying use. Plans for finalizing and publishing a guideline for the countercyclical capital buffer (CCyB) are welcome and action at the current early stage of the financial cycle would be helpful. Indeed, with no evidence of credit and housing booms, introducing limits on loan-to-value and debt-service-to-income ratios could be considered as a medium-term agenda to build the resilience of the financial system preemptively.

B. Banking Regulation and Supervision

43. The authorities have made considerable progress in strengthening banking regulation and supervision. CNBV has operationalized the ICAAP and the SRP (though ¶27 notes the need for enhancements), and the operational risk management framework has significantly improved. Prospects for issuing amended regulations on large exposures in 2022 are important. The amendment will include new definitions and limits for “common risk” and “related parties,” and it is critical that they follow Basel III standards and best international practices (see Appendix Table 1 for the summary compliance with Basel Core Principles).

44. Some financial conglomerates operating in Mexico are outside CNBV’s consolidated supervision. A financial conglomerate can voluntarily request SHCP for legal authorization to operate as a financial group in Mexico. While most financial conglomerates operate as authorized financial groups, seven have not requested the SHCP authorization at the time of the FSAP assessment and are not subject to the CNBV’s consolidated supervision.

45. The legal and regulatory framework should be amended to enhance consolidated supervision. The issuance of the 2014 Financial Groups Law (LRAF) was an important step toward a legal framework for consolidated supervision, but it does not empower CNBV to impose prudential measures on financial conglomerates at the group level.¹² An amendment is needed to provide CNBV with powers to (i) apply a comprehensive set of prudential requirements on financial groups as a whole, (ii) enforce consolidated supervision on all de-facto financial conglomerates in Mexico, and (iii) impose discretionary powers to oversight all relevant entities of financial groups, including those not declared during the authorization and those operating abroad.

46. CNBV has invested heavily in upgrading its supervisory framework towards a more risk-based supervisory approach. CNBV reshaped the risk-based rating methodology (CEFER) in November 2015. Supervisory tools have also been standardized and centralized, aiming at streamlining procedures and optimizing resources.

47. Further efforts are needed to strengthen the risk-based supervisory approach. The CEFER quantitative methodology to determine inherent risks needs to be simplified. Greater use of flexibility and application of expert judgment throughout the supervisory cycle needs to be implemented, as opposed to a formal check-list approach. This will need the set-up of internal supervisory routines to support the development expert judgment among supervisors to better assess banks’ risk management practices. There are also important synergies between strengthening legal protection and improving risk-based supervision; the former will allow incentivize supervisors to further apply their judgment and discretion to emerging risks.

C. Cybersecurity Regulation and Supervision

48. Financial digitalization accentuates cyber risk, requiring careful countermeasures. Interdependencies within and beyond the financial system make Mexico vulnerable to evolving cyber threats. Thus, the CESF has recognized cyber as a risk with the potential to impact financial stability.

49. Banxico and CNBV have made significant progress in enhancing the financial system’s cyber resilience but need further enhancement. Banxico has improved its cybersecurity controls, incident response framework, threat intelligence function, and security measures of participants that connect to its infrastructure. CNBV has built a dedicated cybersecurity supervision unit and designed a cyber supervision methodology.

Banxico and CNBV need to deepen their cybersecurity strategy for the financial system. The purpose is to specify how to identify, manage, and reduce cyber risk effectively. The cyber strategy should outline how coordination and cooperation occur among public and private stakeholders and other jurisdictions.
Cyber risk regulation and supervisory practice need further improvements. CNBV is encouraged to issue regulations or enforceable guidance on Information Communication Technologies (ICT) and cybersecurity to all its supervised financial institutions, not only banks. It could also conduct on-site ICT/cybersecurity inspections and improve off-site supervision. The cyber supervision unit should be given sufficient resources to discharge its responsibilities.
Banxico should strengthen the cybersecurity oversight of FMIs. Intensive cybersecurity training of overseers, together with a comprehensive oversight approach and tools and leveraging the cyber strategy, will increase the capabilities and effectiveness of the FMI oversight function. Banxico could also set clear regulatory requirements for all the FMIs under its mandate.
Banxico and CNBV would benefit from developing a cyber map of the financial system. Cyber mapping will help identify operational and technological interconnectedness (e.g., critical nodes, transmission channels, and critical service providers).
Mexico would benefit from improving its public and private platforms for cyber threat intelligence and information sharing. By exchanging cyber information and intelligence, financial entities can improve their defensive capabilities, threat detection techniques, and mitigation strategies. Banxico could work with the financial sector to develop an industry-wide cyber information and intelligence sharing initiative.
The authorities could improve the implementation processes around the Bases of Coordination.¹³ The Bases of Coordination need to be translated into operational structures, policies, and procedures, with clear leadership by Banxico and CNBV. They could also propose working with the General Attorney’s office to raise awareness of the importance of effective cyber incident investigations and develop guidance for financial entities on how to store, handle, and administer evidence to facilitate investigations.

D. Oversight of Climate-Related Risks

50. The authorities have taken initial steps to advance the climate agenda, but financial institutions are generally at an early stage of managing climate-related risks. The CESF launched the Sustainable Finance Committee to coordinate climate-related policies and green finance practices. Banxico plays an important role in driving the climate risk agenda, for example, by actively participating in international fora and building awareness on climate risks in the financial system.¹⁴ However, financial institutions are at an early stage of integrating climate issues into their governance frameworks, corporate strategies, risk management, and disclosure practices, reflecting the complexities of assessing these risks and the limited supervisory guidance by regulators.

51. The authorities could lay the ground for integrating climate risks into prudential supervision of banks, insurers, and pension funds. They could leverage the Basel Committee on Banking Supervision’s Principles for the Effective Management and Supervision of Climate-related Financial Risks, published in June 2022. Insurers are already required to cover natural catastrophe risk management. Moving forward, CNSF could follow recommendations by the International Association of Insurance Supervisors to develop further guidance to cover climate risks in governance, risk management, business strategy and disclosure practices. Similarly, CONSAR has issued mandatory guidance for retirement funds and could update it over time with more detailed supervisory guidance.

52. Market transparency should be enhanced by introducing disclosure requirements for firms and investors. The lack of credible climate information is a key barrier to climate risk assessment and management and sustainable finance practices in Mexico, as in most other jurisdictions. To address this challenge, CNBV could move ahead with introducing disclosure standards of climate and ESG information for issuers and asset managers, while including such disclosure for firms in accounting standards.

E. Digital Money and CBDC

53. Risks of “digital dollarization” arise in principle, but generalized adoption of foreign stablecoins seems unlikely given robust policy and regulatory frameworks in Mexico. Reflecting legislation and regulatory measures, crypto-asset activities do not appear to have a material penetration in Mexico. Strong links with the U.S. and a large informal sector could increase the risk of eventually adopting foreign CBDC or stablecoins. However, such risks are mitigated by the strong and highly credible policy framework and very low level of dollarization in Mexico.

54. Banxico has a deep understanding of issues regarding its CBDC project but would benefit from preparing a risk management framework and conducting cost-benefit analysis. Banxico aims to foster financial inclusion and payments digitalization with its Payments Strategy and CBDC project. The complexity of issues with CBDC place a high premium on collaboration within Banxico and with all stakeholders, and on allocating enough resources at each phase of the project. Design choices should ensure that new business models based on CBDC are sustainable and that risks to the financial system are contained. Banxico could also continue to evaluate if there are alternatives (e.g., private digital monies) to achieve policy objectives at lower costs.

F. Financial Integrity (AML/CFT)

55. Mexico has progressed in addressing most of the technical deficiencies identified in the 2018 AML/CFT Mutual Assessment Report (MER).¹⁵ The legal framework applicable to the financial sector has been strengthened for customer due diligence, identification and verification of beneficial owners and politically exposed persons, new technologies, and wire transfers. Legal deficiencies, however, remain in the non-financial sector regarding reporting suspicious activities, verification of beneficial ownership, and the obligation to apply a risk-based approach.¹⁶

56. Efforts should continue to improve the effectiveness of the AML/CFT framework. Cognizant of the risks posed by shell companies in Mexico, the National Risk Assessment should be complemented with a comprehensive analysis of risks associated with different types of legal persons. The authorities need to ensure the availability of beneficial ownership information by establishing a beneficial ownership register as planned, strengthen AML/CFT consolidated supervision, and ensure adequate allocation of resources to AML/CFT supervision. Effective, proportionate, and dissuasive sanctions should be consistently applied, including by empowering CNBV to revoke a banking license upon AML/CFT breaches. SAT should step up its supervisory activities and ensure its resources are commensurate with the wide range of supervised professions and businesses. Improvements are also needed in money laundering investigations, including parallel investigations of tax and organized crimes and corruption. The authorities need to enhance monitoring of financial integrity risks from fintech and virtual assets. They should continue monitoring and properly supervising Virtual Asset Service Providers by enforcing registration requirements and customer due diligence obligations.

Systemic Liquidity Management, Financial Safety Net and Crisis Preparedness

A. Systemic Liquidity Management

57. Mexican money markets are well-regulated and function efficiently, but liquidity risk management of NBFIs and DBs could be improved. The efficient functioning of money markets is supported by the marginal level of interbank unsecured transactions, commercial banks’ full compliance with the LCR, and the depth of the repo market. The OTC repo market is bilateral with predominantly government or IPAB debt securities as collaterals. However, development banks are not subject to liquidity regulation (Appendix IV). Some DBs have a significant reliance on short-term funding with low levels of unencumbered HQLAs. While the government backstops their capitalization and explicitly guarantees their liabilities, DBs might contribute to system-wide liquidity risk in severe tail risk scenarios (Section IV. B). As such it would be useful to strengthen their liquidity monitoring and reporting and leverage their internal risk committees to take stock of their risk profile and contribution to systemic risk and consider appropriate action. NBFI’s limited ability to lend securities via repos, despite the relaxation in the pandemic, may constrain their risk management activity. As such, addressing remaining impediments to NBFIs’ more balanced participation in the repo market could be considered.

58. Banxico’s mid-corridor operating framework fully supports the efficient pricing and distribution of liquidity. Banks have certainty about day-to-day liquidity conditions and can access a collateralized intraday facility and an overdraft as backstops. The collateral policy provides a sufficient volume of securities to efficiently implement monetary policy, while the high quality and liquid nature of the securities minimizes the risks to Banxico’s balance sheet.

59. Liquidity management demonstrated flexibility and resilience during the COVID-19 financial market turmoil. The functioning of financial markets was restored after a short period of stress. Most measures were not fully utilized but were effective in restoring market functioning due to their strong signaling effects and Banxico’s liquidity support was essential in enabling local market participants to absorb the large amounts of government bonds sold by foreign investors. The COVID support measures (e.g., funding for lending facility) helped resolve the practical challenges of accepting credit claims as collateral. They had several design features that provide valuable lessons for future market support programs: (i) the programs were price-based facilities and served as effective backstops; (ii) Banxico deployed targeted operations to support market participants in the key securities markets by providing them funding liquidity in well-calibrated amounts and against good collateral with appropriate haircuts; (iii) risk transfer to Banxico remained completely controlled with very limited direct intervention; and (iv) exit strategies were provided by construction as most facilities were term repo or swap transactions. During the pandemic, Banxico utilized the Fed’s USD swapline and has a few other means to provide USD funding to the financial system, such as NDF, other credit facilities (e.g., the FCL arrangement with the IMF) and own FX reserves.

60. Banxico’s ELA framework would benefit from some enhancements. Banxico’s ELA framework has a sound legal foundation and a comprehensive internal policy. The framework provides broad flexibility to Banxico’s Governing Board; it can adjust ELA parameters (e.g., collateral, term, and rate) if credit institutions could pose systemic risks. However, some elements of the framework could be enhanced. First, while credit claims are eligible as collateral, encumbrance of credit claims is time-consuming and should be accelerated to be consistent with the emergency nature of the activity. Second, the ELA policy should set clear boundaries for flexibility in the decision-making process. The policy document should clarify that ELA decisions are based on a forward-looking assessment of the applicant’s solvency. While the ELA framework mitigates moral hazard by requiring the pledging of the shares of the institution, forbidding dividend payments and restricting operations, the policy should contain a binding minimum threshold for the ELA interest rate as is common with most major central banks.¹⁷

B. Financial Safety Net and Crisis Preparedness

61. The authorities have strengthened the financial safety net since the last FSAP and need to continue and accelerate enhancements.¹⁸ Recovery and resolution plans are in place for all commercial banks, and D-SIBs are required to increase their loss absorbency (Figure 21). The authorities progressed preparations for using the bridge bank tool, signed cooperation agreements with all major home jurisdictions of the Mexican systemic banks, clarified the emergency lending facilities including to banks in resolution, and improved the depositor payout process.

62. Further enhancement of the resolution regime will enhance financial stability and give the MFAs more flexibility and reduce the costs of resolution measures. The regime includes a range of resolution options, including administrative liquidation (Figure 22). Bail-in powers are the missing component and should be introduced while appropriately protecting creditors; the creditor hierarchy should be revised to make the newly introduced TLAC requirements more effective. Furthermore, the authorities should trigger resolution when they deem a bank nonviable instead of waiting for certain quantitative thresholds to be met. Moreover, the authorities should remove barriers to the effective use of two critical resolution tools: P&A transactions; and bridge banks. A (partial) P&A transaction with a bridge bank—likely preceded by bail-in—will need to become the primary resolution strategy for systemic banks instead of TOBA, which is a potentially costly tool and should be reconsidered when the authorities introduce further improvements to the resolution framework. Lastly, a recovery and resolution regime for financial holding companies should be adopted. This would address build-in contagion risk and reduce the risk of concurrently applying diverging liquidation procedures for distressed group members.¹⁹

63. As the authorities have been operationalizing important past reforms to the recovery and resolution framework, deficiencies in banks’ recovery plans and impediments to their resolvability need solving. To ensure timely and cost-effective resolutions, it is imperative to ensure the credibility and feasibility of banks’ financial contingency arrangements, to reduce the time horizon over which they are executed, and to be conservative in approving successive plans. IPAB does not have the power to remove impediments to banks’ resolvability, such as changes in banks’ business practices, structure, or organization, to reduce the complexity and cost of resolution, and to ensure that critical functions can be segregated legally and operationally. Thus, it should continue to identify impediments to resolvability and measures to mitigate these impediments— while shortening the resolution planning cycle for systemic and mid-size banks—and clearly articulate and discuss with banks the resolution capabilities that they should develop to effectively support their orderly resolution as planned by the resolution authority. While awaiting statutory powers for IPAB to remove impediments to banks’ resolvability, CNBV should actively support this process.

64. The authorities should continue to increase the deposit insurance fund for an effective and prompt response to the concurrent failures of larger banks. Despite the legacy debt from the Peso crisis, IPAB has built a fund that could cover the resolution and payout of most smaller banks. The deposit insurance fund is projected to reach 3.4 percent of insured deposits in 2027 and 5.1 percent in 2032, which would position it better for the concurrent failure of several of the largest non-systemic banks. This process could be expedited by relieving IPAB from the 1990s’ legacy debt. Furthermore, IPAB’s backup funding should be operationalized, and public awareness of deposit insurance needs to be increased.

Financial Sector Development

65. Access to financial services remain moderate, and competition pressures are limited in parts of the retail and SME markets. About half of adults reported having an account at a financial institution in 2021, up from 44 percent in 2015, but those with primary education experience low access and use level (Figure 23). Access to credit is also subdued, particularly in rural areas and for small and micro enterprises. Although card and digital/mobile wallet payments are expanding, cash remains the primary payment method. Large banks derive advantages from vertical integration and financial conglomerate structures, making it difficult for smaller banks to compete. Customers also appear insensitive to price differentials, despite limited formal switching costs.

66. Digital Financial Services (DFS) holds the promise to promote financial access, but the authorities need to address some obstacles. The National Council for Financial Inclusion and its coordination mechanism could be conducive to boost the DFS agenda, but DFS efforts could leverage more active coordination with an expanded set of public agencies (e.g., National Institute of Transparency, Access to Information and Protection of Personal Data) and private sector entities (e.g., fintech companies). The MFAs could consider expanding the use of Cobro Digital (CoDi) to P2P, P2G, e-commerce, utility bill, and public transportation payments.²⁰ Finally, Banxico’s e-KYC efforts could catalyze the adoption of Digital ID.

67. Refinements to the regulatory framework for fintech and swift implementation of open finance could promote competition from new players and technologies. The authorities could broaden the scope of permissible products and services under the 2018 Fintech Law. A swift implementation and finalization of open finance would be an important step in promoting client mobility and fostering competition. Some regulatory and technical requirements, such as strict rules for contracting and operating banking agents (comisionistas), could be reviewed and simplified without diluting necessary safeguards to ensure financial stability.

68. Development financial institutions (DFIs) play an important role in the financial sector but can be more impactful.²¹ They should prioritize using guarantees and second-tier lending to advance developmental priorities, making efficient use of their capital. The “aprovechamiento” (fees from DBs against the explicit government guarantee) could be revised to become more transparent. In addition, the authorities should pay attention to the strategy for Banco del Bienestar, whereby social objectives should be complemented with competitive neutrality and preservation of capital. Also, the authorities should pay attention to Infonavit’s high NPLs, as it plays a major role in the Mexican mortgage market.

69. The authorities should explore ways to stimulate markets for green finance. The financial sector could play an important role in providing the financing required to reach Mexico’s climate goals. The authorities should establish a climate finance strategy and introduce a green taxonomy. DFIs could be given more ambitious climate finance targets to deepen green markets.

Authorities' Views

70. The authorities welcomed the FSAP’s positive assessment of the continued resilience of the financial system and strong financial policy frameworks. They appreciated the FSAP team’s comprehensive assessment and found the engagement useful to bring an additional perspective to their risk analysis, explore emerging issues, and discuss the evolution of their financial sector policy frameworks. While the authorities expressed some reservations on a few of the FSAP recommendations, they indicated their intent to consider all of them and agreed to publish the FSSA.

71. The authorities broadly agreed with the systemic risk assessment. They concurred that the Mexican financial system is robust and resilient to plausible future adverse shocks. As Mexico’s financial sector continues to face new challenges and grow in size, complexity, and interconnectedness, the authorities underscored their commitment to monitoring and containing emerging systemic risks in the context of their risk-based prudential oversight. They share the view that the policy framework performed well during the pandemic shock and are considering further analysis of potential system-wide liquidity risks, as new global shocks emerge. They agreed to consider the recommendation to further evaluate liquidity risk management in development banks, although they see it as a non-pressing issue, given that these entities are fully backed by the sovereign, thereby substantially reducing this risk. The climate risk analysis was useful but points to the need for further work given the high level of uncertainties ahead.

72. The authorities welcomed the assessment of the regulatory and supervisory framework which has supported positive outcomes on resilience. They flagged that the financial system had weathered well the COVID-19 shock, reflecting in part the agile policy responses during the pandemic, building on the good progress in strengthening financial sector policies. They note that the institutional arrangements supporting autonomy of the regulatory agencies are defined in organic legislation and the track record shows that supervisors and regulators operate with a high level of independence. They intend to continue to develop the risk-based supervisory framework and plan to issue an amended regulation on large exposures in 2022. The authorities also take note of the recommendations to improve the de jure application of the consolidated supervision framework, however, they noted that all D-SIBs provide regular information to the supervisors on a consolidated basis and each regulatory agency has powers over different entities (e.g., bank, insurer, and pension fund) that comprise a financial group, which de facto reduces the gap to consolidated supervision. They are committed to boosting cyber resilience and will continue to evaluate new areas, such as climate and fintech, including in the context of their digital payments strategy that is focused on promoting financial inclusion.

73. The authorities also welcomed the positive assessment of the liquidity management framework and progress on strengthening the crisis management and resolution frameworks. They have invested heavily in developing a globally state of the art liquidity management framework that was effectively deployed by Banxico to help contain risks during the massive pandemic shock. They have made advances with implementation of the new Basel standards, including the TLAC requirement. They viewed that their track-record of managing the few instances of failure in smaller financial institutions has shown that the framework works well, but are mindful of the need to keep constantly improving and updating matters given the evolving dynamics of the financial sector landscape.

^{Table 2.}

Mexico: Selected Economic and Financial Indicators

Sources: World Bank Development Indicators; Banxico; SHCP; CONEVAL; National Institute of Statistics and Geography; National Council of Population; and IMF staff estimates. 1/ CONEVAL uses a multi-dimensional approach to measuring poverty based on a “social deprivation index,” which considers the level of income; education; access to health services; to social security; to food; and quality, size, and access to basic services in the dwelling. 2/ Percent of population enrolled in primary school regardless of age as a share of the population of official primary education age. 3/ Contribution to growth. Excludes statistical discrepancy. 4/ Excludes goods procured in ports by carriers. 5/ Includes domestic credit by banks, nonbank intermediaries, and social housing funds. 6/ Data exclude state and local governments and include state-owned enterprises and development banks.

^{Table 3.}

Mexico: Monetary and Financial Sector Responses During the COVID-19 Crisis

Sources: Mexican authorities; and IMF staff.

^{Table 4.}

Mexico: Structure of Financial System

Sources: Mexican authorities; and IMF staff calculation.

^{^1/}FND: Financiera Nacional de Desarrollo Agropecuario, Rural, Forestal y Pesquero.

^{^2/}Infonavit: Instituto del Fondo Nacional de la Vivienda para los Trabajadores. The total assets are in the constant term for 2016.

^{^3/}Fovissste: Fondo de la Vivienda del Instituto de la Seguridad y Servicios Sociales de los Trabajadores del Estado.

^{^4/}Infonacot: Instituto del Fondo Nacional para el Consumo de los Trabajadores.

^{^5/}FOVI: Fondo de Operación y Financiamiento Bancario de la Vivienda.

^{^6/}FIRA: Fideicomisos Instituidos en Relación con la Agricultura.

^7/FIFOMI: Fideicomiso de Fomento Minero.

^{Table 4.}

Mexico: Structure of Financial System

	2016				2021
		Total Assets				Total Assets
	Number	In billions of Mexican pesos	In percent of finacial sector assets	In percent of GDP	Number	In billions of Mexican pesos	In percent of finacial sector assets	In percent of GDP
Commercial banks	47	8,668	48.1	43.1	50	11,078	43.8	42.2
Domestic banks	32	2,803	15.5	13.9	30	3,643	14.4	13.9
Foreign subsidiaries	15	5,865	32.5	29.1	20	7,435	29.4	28.3
D-SIBs	7	6,879	38.1	34.2	6	8,099	32.0	30.8
Domestic D-SIB	2	1,440	8.0	7.2	1	1,236	4.9	4.7
Five foreign D-SIBs	5	5,439	30.2	27.0	5	6,863	27.2	26.1
Development banks	6	1,796	10.0	8.9	6	2,279	9.0	8.7
Pension funds (Siefores)	73	2,754	15.3	13.7	117	5,236	20.7	19.9
Investment funds (Fondos de inversión)	578	2,047	11.4	10.2	613	2,795	11.1	10.6
Insurance and Surety (Seguros y fianzas)	115	1,358	7.5	6.7	113	2,005	7.9	7.6
Brokerage firms (Casas de bolsa)	36	486	2.7	2.4	36	862	3.4	3.3
Multiple objective finance companies (Sofomes)	1704	721	4.0	3.6	1129	709	2.8	2.7
Regulated sofomes	52	389	2.2	1.9	43	257	1.0	1.0
Unregulated sofomes	1652	332	1.8	1.6	1086	452	1.8	1.7
Cooperatives (Socaps)	151	118	0.7	0.6	153	212	0.8	0.8
Microfinance savings and loan entities (Sofipos)	43	31	0.2	0.2	37	35.6	0.1	0.1
Credit unions	85	55	0.3	0.3	77	59	0.2	0.2
Total	2,845	18,034	100.0	89.6	2,337	25,271	100.0	96.2
Memo:
Financial holding companies (FHCs)	10	6,546	36.3	32.5	15	8,798	34.8	33.5
Largest four FHCs	4	5,434	30.1	27.0	4	6,707	26.5	25.5
Development agencies	4	1,418	7.9	7.0	4	2,199	8.7	8.4
FND^1/	1	58	0.3	0.3	1	51	0.2	0.2
Infonavit^2/	1	1,182	6.6	5.9	1	1,882	7.4	7.2
Fovissste^3/	1	159	0.9	0.8	1	233	0.9	0.9
Infonacot^4/	1	19	0.1	0.1	1	33	0.1	0.1
Development trusts	3	170	0.9	0.8	3	227	0.9	0.9
FOVI^5/	1	21	0.1	0.1	1	17	0.1	0.1
FIRA^5/	1	144	0.8	0.7	1	204	0.8	0.8
FIFOMI^6/	1	5	0.0	0.0	1	6	0.0	0.0

Sources: Mexican authorities; and IMF staff calculation.

^{^1/}FND: Financiera Nacional de Desarrollo Agropecuario, Rural, Forestal y Pesquero.

^{^2/}Infonavit: Instituto del Fondo Nacional de la Vivienda para los Trabajadores. The total assets are in the constant term for 2016.

^{^3/}Fovissste: Fondo de la Vivienda del Instituto de la Seguridad y Servicios Sociales de los Trabajadores del Estado.

^{^4/}Infonacot: Instituto del Fondo Nacional para el Consumo de los Trabajadores.

^{^5/}FOVI: Fondo de Operación y Financiamiento Bancario de la Vivienda.

^{^6/}FIRA: Fideicomisos Instituidos en Relación con la Agricultura.

^7/FIFOMI: Fideicomiso de Fomento Minero.

^{Table 4.}

Mexico: Structure of Financial System

	2016				2021
		Total Assets				Total Assets
	Number	In billions of Mexican pesos	In percent of finacial sector assets	In percent of GDP	Number	In billions of Mexican pesos	In percent of finacial sector assets	In percent of GDP
Commercial banks	47	8,668	48.1	43.1	50	11,078	43.8	42.2
Domestic banks	32	2,803	15.5	13.9	30	3,643	14.4	13.9
Foreign subsidiaries	15	5,865	32.5	29.1	20	7,435	29.4	28.3
D-SIBs	7	6,879	38.1	34.2	6	8,099	32.0	30.8
Domestic D-SIB	2	1,440	8.0	7.2	1	1,236	4.9	4.7
Five foreign D-SIBs	5	5,439	30.2	27.0	5	6,863	27.2	26.1
Development banks	6	1,796	10.0	8.9	6	2,279	9.0	8.7
Pension funds (Siefores)	73	2,754	15.3	13.7	117	5,236	20.7	19.9
Investment funds (Fondos de inversión)	578	2,047	11.4	10.2	613	2,795	11.1	10.6
Insurance and Surety (Seguros y fianzas)	115	1,358	7.5	6.7	113	2,005	7.9	7.6
Brokerage firms (Casas de bolsa)	36	486	2.7	2.4	36	862	3.4	3.3
Multiple objective finance companies (Sofomes)	1704	721	4.0	3.6	1129	709	2.8	2.7
Regulated sofomes	52	389	2.2	1.9	43	257	1.0	1.0
Unregulated sofomes	1652	332	1.8	1.6	1086	452	1.8	1.7
Cooperatives (Socaps)	151	118	0.7	0.6	153	212	0.8	0.8
Microfinance savings and loan entities (Sofipos)	43	31	0.2	0.2	37	35.6	0.1	0.1
Credit unions	85	55	0.3	0.3	77	59	0.2	0.2
Total	2,845	18,034	100.0	89.6	2,337	25,271	100.0	96.2
Memo:
Financial holding companies (FHCs)	10	6,546	36.3	32.5	15	8,798	34.8	33.5
Largest four FHCs	4	5,434	30.1	27.0	4	6,707	26.5	25.5
Development agencies	4	1,418	7.9	7.0	4	2,199	8.7	8.4
FND^1/	1	58	0.3	0.3	1	51	0.2	0.2
Infonavit^2/	1	1,182	6.6	5.9	1	1,882	7.4	7.2
Fovissste^3/	1	159	0.9	0.8	1	233	0.9	0.9
Infonacot^4/	1	19	0.1	0.1	1	33	0.1	0.1
Development trusts	3	170	0.9	0.8	3	227	0.9	0.9
FOVI^5/	1	21	0.1	0.1	1	17	0.1	0.1
FIRA^5/	1	144	0.8	0.7	1	204	0.8	0.8
FIFOMI^6/	1	5	0.0	0.0	1	6	0.0	0.0

Sources: Mexican authorities; and IMF staff calculation.

^{^1/}FND: Financiera Nacional de Desarrollo Agropecuario, Rural, Forestal y Pesquero.

^{^2/}Infonavit: Instituto del Fondo Nacional de la Vivienda para los Trabajadores. The total assets are in the constant term for 2016.

^{^3/}Fovissste: Fondo de la Vivienda del Instituto de la Seguridad y Servicios Sociales de los Trabajadores del Estado.

^{^4/}Infonacot: Instituto del Fondo Nacional para el Consumo de los Trabajadores.

^{^5/}FOVI: Fondo de Operación y Financiamiento Bancario de la Vivienda.

^{^6/}FIRA: Fideicomisos Instituidos en Relación con la Agricultura.

^7/FIFOMI: Fideicomiso de Fomento Minero.

^{Table 5.}

Mexico: Foreign D-SIBs’ Contribution to the Group’s Profits

(In percent, 2020)

Sources: BBVA; Santander; Citi Group; HSBC; Scotiabank; and IMF staff calculation.

^{Table 5.}

Mexico: Foreign D-SIBs’ Contribution to the Group’s Profits

(In percent, 2020)

Foreign D-SIBs	Total Assets		Parent Banks	Home Country	Share of Total Assets in Mexico	Share of Gross Income from Mexico	Share of Net Profit from Mexico	Share of Employees in Mexico
Foreign D-SIBs	(In billions of Mexican pesos)	(In billions of U.S. Dollars)	Parent Banks	Home Country	(In percent)
BBVA Mexico	2,443.40	122.9	BBVA	Spain	14.7	30.5	44.6	29.8
Santander Mexico	1,855.80	93.4	Banco Santander	Spain	5.3	8.2	11.2	11.3
Citibanamex	1,357.10	68.3	Citi	U.S.	3.7	8.5	n/a	n/a
HSBC Mexico	780	39.3	HSBC	U.K.	1.7	4.4	-2.1	n/a
Scotiabank Mexico	638.2	32.1	Scotiabank	Canada	5.1	7.6	5.1	n/a

Sources: BBVA; Santander; Citi Group; HSBC; Scotiabank; and IMF staff calculation.

^{Table 5.}

Mexico: Foreign D-SIBs’ Contribution to the Group’s Profits

(In percent, 2020)

Foreign D-SIBs	Total Assets		Parent Banks	Home Country	Share of Total Assets in Mexico	Share of Gross Income from Mexico	Share of Net Profit from Mexico	Share of Employees in Mexico
Foreign D-SIBs	(In billions of Mexican pesos)	(In billions of U.S. Dollars)	Parent Banks	Home Country	(In percent)
BBVA Mexico	2,443.40	122.9	BBVA	Spain	14.7	30.5	44.6	29.8
Santander Mexico	1,855.80	93.4	Banco Santander	Spain	5.3	8.2	11.2	11.3
Citibanamex	1,357.10	68.3	Citi	U.S.	3.7	8.5	n/a	n/a
HSBC Mexico	780	39.3	HSBC	U.K.	1.7	4.4	-2.1	n/a
Scotiabank Mexico	638.2	32.1	Scotiabank	Canada	5.1	7.6	5.1	n/a

Sources: BBVA; Santander; Citi Group; HSBC; Scotiabank; and IMF staff calculation.

^{Table 6.}

Mexico: Financial Soundness Indicators

(In percent, latest)

Sources: Mexican authorities; and IMF Financial Soundness Indicator.

^{Table 6.}

Mexico: Financial Soundness Indicators

(In percent, latest)

	2016	2017	2018	2019	2020	2021	2022 Q2
Capital Adequacy
Regulatory capital to risk-weighted assets	14.9	15.6	15.9	16.0	17.7	19.5	18.7
Regulatory Tier 1 capital to risk-weighted assets	13.2	14.2	14.2	14.4	16.1	18.1	17.3
Capital to assets	9.9	10.4	10.7	11.0	10.7	11.8	10.8
Asset Quality
Nonperforming loans to total gross loans	2.1	2.1	2.1	2.1	2.4	2.0	2.3
Provisions to Nonperforming loans	157.1	154.9	152.4	146.2	160.1	160.5	143.4
Earnings and Profitability
Return on assets	1.7	2.0	2.2	2.2	1.2	2.1	1.9
Return on equity	16.3	19.6	20.9	20.5	11.7	18.6	17.4
Interest margin to gross income	73.8	73.3	74.5	74.3	76.0	72.7	76.0
Trading income to total income	4.4	5.0	4.5	5.8	5.5	6.7	9.4
Liquidity
Liquid assets to total assets	31.4	32.0	31.6	31.1	35.7	36.3	38.5
Liquid assets to short-term liabilities	42.4	42.2	42.3	40.8	48.0	47.0	49.8
Customer deposits to total loans, excluding interbank loans	88.9	91.4	89.3	90.7	100.2	105.2	99.5
Net open position in foreign exchange to capital	0.8	1.1	1.2	2.9	1.8	0.1	2.2

Sources: Mexican authorities; and IMF Financial Soundness Indicator.

^{Table 6.}

Mexico: Financial Soundness Indicators

(In percent, latest)

	2016	2017	2018	2019	2020	2021	2022 Q2
Capital Adequacy
Regulatory capital to risk-weighted assets	14.9	15.6	15.9	16.0	17.7	19.5	18.7
Regulatory Tier 1 capital to risk-weighted assets	13.2	14.2	14.2	14.4	16.1	18.1	17.3
Capital to assets	9.9	10.4	10.7	11.0	10.7	11.8	10.8
Asset Quality
Nonperforming loans to total gross loans	2.1	2.1	2.1	2.1	2.4	2.0	2.3
Provisions to Nonperforming loans	157.1	154.9	152.4	146.2	160.1	160.5	143.4
Earnings and Profitability
Return on assets	1.7	2.0	2.2	2.2	1.2	2.1	1.9
Return on equity	16.3	19.6	20.9	20.5	11.7	18.6	17.4
Interest margin to gross income	73.8	73.3	74.5	74.3	76.0	72.7	76.0
Trading income to total income	4.4	5.0	4.5	5.8	5.5	6.7	9.4
Liquidity
Liquid assets to total assets	31.4	32.0	31.6	31.1	35.7	36.3	38.5
Liquid assets to short-term liabilities	42.4	42.2	42.3	40.8	48.0	47.0	49.8
Customer deposits to total loans, excluding interbank loans	88.9	91.4	89.3	90.7	100.2	105.2	99.5
Net open position in foreign exchange to capital	0.8	1.1	1.2	2.9	1.8	0.1	2.2

Sources: Mexican authorities; and IMF Financial Soundness Indicator.

^{Table 7.}

Mexico: Commercial Bank Loans Under Deferred Loan Category

Sources: Banxico; CNBV; and IMF staff calculation.

^{^1/}The official name of the deferred loan category is Special Accounting Criteria. CNBV issued accounting flexibilities for credit institutions that helped to provide payment facilities to clients who had taken commercial, consumer, and housing loans. In general terms, the payment facilities consisted of the partial or total deferral of principal and interest payments for up to 4 months, with a possibility of extending it for two additional months. Credits were eligible for this support program provided they were fully performing as of March 31, 2020.

^{Table 8.}

Mexico: FSAP Stress Test Scenarios

Source: IMF staff calculation.

^{Table 8.}

Mexico: FSAP Stress Test Scenarios

	2021	2022	2023	2024
Real GDP (2021=100)
Baseline	100.0	102.4	104.6	106.0
Adverse	100.0	97.5	93.9	98.3
Real GDP Growth Rate (In percent, y-o-y)
Baseline	4.8	2.4	2.2	1.4
Adverse	4.8	-2.5	-3.7	4.6
CPI Inflation Rate (In percent, y-o-y)
Baseline	5.7	7.2	4.4	3.3
Adverse	5.7	9.6	8.7	5.8
Exchange Rate (Mexican peso per U.S. dollar, end of period)
Baseline	20.6	21.4	21.6	21.9
Adverse	20.6	24.1	26.1	25.8
Policy Rate (In percent, year averages except 2021)
Baseline	5.5	7.9	9.1	8.1
Adverse	5.5	9.4	10.1	6.9
10-Year Sovereign Bond Yield (In percent, year averages except 2021)
Baseline	8.0	9.4	9.4	9.4
Adverse	8.0	10.9	11.2	10.2
Equity Prices (2021=100)
Baseline	100.0	106.7	113.3	119.7
Adverse	100.0	90.3	78.1	76.0
Price of Commodities (energy/oil, 2016 = 100)
Baseline	184.4	346.5	262.4	224.1
Adverse	184.4	443.9	258.8	191.9

Source: IMF staff calculation.

^{Table 8.}

Mexico: FSAP Stress Test Scenarios

	2021	2022	2023	2024
Real GDP (2021=100)
Baseline	100.0	102.4	104.6	106.0
Adverse	100.0	97.5	93.9	98.3
Real GDP Growth Rate (In percent, y-o-y)
Baseline	4.8	2.4	2.2	1.4
Adverse	4.8	-2.5	-3.7	4.6
CPI Inflation Rate (In percent, y-o-y)
Baseline	5.7	7.2	4.4	3.3
Adverse	5.7	9.6	8.7	5.8
Exchange Rate (Mexican peso per U.S. dollar, end of period)
Baseline	20.6	21.4	21.6	21.9
Adverse	20.6	24.1	26.1	25.8
Policy Rate (In percent, year averages except 2021)
Baseline	5.5	7.9	9.1	8.1
Adverse	5.5	9.4	10.1	6.9
10-Year Sovereign Bond Yield (In percent, year averages except 2021)
Baseline	8.0	9.4	9.4	9.4
Adverse	8.0	10.9	11.2	10.2
Equity Prices (2021=100)
Baseline	100.0	106.7	113.3	119.7
Adverse	100.0	90.3	78.1	76.0
Price of Commodities (energy/oil, 2016 = 100)
Baseline	184.4	346.5	262.4	224.1
Adverse	184.4	443.9	258.8	191.9

Source: IMF staff calculation.

^{Table 9.}

Mexico: Bank Liquidity Stress Test Results

Source: IMF staff calculation. Note: 1/ In the regulatory scenario, the LCR is computed by using the regulatory run-off and haircut rates. 2/ In the retail shock scenario, run-off rates on retail deposits are increased above the regulatory rates. 3/ In the wholesale shock scenario, run-off rates on wholesale deposits are increase above the regulatory rates.

Table 10.

Mexico and Selected Countries: Existing Macroprudential Instruments

Source: IMF staff. Note: 1/ there is no LCR requirement by currency but LCR by currency is monitored.

Table 10.

Mexico and Selected Countries: Existing Macroprudential Instruments

Country	Brazil	China	Colombia	India	Mexico	Russia	South Africa
Broad-Based Tools
Countercyclical capital buffer	yes	yes	no	yes	yes	yes	yes
Positive countercyclical capital buffer	no	no	no	no	no	no	no
Capital conservation buffer	yes	yes	yes	yes	yes	yes	yes
Limit on leverage ratio	yes	yes	yes	yes	yes	yes	yes
Forward-looking loan loss provisioning requirement	yes	yes	yes	no	yes	yes	yes
Cap on credit growth	no	no	no	no	no	no	no
Household Sector Tools
Household sector capital requirements	yes	no	no	yes	yes	yes	no
Cap on loan-to-value ratio	yes	yes	yes	yes	no	no	no
Cap on debt-service-to-income ratio	no	yes	yes	no	no	no	no
Restrictions on unsecured loans	no	no	no	no	no	no	no
Corporate Sector Tools
Corporate sector capital requirements	yes	no	no	yes	yes	yes	no
Cap on loan-to-value ratio for CRE	no	yes	no	no	no	no	no
Liquidity Tools
Liquidity Coverage Ratio	yes	yes	yes	yes	yes	yes	yes
• Differentiated by currency^1/	no	no	yes	yes	no	no	no
Net Stable Funding Ratio	yes	yes	yes	no	yes	yes	yes
Reserve requirements for macroprudential purposes	yes	yes	no	no	no	yes	no
• Differentiated by currency	no	yes	no	no	no	yes	no
Limits on foreign exchange positions	yes	yes	yes	yes	yes	yes	yes
Net foreign exchange positions	yes	yes	yes	yes	yes	yes	yes
Structural Tools
Capital surcharges for G-SIFIs or D-SIFIs	yes	yes	yes	yes	yes	yes	yes
Limits on the size of exposures between financial institutions	no	yes	yes	yes	yes	yes	no
Measures to mitigate risks from financial institutions' exposures to sovereigns	no	yes	no	no	yes	no	no

Source: IMF staff. Note: 1/ there is no LCR requirement by currency but LCR by currency is monitored.

Table 10.

Mexico and Selected Countries: Existing Macroprudential Instruments

Country	Brazil	China	Colombia	India	Mexico	Russia	South Africa
Broad-Based Tools
Countercyclical capital buffer	yes	yes	no	yes	yes	yes	yes
Positive countercyclical capital buffer	no	no	no	no	no	no	no
Capital conservation buffer	yes	yes	yes	yes	yes	yes	yes
Limit on leverage ratio	yes	yes	yes	yes	yes	yes	yes
Forward-looking loan loss provisioning requirement	yes	yes	yes	no	yes	yes	yes
Cap on credit growth	no	no	no	no	no	no	no
Household Sector Tools
Household sector capital requirements	yes	no	no	yes	yes	yes	no
Cap on loan-to-value ratio	yes	yes	yes	yes	no	no	no
Cap on debt-service-to-income ratio	no	yes	yes	no	no	no	no
Restrictions on unsecured loans	no	no	no	no	no	no	no
Corporate Sector Tools
Corporate sector capital requirements	yes	no	no	yes	yes	yes	no
Cap on loan-to-value ratio for CRE	no	yes	no	no	no	no	no
Liquidity Tools
Liquidity Coverage Ratio	yes	yes	yes	yes	yes	yes	yes
• Differentiated by currency^1/	no	no	yes	yes	no	no	no
Net Stable Funding Ratio	yes	yes	yes	no	yes	yes	yes
Reserve requirements for macroprudential purposes	yes	yes	no	no	no	yes	no
• Differentiated by currency	no	yes	no	no	no	yes	no
Limits on foreign exchange positions	yes	yes	yes	yes	yes	yes	yes
Net foreign exchange positions	yes	yes	yes	yes	yes	yes	yes
Structural Tools
Capital surcharges for G-SIFIs or D-SIFIs	yes	yes	yes	yes	yes	yes	yes
Limits on the size of exposures between financial institutions	no	yes	yes	yes	yes	yes	no
Measures to mitigate risks from financial institutions' exposures to sovereigns	no	yes	no	no	yes	no	no

Source: IMF staff. Note: 1/ there is no LCR requirement by currency but LCR by currency is monitored.

Annex I. Credit and Market Risks in Development Banks and Top Twenty Nonbank Credit Institutions

CNBV has analyzed credit and market risks for all commercial banks, development banks, and non-bank credit institutions under the FSAP adverse scenario.¹ This collaboration has allowed the FSAP to partially expand the solvency stress tests (Section IV. A) by assessing the impact on credit and market risk for all six development banks and the twenty largest non-bank credit institutions.

The results show that the impact of market and credit risks is limited under the adverse scenario. Market risk is contained and driven mainly by the revaluation of bonds and the impact on P&L from derivatives’ exposures for both commercial and development banks (Figure 24). Non-bank credit institutions do not have material market risk exposures in their portfolio. Reflecting the different credit quality of the loan portfolios, credit losses under the adverse scenario would be higher for development banks and non-bank credit institutions than commercial banks.

Annex II. Organization of the MFAs

Interlocking boards. CNBV’s Board consists of ex officio officials, with five out of 13 members appointed by SHCP (Figure 25). IPAB’s Board comprises three ex officio officials—the finance minister (chair), the Banxico governor, and the CNBV president—and four independent members. The finance minister and deputy finance minister are not members of Banxico’s Governing Board but may participate in its sessions without a vote. SHCP does not have a Board.
The Financial System Stability Council (CESF). The CESF has an explicit, formal mandate to promote the stability of the financial system. It comprises nine voting members: the finance minister (Chair) and the deputy minister; the Banxico governor and two deputy governors; the heads of three supervisors (CNBV, CNSF, CONSAR); and the chief executive of IPAB. It makes formal recommendations, coupled with a de facto comply-or-explain mechanism, to mitigate systemic risks over the medium term. Although there is a formal voting arrangement, CESF’s recommendations have been decided by consensus and fully implemented by the members. Banxico plays a strong role as its secretariat. The CESF communicates through quarterly press releases and an annual report, separately from Banxico’s Financial Stability Report (FSR).
The Banking Stability Committee (CEB). The CEB is a platform where the authorities decide on the systemicness of a failing bank and, should a determination of systemic impact be made, the extent to which liabilities be protected in resolution. It determines the resolution options and gives direction to their use by IPAB. It comprises eight voting members: the finance minister (Chair) and the deputy minister; the Banxico governor and a deputy governor appointed by the governor; the CNBV president and the vice president overseeing CNBV; and the chief executive of IPAB and an IPAB board member.
The Banking Liquidity Regulation Committee (CRLB). The CRLB is a committee composed of SHCP, Banxico, and CNBV, to dictate the guidelines to establish the liquidity requirements for commercial banks and any amendments to the requirements. At the beginning of the COVID-19 shock, the CRLB met to establish temporary general exceptions to the Liquidity Provisions.

Appendix I. Implementation Status of Key Recommendations in the 2016 FSSA

Key Recommendations	Timeframe	Status
Institutional Arrangements and Governance
Integrate all prudential supervision aimed at the safety and soundness of financial institutions, in one Prudential Supervisor, covering banks, securities, insurance firms, pension funds and other financial institutions.	MT	Not implemented. The organizational architecture for financial system oversight remains as it was in 2016. The authorities consider there is no need to change the current supervisory architecture, since coordination and cooperation arrangements in place among authorities, reinforced by the oversight of the Financial System Stability Council (CESF), are effective for financial stability purposes. The CESF makes formal recommendations, coupled with a de facto comply-or-explain mechanism.
Amend relevant laws to (a) clearly establish financial stability as the primary objective for the new supervisor, other objectives (e.g., development) are secondary and should be narrowly defined; and (b) strengthen the governance of the supervisor and IPAB (e.g., composition of governing boards and the appointment and dismissal of senior personnel) and ensure their supervisory and budgetary independence.	MT	Not implemented. Full political and budgetary autonomy are still missing. The institutional governance arrangements remains as it was in 2016, thus supervisors´ budgets are still determined by SHCP. Likewise, the heads of the Commissions are appointed by the Executive Branch, via the Minister of Finance. For IPAB, the Banks Savings Protection Law establishes that the Government Board has the power and duty to appoint, upon proposal of at least two of its directors, the Institute’s Executive Secretary.
Financial Stability Policy Framework
Establish more clearly the status of the CESF as the preeminent voice of its members regarding the assessment of financial stability risks.	ST	Partially implemented. The macroprudential mandate is shared among various agencies, including the Ministry of Finance and Public Credit, Banxico, regulatory and supervisory agencies, and IPAB. They coordinate in the macroprudential issues within the Financial System Stability Council (CESF). The CESF makes formal recommendations, coupled with a de facto comply-or-explain mechanism. The CESF communicates its coordinated risk assessments and policy intentions through quarterly press releases and an annual report on the stability of the financial system
Financial Sector Oversight
Adopt a consolidated supervision framework that corrects for legal gaps on CNBV’s ability to perform consolidated supervision and strengthen the regulatory reporting framework for related party lending.	ST	Not Implemented. Although some efforts to better understand financial groups´ activities and risks have been introduced, the current legal and regulatory framework falls short of creating conditions for effective consolidated supervision.
The corporate governance of development banks should be revised in line with international best practices in some key areas such as the composition of board members and mechanisms for the election of CEOs.	ST	Not reviewed.
The definitions of “common risk” and “related party” should be enhanced, including explicit definition of “economic dependency” in exposures to corporations, provision for grouping loans that are collateralized by the same collateral, and explicit references to persons who, while not having a quantitative relationship with other borrowers, exercise significant control over them.	ST	Not yet Implemented. Amended regulations on large exposures have been delayed due to the COVID-19 outbreak and are expected to be issued by the second half of 2022. The revised regulation would include new definitions and revised limits for “common risk” and “related party” in accordance with Basel III standards and best practices.
Review the role of Banxico in determining certain capital requirements. CNBV, as the agency charged with the prudential supervision of banks, should assume sole responsibility for such function.	MT	Not yet Implemented. The authorities argue that all capital requirements fall under the CNBV domain. We need to better understand the recommendation. Banxico and CNBV are finalizing the guideline for countercyclical capital buffers.
Streamline the regulation and supervision of “other financial institutions” to facilitate and promote consolidation and integration.	MT	Not reviewed.
Deposit Insurance, Crisis Management, and Resolution
Transfer the legacy debt at IPAB to the sovereign balance sheet.	MT	Not Implemented. The legacy debt continues to weigh heavily on IPAB finances: each year 75 percent of banks’ contributions to IPAB are allocated to repay this debt. This debt is projected to be fully repaid in 2069. While IPAB has not set a formal target ratio for the FPAB, it is projected to stand at around 3.4 percent of insured deposits in 2027 and 5.1 percent in 2032. The modalities for IPAB borrowing from Banxico have not been worked out.
Adopt legislation removing bail out options for shareholders and subordinated debt holders of systemic banks.	NT	Implemented. IPAB has adopted internal procedures for the “Establishment, organization and operation of commercial banks by IPAB (Bridge Bank),” setting out the model corporate charter and model contracts for asset and liability transfers, and the provision of services; IPAB has also developed methodologies for valuations for purposes of a bridge bank. The ex-ante incorporation of a bridge bank without using it in the near term would be costly. IPAB’s 2016 systemic bank resolution simulation covered using bridge banks.
Develop formal contingency plans and simulation exercises to deal with a systemic crisis.	MT	Partially Implemented. While the MFAs individually undertake simulation exercises, there are no system-wide contingency plans, and no collective simulation exercise for a systemic event was undertaken since 2011. Preparations for an interagency crisis simulation were well advanced when it had to be postponed due to the COVID-19 outbreak. This exercise will test the MFAs’ response to a cybersecurity incident and the resulting financial fallout.
Development Banks
Revise the strategy and objectives for development banks targets to include indicators of financial inclusion and private sector crowding-in, eliminating quantitative targets.	ST	Implemented. SHCP published the National Development Financing Program 2020-2024 (PRONAFIDE 2020-2024) in the Official Gazette of the Federation (DOF), including a component aimed at generating greater financial inclusion through development banking. The Program aligns development banks’ priority objectives, strategies, lines of action and indicators to the pillars indicated in PRONAFIDE, thereby addressing financial inclusion, among other issues that they considered important for the attention of their target markets.
Pensions
Increase the contribution rates to fully funded pension schemes to ensure higher replacement rates and reduce fiscal risk.	ST	Implemented. The Mexican government has introduced several changes to guarantee higher replacement rates for Mexicans during retirement. One of the most important changes recently introduced was to increase the total contribution from 6.5 percent to 15 percent mainly through an increase in the employer’s contribution and to establish in the Constitution a non-contributory pension, granting universal economic support to all older adults. The latter means that all Mexicans automatically receive a pension when they reach sixty-five years old, which constitutes a social protection floor that guarantees a higher replacement rate for workers who contribute to their pension, as well as for those who do not.
Small and Medium-size Enterprise Finance
Create a credit registry to increase financial information available to lenders.	MT	Not implemented. There are three private credit bureaus which play an effective role in providing credit information to lenders. Regulated financial entities must report information to at least one of them, but non-regulated ones and commercial firms may also do so. Information is also sent by some public service or fiscal authorities (Federal Electricity Commission and the Tax Administration Service). Regulated entities include commercial banks, development banks, insurance institutions, surety institutions, public trusts, credit unions, savings and loans institutions, non-bank banks, microfinance companies, etc. While data may be fragmented in each credit bureau’s database, credit reports include consolidated data from all registries.

Key Recommendations	Timeframe	Status
Institutional Arrangements and Governance
Integrate all prudential supervision aimed at the safety and soundness of financial institutions, in one Prudential Supervisor, covering banks, securities, insurance firms, pension funds and other financial institutions.	MT	Not implemented. The organizational architecture for financial system oversight remains as it was in 2016. The authorities consider there is no need to change the current supervisory architecture, since coordination and cooperation arrangements in place among authorities, reinforced by the oversight of the Financial System Stability Council (CESF), are effective for financial stability purposes. The CESF makes formal recommendations, coupled with a de facto comply-or-explain mechanism.
Amend relevant laws to (a) clearly establish financial stability as the primary objective for the new supervisor, other objectives (e.g., development) are secondary and should be narrowly defined; and (b) strengthen the governance of the supervisor and IPAB (e.g., composition of governing boards and the appointment and dismissal of senior personnel) and ensure their supervisory and budgetary independence.	MT	Not implemented. Full political and budgetary autonomy are still missing. The institutional governance arrangements remains as it was in 2016, thus supervisors´ budgets are still determined by SHCP. Likewise, the heads of the Commissions are appointed by the Executive Branch, via the Minister of Finance. For IPAB, the Banks Savings Protection Law establishes that the Government Board has the power and duty to appoint, upon proposal of at least two of its directors, the Institute’s Executive Secretary.
Financial Stability Policy Framework
Establish more clearly the status of the CESF as the preeminent voice of its members regarding the assessment of financial stability risks.	ST	Partially implemented. The macroprudential mandate is shared among various agencies, including the Ministry of Finance and Public Credit, Banxico, regulatory and supervisory agencies, and IPAB. They coordinate in the macroprudential issues within the Financial System Stability Council (CESF). The CESF makes formal recommendations, coupled with a de facto comply-or-explain mechanism. The CESF communicates its coordinated risk assessments and policy intentions through quarterly press releases and an annual report on the stability of the financial system
Financial Sector Oversight
Adopt a consolidated supervision framework that corrects for legal gaps on CNBV’s ability to perform consolidated supervision and strengthen the regulatory reporting framework for related party lending.	ST	Not Implemented. Although some efforts to better understand financial groups´ activities and risks have been introduced, the current legal and regulatory framework falls short of creating conditions for effective consolidated supervision.
The corporate governance of development banks should be revised in line with international best practices in some key areas such as the composition of board members and mechanisms for the election of CEOs.	ST	Not reviewed.
The definitions of “common risk” and “related party” should be enhanced, including explicit definition of “economic dependency” in exposures to corporations, provision for grouping loans that are collateralized by the same collateral, and explicit references to persons who, while not having a quantitative relationship with other borrowers, exercise significant control over them.	ST	Not yet Implemented. Amended regulations on large exposures have been delayed due to the COVID-19 outbreak and are expected to be issued by the second half of 2022. The revised regulation would include new definitions and revised limits for “common risk” and “related party” in accordance with Basel III standards and best practices.
Review the role of Banxico in determining certain capital requirements. CNBV, as the agency charged with the prudential supervision of banks, should assume sole responsibility for such function.	MT	Not yet Implemented. The authorities argue that all capital requirements fall under the CNBV domain. We need to better understand the recommendation. Banxico and CNBV are finalizing the guideline for countercyclical capital buffers.
Streamline the regulation and supervision of “other financial institutions” to facilitate and promote consolidation and integration.	MT	Not reviewed.
Deposit Insurance, Crisis Management, and Resolution
Transfer the legacy debt at IPAB to the sovereign balance sheet.	MT	Not Implemented. The legacy debt continues to weigh heavily on IPAB finances: each year 75 percent of banks’ contributions to IPAB are allocated to repay this debt. This debt is projected to be fully repaid in 2069. While IPAB has not set a formal target ratio for the FPAB, it is projected to stand at around 3.4 percent of insured deposits in 2027 and 5.1 percent in 2032. The modalities for IPAB borrowing from Banxico have not been worked out.
Adopt legislation removing bail out options for shareholders and subordinated debt holders of systemic banks.	NT	Implemented. IPAB has adopted internal procedures for the “Establishment, organization and operation of commercial banks by IPAB (Bridge Bank),” setting out the model corporate charter and model contracts for asset and liability transfers, and the provision of services; IPAB has also developed methodologies for valuations for purposes of a bridge bank. The ex-ante incorporation of a bridge bank without using it in the near term would be costly. IPAB’s 2016 systemic bank resolution simulation covered using bridge banks.
Develop formal contingency plans and simulation exercises to deal with a systemic crisis.	MT	Partially Implemented. While the MFAs individually undertake simulation exercises, there are no system-wide contingency plans, and no collective simulation exercise for a systemic event was undertaken since 2011. Preparations for an interagency crisis simulation were well advanced when it had to be postponed due to the COVID-19 outbreak. This exercise will test the MFAs’ response to a cybersecurity incident and the resulting financial fallout.
Development Banks
Revise the strategy and objectives for development banks targets to include indicators of financial inclusion and private sector crowding-in, eliminating quantitative targets.	ST	Implemented. SHCP published the National Development Financing Program 2020-2024 (PRONAFIDE 2020-2024) in the Official Gazette of the Federation (DOF), including a component aimed at generating greater financial inclusion through development banking. The Program aligns development banks’ priority objectives, strategies, lines of action and indicators to the pillars indicated in PRONAFIDE, thereby addressing financial inclusion, among other issues that they considered important for the attention of their target markets.
Pensions
Increase the contribution rates to fully funded pension schemes to ensure higher replacement rates and reduce fiscal risk.	ST	Implemented. The Mexican government has introduced several changes to guarantee higher replacement rates for Mexicans during retirement. One of the most important changes recently introduced was to increase the total contribution from 6.5 percent to 15 percent mainly through an increase in the employer’s contribution and to establish in the Constitution a non-contributory pension, granting universal economic support to all older adults. The latter means that all Mexicans automatically receive a pension when they reach sixty-five years old, which constitutes a social protection floor that guarantees a higher replacement rate for workers who contribute to their pension, as well as for those who do not.
Small and Medium-size Enterprise Finance
Create a credit registry to increase financial information available to lenders.	MT	Not implemented. There are three private credit bureaus which play an effective role in providing credit information to lenders. Regulated financial entities must report information to at least one of them, but non-regulated ones and commercial firms may also do so. Information is also sent by some public service or fiscal authorities (Federal Electricity Commission and the Tax Administration Service). Regulated entities include commercial banks, development banks, insurance institutions, surety institutions, public trusts, credit unions, savings and loans institutions, non-bank banks, microfinance companies, etc. While data may be fragmented in each credit bureau’s database, credit reports include consolidated data from all registries.

Appendix II. Risk Assessment Matrix

Source: IMF staff.

Sources of risks	Relative likelihood	Impact and transmission channels
Commodity price shocks due to the Russia’s war in Ukraine and geopolitical tensions Commodity prices are volatile and trend up amid supply constraints and the Russia’s war in Ukraine, keeping inflationary pressure upward.	High	Medium Pressure on inflation and inflation expectations due to rising energy and food prices. Deterioration of current account, exchange rate pressure and purchase power. Prompting Banxico to tighten policies faster than anticipated, causing an increase in funding costs.
De-anchoring of inflation expectations and stagflation and abrupt global slowdown or recession Worsening supply-demand imbalances, higher commodity prices and higher nominal wage growth lead to persistently higher inflation and/or inflation expectations, prompting central banks to tighten policies faster than anticipated, resulting in a hard landing globally, housing market correction, and a stronger U.S. dollar.	Medium	High Rising the U.S. interest rates pressuring sovereign and corporate funding costs. A reassessment of market fundamentals causing a widespread risk-off event in the global financial markets, capital outflows from Mexico, currency depreciation, and liquidity stress. Financing difficulties to the sovereign, resulting in higher sovereign credit spreads and material mark-to-market revaluation and associated losses. Higher funding cost leading to sharp deterioration of financial condition of corporate borrowers and associated credit quality. A wave of bankruptcies and devaluation of debt securities eroding bank capital buffers. Transmission of the hard landing to Mexico through reduced external demand and remittances.
Local COVID-19 outbreaks of lethal and highly contagious variants Rapidly increasing hospitalizations and deaths due to low vaccine protection or vaccine-resistant variants force more social distancing and/or new lockdowns.	Medium	Medium Renewed costly containment efforts, including broad-based lockdowns resulting in economic contraction, financial market turmoil, high unemployment, and corporate distress. A reassessment of growth prospects, triggering capital outflows, financial tightening, notable currency depreciations. Extended supply chain disruptions and inflationary pressures.
Increasing frequency and severity of climate events Natural disasters can lead to severe physical damages and losses to the economy in terms of capital stock destructions, productivity losses, business interruption, and affect the financial sector.	Medium	Medium Economic damages from frequent and severe climate events, e.g., tropical cyclones/hurricanes, floods. Deterioration of financial conditions of households and corporates leading to large credit losses in the financial sector, amplified by productivity losses and collateral devaluations. The global and domestic decarbonization efforts to mitigate the impact of climate change, leading to side-effects, i.e., transition risks to the financial sector depending on the global/domestic policy ambitions and degree of exposures to the carbon intensive firms and industries.
Cyberthreats	Medium	Medium Cyber-attacks on critical infrastructure and interconnected financial systems that trigger systemic financial instability or widely disrupt socio-economic activities and remote work arrangements.

Source: IMF staff.

Sources of risks	Relative likelihood	Impact and transmission channels
Commodity price shocks due to the Russia’s war in Ukraine and geopolitical tensions Commodity prices are volatile and trend up amid supply constraints and the Russia’s war in Ukraine, keeping inflationary pressure upward.	High	Medium Pressure on inflation and inflation expectations due to rising energy and food prices. Deterioration of current account, exchange rate pressure and purchase power. Prompting Banxico to tighten policies faster than anticipated, causing an increase in funding costs.
De-anchoring of inflation expectations and stagflation and abrupt global slowdown or recession Worsening supply-demand imbalances, higher commodity prices and higher nominal wage growth lead to persistently higher inflation and/or inflation expectations, prompting central banks to tighten policies faster than anticipated, resulting in a hard landing globally, housing market correction, and a stronger U.S. dollar.	Medium	High Rising the U.S. interest rates pressuring sovereign and corporate funding costs. A reassessment of market fundamentals causing a widespread risk-off event in the global financial markets, capital outflows from Mexico, currency depreciation, and liquidity stress. Financing difficulties to the sovereign, resulting in higher sovereign credit spreads and material mark-to-market revaluation and associated losses. Higher funding cost leading to sharp deterioration of financial condition of corporate borrowers and associated credit quality. A wave of bankruptcies and devaluation of debt securities eroding bank capital buffers. Transmission of the hard landing to Mexico through reduced external demand and remittances.
Local COVID-19 outbreaks of lethal and highly contagious variants Rapidly increasing hospitalizations and deaths due to low vaccine protection or vaccine-resistant variants force more social distancing and/or new lockdowns.	Medium	Medium Renewed costly containment efforts, including broad-based lockdowns resulting in economic contraction, financial market turmoil, high unemployment, and corporate distress. A reassessment of growth prospects, triggering capital outflows, financial tightening, notable currency depreciations. Extended supply chain disruptions and inflationary pressures.
Increasing frequency and severity of climate events Natural disasters can lead to severe physical damages and losses to the economy in terms of capital stock destructions, productivity losses, business interruption, and affect the financial sector.	Medium	Medium Economic damages from frequent and severe climate events, e.g., tropical cyclones/hurricanes, floods. Deterioration of financial conditions of households and corporates leading to large credit losses in the financial sector, amplified by productivity losses and collateral devaluations. The global and domestic decarbonization efforts to mitigate the impact of climate change, leading to side-effects, i.e., transition risks to the financial sector depending on the global/domestic policy ambitions and degree of exposures to the carbon intensive firms and industries.
Cyberthreats	Medium	Medium Cyber-attacks on critical infrastructure and interconnected financial systems that trigger systemic financial instability or widely disrupt socio-economic activities and remote work arrangements.

Source: IMF staff.

Appendix III. Stress Testing Matrix (STeM)

Domain		Top-down Stress Test by FSAP Team—Assumptions
Banking Sector: Solvency Risk
1. Institutional Perimeter	Institutions included	All D-SIBs (6 banks) and other important banks (4 additional mid-tier commercial banks for top-down (TD) ST at the highest level of consolidation.
	Market share	For the 10 commercial banks within scope, approximately 84 percent of banking sector assets.
	Data Source and Baseline Date	Banxico’s regulatory returns and supervisory data. Historical data on bank parameters based on Banxico’s statistical data warehouse. Balance sheet and financial statement data available in the public domain. Moody’s Analytics: CreditEdge data on corporate default probabilities. Data as of December 2021 (cut-off). End-2019 data might also be used for comparisons and sensitivity analysis purposes. Scope of financial consolidation: group-wide at the domestic level.
2. Channels of Risk Propagation	Methodology	Balance sheet approach. Projections of key balance sheet, income statement and capital account items. Static balance sheet assumption. Credit risk, market risk, net interest income and non-interest income projections are produced for all banks within scope for two scenarios: baseline and macro adverse. Granular projections of credit risk parameters are performed, including probabilities of default (PDs) losses given default (LGDs) for each asset class. Five different loan segments are used: corporates, mortgages, financials, government, and consumer credit. Segmentation is based on current prudential rules and availability of historical data for the estimation of satellite models. PD PIT satellites are based on historical data series of PDs for the system and by individual bank. LGD PiTs were produced for each loan segment by applying the Frye-Jakobs method. Net interest income is projected based on its sensitivity to macrofinancial conditions for both reference rates and effective spread margins across all interest rate sensitive asset and liability segments. Liability reference and margin rate shocks are linked to the macroeconomic scenario and econometric models are used to estimate pass-through rates for both asset and liability sides together with scenario anchored assumptions. The impact on P&L and OCI due to FVTPL and FVOCI positions is also estimated as part of the market risk impact. Market risk is based on the estimation of FV and OCI impact on the securities portfolios. The impact of the scenario on mutual fund, equity and FX exposures will also be measured. Net fee and commission income are stressed based on its historical volatility in combination with haircuts based on a conservative methodology reflecting the conditions prevailing the scenario narrative. Operational expenses over total assets are kept at the same level as in 2021 (cut-off). RWAs are adjusted to reflect changes in the quality of credit exposures.
	Satellite models for macro-financial linkages	Several satellite model estimation alternatives are explored: PD PIT models for each segment based on country aggregate historical PD time series and scenario translation of bank-specific starting points in the distance to default space. Bayesian Model Averaging (BMA) techniques are used to control for model uncertainty, Panel PD PIT econometric estimation models on bank-specific historical PD PIT time series using BMA techniques to control for model uncertainty, Moody’s EDF data series may also be explored for the calibration of econometric satellites for the corporate segments. Cross-sector country proxies could also be used for the projection of parameters where a direct calibration is not feasible due to data constraints (e.g., governments and financials may be proxied using corporate PD paths).
	Stress test horizon	Three years (2022 Q1 – 2024 Q4).
3. Tail Shocks	Scenario analysis	Based on two macroeconomic and financial scenarios (baseline and macro adverse). The scenarios specify key macrofinancial variables (e.g., real GDP growth, inflation rate, unemployment rates, exchange rates, equity prices, house prices, interest rates and credit growth) for Mexico, as well as global variables (e.g., oil and other commodity prices). The baseline scenario is based on April 2022 World Economic Outlook (WEO) projections. The macro adverse scenario is calibrated using the Global Macrofinancial Model (GFM) model and it assumes the materialization of the systemic risks highlighted in the RAM. The adverse scenario features a protracted global COVID-19 pandemic and supply-side disruptions that lead to higher inflation. The scenario assumes that supply-side disruptions and higher commodity prices continue to weigh on the global economy, which brings out a difficult trade-off between output and inflation for policymakers. Inflation in major economies including the U.S. surprises on the upside, and the Fed tightens monetary policy faster than expected, by about one percentage point within the first year. Higher U.S. interest rates and tighter financial conditions globally trigger capital outflows, depreciations, and higher long-term interest rates in emerging markets. The domestic layer introduces additional confidence shocks that applies downward pressure on domestic demand with subdued consumption and investment aggravating the sharp correction on both real estate and equity prices. These losses, most of which are absorbed by the banking system, subsequently curtail banks’ profitability, and prompt a broad-based tightening in the interbank market, echoing market concerns towards banks’ financial soundness. Finally, monetary policy is assumed to maintain its accommodative stance under the domestic layer and short-term interest rates are assumed to decrease towards the 4 percent effective lower bound. In terms of severity, the adverse scenario features a deviation of Mexico real GDP from its baseline of 11.3 percent by 2023, with a 2.3 Standard Deviation move in two-year cumulative real GDP growth rate, a 6.3 percent increase in unemployment rate from its baseline.
3. Tail Shocks	Sensitivity analysis	The impact of triggering credit lines to NFCs and financial entities will be covered by targeted sensitivity analysis. A more pronounced interest rate shift will also be captured by the solvency sensitivity analysis. A partial credit and market risk analysis exercise on Development banks and the twenty largest credit-providing NBFIs are attempted to increase the coverage of the solvency analysis. The FSAP adverse macroeconomic scenario is used to produce top-down estimates for PDs and LGDs for these entities using CNBV’s TD models and infrastructure. Market risk impact will also be simulated using data and models developed internally at CNBV.
4. Risks and Buffers	Risks/factors assessed	Credit risk captures all on-balance/off-balance sheet exposures at amortized cost by regulatory exposure sector. Exposures are largely domestic; therefore, no scenarios and parameter paths would be required for geographies outside Mexico. Market risk is reflected in valuation effects of FVTPL and FVOCI positions, as well as net open financial positions (i.e., equities, funds, and inflation-linked instruments exposures). Scenario-based Interest rate curves are used to infer reference interest rate changes. The adverse macro scenario is further augmented to include financial variables that are needed to produce accurate projections for fair value positions (like corporate spread rate shock or bank issued bonds spread shock). Net interest income is affected by projecting effective interest rates by asset/liability class. Policy rates and wholesale/interbank rates will directly follow the macroeconomic scenario paths and a panel econometric approach will be used to define the velocity of passthrough rates to all remaining asset and liability segments. Shocks to non-interest income are simulated to capture varying degrees of market-sensitive components of non-interest income. Projected RWA densities are also capturing a twofold impact: deterioration of credit quality and partial/full unwinding of relevant policy support measures.
4. Risks and Buffers	Behavioral adjustments	Under the static balance sheet assumption exposures remain constant and do not evolve in accordance with credit growth assumptions of scenarios. For NII, maturing assets/liabilities are assumed to be replaced by instruments of the same type, maturity but at current rates. There is no recognized interest on non-performing exposures. If banks’ capital falls below regulatory requirements, no prompt corrective action is assumed. Banks are assumed to pay 30 percent of their profits as tax. Dividend payout ratio is assumed to be the maximum of 40 percent or the payout ratio of the cut-off year unless the capital conservation buffer falls below 2.5 percent.
5. Regulatory and Market Based Standards and Parameters	Calibration of risk parameters	Currently the banking system is regulated under a full Basel III prudential framework. Accounting provisions are set by CNBV regulations (IFRS 9 was only implemented in January 2022 and CNBV has the mandate to set requirements for the accounting loan loss provisioning). In this context the stress test analysis will follow regulatory definitions of PDs and LGDs where applicable. Currently credit exposure portfolios are under the Standardized (STA) and the Advanced Internal Rating Based (A-IRB) regulatory approach. Risk-weighted asset densities are either assumed to remain constant for STA portfolios and following the PD PIT path (making use of a smoothening factor for the TTC effect).
5. Regulatory and Market Based Standards and Parameters	Regulatory/accounting and market-based standards	In the baseline, hurdle rates include the regulatory minimum (CET1: 4.5 percent, Tier1: 6 percent, Total Capital: 8 percent) and any applicable capital buffers (CCB, D-SIB surcharge, P2R). D-SIB charge ranges from 0.6 percent to 1.5 percent for the banks within scope. In the adverse scenario, the regulatory minimum (including D-SIB surcharge and P2R) is assumed to be the hurdle rate, as banks can draw down the CCB. Note that D-SIB surcharge is not considered as a buffer in Mexico. Hurdle rates are based on the CET1, Tier1, and Total Capital ratios.
6. Reporting Format for Results	Output presentation	System-wide evolution of aggregate CET1 and capital ratios. Distribution of banks’ capital positions Contribution to key drivers to system-wide net income and capital position, including differences between the baseline scenario and the adverse scenario. Share of institutions with capital below the hurdle rates.
Banking Sector: Liquidity Risk
1. Institutional Perimeter	Institutions included	The fifty commercial banks in Mexico at the highest level of consolidation.
	Market share	100 percent of commercial banking sector assets.
	Data and baseline date	Banxico’s regulatory reports monitoring the Liquidity Coverage Ratio and the Net Stable Funding Ratio and the additional (synthetically constructed) monitoring report capturing liquidity contractual maturity ladder. Data as of December 2021; December 2019 data will also be used to highlight the impacts of the pandemic on liquidity positions of banks. Scope of financial consolidation: group-wide at the highest level.
2. Channels of Risk Propagation	Methodology	The exercise is based on three types of tests—LCR test, cash-flow analysis and NSFR test. The LCR test is in line with the standard Banxico (and Basel compliant) monitoring tool, featuring total consolidated liquidity and liquidity in significant currencies (mainly USD). A set of scenarios for LCR outflows and HQLA haircuts is used to produce stressed LCR ratios (by currency and at the consolidated level). For the LCR test, the stress test horizon is 30 days. The cash-flow analysis analyzes the net cash balance (as a proxy of banks’ resiliency to liquidity stress events), accounting for available unencumbered assets, contractual cash inflows and outflows, and behavioral flows. For the cash-flow analysis, a range of scenarios featuring funding run-off rates, liquid assets haircuts and assumptions on inflows and outflows of increased severity for different durations of liquidity stress are explored (a stress-horizon of 3 months is used as the central assumption). Positive counterbalancing capacity post-scenario implies bank resiliency, negative is an indication of positive bank liquidity stress. For the cash-flow analysis, asset haircuts reflect two components: (i) shocks to interest rates and asset prices as captured the macrofinancial scenarios; and (ii) additional haircuts required by counterparties to accept specific assets as collateral for secured funding transactions. The NSFR became a binding requirement for Mexican banks in March 2022. For monitoring purposes, banks have been reporting NSFR calculations to competent authorities since 2017.
3. Risks and Buffers	Risks	Funding liquidity risk is reflected in funding run-off rates and asset roll-over rates, the latter providing cash inflows related to non-renewal of maturing assets. Market liquidity risk is reflected in asset haircuts, which could be influenced by market movements, potential fire sales and collateral supply considerations.
	Behavioral adjustments	Liquidity from the central bank’s emergency lending assistance (ELA) is not considered. Inflows from maturing loans are ignored (cash-flow analysis, after a certain level of scenario severity) capturing a systemic liquidity stress scenario vs a bank-idiosyncratic one. The cash-flow analysis may consider some behavioral assumptions about a counterparty’s ability or willingness to transact based on banks’ solvency and liquidity conditions.
4. Tail shocks	Scenario analysis	For the LCR test, 12 scenarios are considered as a combination of: (i) three scenarios on liquid assets shocks (regulatory, mild, and severe), and ii) four scenarios on liability outflows; regulatory, one reflecting retail outflows, one reflecting higher wholesale outflows, and one combining the retail and wholesale outflows. For the cash-flow analysis, a series of scenarios are considered, with a range from mild to severely adverse liquidity conditions. The cash-flow analysis considers both funding and market liquidity risks.
5. Regulatory and Market-Based Standards and Parameters	Calibration of risk parameters	LCR tests are based on regulatory and stress parameters. Cash-flow analysis may incorporate relevant second-round effects. Stress funding run-off rates, asset roll-over rates, and asset haircuts are calibrated based on empirical evidence and relevant international experiences.
5. Regulatory and Market-Based Standards and Parameters	Regulatory/accounting and market-based standards	LCR per Basel III; the hurdle at 100 percent. Net cash balance for the cash-flow analysis; to pass, a non-negative net cash balance is required, where the balance reflects net funding outflows and counterbalancing capacity. NSFR per Basel III; the hurdle at 100 percent.
6. Reporting Format for Results	Output presentation	Changes in the system-wide liquidity position, including important drivers for cash outflows, cash inflows and counterbalancing capacity. Distribution of banks’ liquidity positions. Number of institutions with LCR/NSFR below 100 percent and/or negative net cash balance. Amount of liquidity shortfalls, including by currencies.
7. Sensitivity Analysis	Output presentation	The analysis would cover policy support measures and will identify how such measures have impacted regulatory liquidity metrics. As a natural result, the analysis will also assess how the gradual measure unwinding will have affect liquidity positions of banks.
8. Infrastructure	Infrastructure used	For the LCR test, Banxico’s infrastructure to run the scenario developed by IMF staff and Banxico’s Liquidity at Risk tests. For cash flow analysis, fully comprehensive infrastructure developed by IMF staff using Banxico’s regulatory reports as a data repository. MATLAB and Excel based.
Climate Change: Physical Risk
1. Institutional Perimeter	Institutions included	Same set as in solvency stress test (10 largest commercial banks).
1. Institutional Perimeter	Data and baseline date	Sectoral exposure breakdown Source: Supervisory data Data as of December 2021 (cut-off)
2. Channels of Risk Propagation	Methodology	Climate scenario around tropical cyclones and/or floods based on history repeating and/or identification of future acute events reflecting climate change (subject to data/model availability), generating estimation of direct economic losses and damages, i.e., the physical capital damage rates (provided by the WB FSAP team). The adverse physical risk via capital damage rates is used as a layer of shock in a DSGE macro model. This also leads to persistent productivity shocks with additional considerations of investment adjustments costs and/or investment specific technological shocks, The underlying DSGE model is used to calibrate a full macroeconomic scenario.
3. Risks and Buffers	Risks	Credit channel risks are assumed (revised PD paths). All other channels are assumed to remain unaffected. Scenario dependent capital projections are produced based on the physical risk shock dependent PD paths.
3. Risks and Buffers	Buffers	Banks’ own capital
5. Reporting Format for Results	Output presentation	Delta PDs at the bank and system-wide level for corporate credit exposures. System-wide capital path projection under the physical risk scenarios (partial analysis, assuming only corporate credit risk, to be finalized). Comparison with the central baseline scenario. Bank-level capital impact and shortfalls.
Climate Change: Transition Risk
1. Institutional Perimeter	Institutions included	Same set as in solvency stress test (10 largest commercial banks).
1. Institutional Perimeter	Data and baseline date	Sectoral exposure breakdown Source: Supervisory data Firm-specific emission: from Urgentem. Firm balance sheets: DataStream and Capital IQ. Firm-specific historical default rates: Moody’s firm-level EDFs.
2. Channels of Risk Propagation	Methodology	Firm balance sheet stress approach. Step 1 (Bridge equation): establishing a relationship between firm-specific default rates and three firm level balance sheet indicators reflecting viability, liquidity, and solvency conditions (interest coverage ratio, current ratio and leverage ratio called vulnerability indicators). Firm sample restricted to listed companies with available historical default rate estimates. Step 2: Scenario dependent carbon prices and sectoral paths applied to firms’ balance sheets. Multi-year projections for balance sheet and profit components (forward-looking interest coverage ratio, current ratios, and leverage ratios) estimated via micro-simulations. Additional shocks, such as a sudden/unexpected large shift in market’s risk assessment are explored. Step 3: Elasticities from Step 1 are used to infer stressed default rates (using forward looking metrics from Step 2) for the sample of firms. Step 4: Weighted sectoral aggregates scenario dependent PDs are produced by aggregating firm level default rates and using total outstanding debt as weights. Step 5: Bank level sectoral corporate exposure breakdown is used to produce delta PDs using baseline and adverse default rates from Step 4. Step 6: Stressed delta PDs (reflecting transition risk) are fed to the standard solvency ST machinery to produce capital projections.
	Satellite models for macro-financial linkages	Bridge equation linking defaults rates to firm level vulnerability indicators: a fixed effects panel regression on historical firm level default rates; additional stochastic model to be explored for other shocks.
	Horizon	One to five years: multi-year projection of balance sheet dynamics and vulnerability indicators under transition scenarios.
3. Tail Shocks	Scenario analysis	Based on transition risk scenarios anchored to NGFS scenario categories and augmented to obtain sectoral output pathways via CGE model. Hot house world/business as usual is baseline with 1-2 adverse scenarios aligned to orderly and/or disorderly NGFS categories.
3. Risks and Buffers	Risks	Credit channel risks. All other channels are assumed to remain unaffected. Delta PDs relative to the baseline by bank is the envisaged outcome of the analysis.
5. Reporting Format for Results	Output presentation	Delta PDs by sector, by bank and (weighted) system-wide average. Bank-level capital impact and shortfalls (optional).
Financial System: Contagion Risk
1. Institutional Perimeter	Institutions included	All commercial and development banks, brokerage houses, investment and pension funds and the largest credit providing NBFIs (subject to data availability) in Mexico, at the highest level of consolidation
	Market share	Almost the entire system in terms of asset coverage
	Data and baseline date	Source: Supervisory data and ad-hoc data request Data as of December 2021 (random day cut-off, to avoid window dressing effects) BIS consolidated banking statistics, data as of end-Sept 2021
2. Channels of Risk Propagation	Methodology	Interbank and cross-border network model by Espinosa-Vega and Solé (2010)
3. Risks and Buffers	Risks	Credit and funding losses related to interbank/inter-entity cross-exposures (and cross-border banking exposures)
3. Risks and Buffers	Buffers	Banks’ and brokerage houses’ own capital buffers, other entities are not assumed to default in the simulation (internal loss absorption)
4. Tail shocks	Size of the shock	Pure contagion: default of individual institutions Several types of cross-entity exposures considered: secured, unsecured, crossholdings of debt instruments, settlement exposures. Different LGDs might be used, depending on exposure type. Simulation of multiple concurrent defaults may also be examined.
6. Reporting Format for Results	Output presentation	Contagion and vulnerability indicators System-wide capital shortfall Bank-level capital shortfall Number of undercapitalized and/or failed institutions, and their shares of assets in the system Evolution and direction of spillovers.
Financial System: System-Wide Liquidity (SWL) Analysis
1. Institutional Perimeter	Entities included	Most economic agent type present in the financial system: Central Bank Government Commercial Banks State-owned banks Investment Funds NFCs Households Foreign investors
1. Institutional Perimeter	Data and baseline date	Ad-hoc data request template provided by the FSAP team to Banxico, capturing: Available collateral (encumbered and unencumbered) by asset class, remaining maturity bucket and eligibility for CB operations Existing collateralized funding and margin positions for all agents Composition of the most important segments of B/S assets and liabilities by agent type, as well as bilateral exposure between agents informed by who-to-whom holdings. Data as of December 2021, at the aggregate B/S level and on a best effort basis. Scope of financial consolidation: group-wide at the highest level
2. Channels of Risk Propagation	Methodology	The analysis is conducted at the aggregated B/S data for each type of economic agent. For each scenario, the liquidity counterbalancing capacity for each type of economic agent is measured, in response to direct shocks (funding and market) and after considering second round effects due to calls on available collateral for existing funding and margin positions. Shocks are generated based on correlated distributions (copula) with flexibility of adjusting ranges of the distributions and correlation factors between distributions to reflect different level of severity. Cash and unencumbered collateral are considered as accessible liquidity buffers. Pecking order of the utilization of liquid assets: 1. Cash and equivalences 2. Short term assets including short term paper and outstanding reverse repos 3. Repos using unencumbered assets Willingness and capacity to roll-over existing funding positions across agents are assessed after measuring liquidity excess or shortfalls. The resilience of the system (and of individual agents) is assessed based on the net liquidity distribution across the number of simulated scenarios (shortfall probability density). Agents will be classified in accordance with their liquidity shortfall propensity and with respect to their contribution to the overall system-wide resiliency or vulnerability. Existing counterbalancing capacity of unencumbered collateral is measured against severe tail events as the point in the distribution that would force Banxico to increase the perimeter of eligible collateral.
3. Risks and Buffers	Risks	Funding liquidity risk is reflected in funding run-off rates, capital outflows, share redemption and offshore switching. Market liquidity risk is reflected in asset haircuts, influenced by market movements, potential fire sales and collateral supply considerations.
3. Risks and Buffers	Buffers	Available unencumbered collateral (CB eligible and non-eligible), cash position and capacity to absorb pressure in all market segments considered (sovereign, repo, and derivatives markets, etc.)
4. Behavioral Assumptions	Behavioral adjustments	Liquidity from the central bank’s emergency lending assistance (ELA) or any other increase in the perimeter of eligible collateral or eligible counterparts is not considered. Pecking order in the way agents with excess (insufficient) liquidity decide to (not) roll-over funding positions may be important. Binding liquidity requirements (LCR constraints) can be switched on/off.
5. Tail shocks	Scenario analysis	The analysis narrative would entail the simulation of a material number of scenarios consisting of a series of random (but correlated) layers of shocks: Sovereign market repricing shocks due to capital outflows and risk premia reassessment Drawdown of existing credit and liquidity facilities by NFCs due to global tightening funding conditions Run-offs on wholesale and retail deposits and switch to offshore accounts due to rebalancing of funding requirements Investment Fund redemption shocks and associated short-term funding stress (e.g., via the repo market) FX depreciation and shocks attributed to the shortage of sufficient FX reserves (implemented but muted) Shocks attributed to dislocated derivatives markets and margin requirements and derivative basis shocks (implemented but muted)
6. Sensitivity analysis	Shock severity and policy experiment	Single factor sensitivity analysis by increasing of correlation factor between shock parameters Mute repo or pull back other short-term funding (deposits or short-term paper) from commercial banks to other agents as commercial banks reach liquidity regulatory threshold (e.g., LCR) Allow expanded access of investment fund to repo market to assess benefit of repo participation
7. Regulatory and Market-Based Standards and Parameters	Regulatory Standards	LCR and other liquidity constraints are not used for the identification of bank pass/failure since the analysis is performed at the aggregate level (not entity specific).
8. Reporting Format for Results	Output presentation	Probability distribution of excess/shortfall for the system and by agent type Impact attribution by agent type in the overall resiliency or vulnerability Shortfall thresholds for different agents Contribution of each layer of shocks to the overall liquidity shortfalls
9. Infrastructure		Fully comprehensive and novel infrastructure developed by IMF staff using the ad-hoc data request as a data repository. MATLAB based.
Banking Sector: Transition Risk with Digital Money
1. Institutional Perimeter	Institutions included	All D-SIBs (6 banks) and other important banks (4 additional mid-tier commercial banks for top-down ST at the highest level of consolidation.
	Market share	For the 10 commercial banks within scope, approximately 84 percent of banking sector assets.
	Data Source	Banxico’s regulatory returns and supervisory data.
2. Channels of Risk Propagation	Methodology	Balance sheet approach. Projections of key balance sheet, income statement and capital account items. Static balance sheet assumption. Non-interest income and interest expense projections are produced for all banks within scope. Non-interest income is shocked by a fall of in income from payment fees, due to more competition from new forms of payments that contest markets and force banks to compress fees. Given lack of granularity in the data, income from payments fees is proxied by credit cards income from merchants and users. Given the lack of variability in the historical data, the shock is calibrated in a similar order of magnitude than a similar analysis done for the U.K. FSAP. Interest expense increases as banks must increase remuneration to offset competition from new forms of payment that compete with sight deposits. The shock is calibrated to be the mid-point from two theoretical models with different assumptions in terms of banks’ market power and households’ preferences.
	Stress test horizon	Three years (2022 Q1 – 2024 Q4).
	Scenario analysis	Based on two scenarios: private digital money and CBDC. In both scenarios banks lose 20 percent of income from credit card fees at the end of the projection. In the private money scenario, banks have to increase the remuneration of retail sight deposits (here defined as below 1 million Mexican pesos) by 50 basis points at the end of the projection. In the CBDC scenario, banks must increase the remuneration of a smaller retail sight deposit as CBDC is assumed to be designed with a cap of 21000 Mexican pesos per account. The increase in remuneration is also 50 basis points at the end of the projection. All shocks are phased-in as 30 percent in the 2022, 70 percent in 2023, and a full impact in 2024.
3. Results	Output presentation	System-wide evolution of aggregate Core Equity Tier 1 and capital ratios relative to the baseline solvency stress test.

Domain		Top-down Stress Test by FSAP Team—Assumptions
Banking Sector: Solvency Risk
1. Institutional Perimeter	Institutions included	All D-SIBs (6 banks) and other important banks (4 additional mid-tier commercial banks for top-down (TD) ST at the highest level of consolidation.
	Market share	For the 10 commercial banks within scope, approximately 84 percent of banking sector assets.
	Data Source and Baseline Date	Banxico’s regulatory returns and supervisory data. Historical data on bank parameters based on Banxico’s statistical data warehouse. Balance sheet and financial statement data available in the public domain. Moody’s Analytics: CreditEdge data on corporate default probabilities. Data as of December 2021 (cut-off). End-2019 data might also be used for comparisons and sensitivity analysis purposes. Scope of financial consolidation: group-wide at the domestic level.
2. Channels of Risk Propagation	Methodology	Balance sheet approach. Projections of key balance sheet, income statement and capital account items. Static balance sheet assumption. Credit risk, market risk, net interest income and non-interest income projections are produced for all banks within scope for two scenarios: baseline and macro adverse. Granular projections of credit risk parameters are performed, including probabilities of default (PDs) losses given default (LGDs) for each asset class. Five different loan segments are used: corporates, mortgages, financials, government, and consumer credit. Segmentation is based on current prudential rules and availability of historical data for the estimation of satellite models. PD PIT satellites are based on historical data series of PDs for the system and by individual bank. LGD PiTs were produced for each loan segment by applying the Frye-Jakobs method. Net interest income is projected based on its sensitivity to macrofinancial conditions for both reference rates and effective spread margins across all interest rate sensitive asset and liability segments. Liability reference and margin rate shocks are linked to the macroeconomic scenario and econometric models are used to estimate pass-through rates for both asset and liability sides together with scenario anchored assumptions. The impact on P&L and OCI due to FVTPL and FVOCI positions is also estimated as part of the market risk impact. Market risk is based on the estimation of FV and OCI impact on the securities portfolios. The impact of the scenario on mutual fund, equity and FX exposures will also be measured. Net fee and commission income are stressed based on its historical volatility in combination with haircuts based on a conservative methodology reflecting the conditions prevailing the scenario narrative. Operational expenses over total assets are kept at the same level as in 2021 (cut-off). RWAs are adjusted to reflect changes in the quality of credit exposures.
	Satellite models for macro-financial linkages	Several satellite model estimation alternatives are explored: PD PIT models for each segment based on country aggregate historical PD time series and scenario translation of bank-specific starting points in the distance to default space. Bayesian Model Averaging (BMA) techniques are used to control for model uncertainty, Panel PD PIT econometric estimation models on bank-specific historical PD PIT time series using BMA techniques to control for model uncertainty, Moody’s EDF data series may also be explored for the calibration of econometric satellites for the corporate segments. Cross-sector country proxies could also be used for the projection of parameters where a direct calibration is not feasible due to data constraints (e.g., governments and financials may be proxied using corporate PD paths).
	Stress test horizon	Three years (2022 Q1 – 2024 Q4).
3. Tail Shocks	Scenario analysis	Based on two macroeconomic and financial scenarios (baseline and macro adverse). The scenarios specify key macrofinancial variables (e.g., real GDP growth, inflation rate, unemployment rates, exchange rates, equity prices, house prices, interest rates and credit growth) for Mexico, as well as global variables (e.g., oil and other commodity prices). The baseline scenario is based on April 2022 World Economic Outlook (WEO) projections. The macro adverse scenario is calibrated using the Global Macrofinancial Model (GFM) model and it assumes the materialization of the systemic risks highlighted in the RAM. The adverse scenario features a protracted global COVID-19 pandemic and supply-side disruptions that lead to higher inflation. The scenario assumes that supply-side disruptions and higher commodity prices continue to weigh on the global economy, which brings out a difficult trade-off between output and inflation for policymakers. Inflation in major economies including the U.S. surprises on the upside, and the Fed tightens monetary policy faster than expected, by about one percentage point within the first year. Higher U.S. interest rates and tighter financial conditions globally trigger capital outflows, depreciations, and higher long-term interest rates in emerging markets. The domestic layer introduces additional confidence shocks that applies downward pressure on domestic demand with subdued consumption and investment aggravating the sharp correction on both real estate and equity prices. These losses, most of which are absorbed by the banking system, subsequently curtail banks’ profitability, and prompt a broad-based tightening in the interbank market, echoing market concerns towards banks’ financial soundness. Finally, monetary policy is assumed to maintain its accommodative stance under the domestic layer and short-term interest rates are assumed to decrease towards the 4 percent effective lower bound. In terms of severity, the adverse scenario features a deviation of Mexico real GDP from its baseline of 11.3 percent by 2023, with a 2.3 Standard Deviation move in two-year cumulative real GDP growth rate, a 6.3 percent increase in unemployment rate from its baseline.
3. Tail Shocks	Sensitivity analysis	The impact of triggering credit lines to NFCs and financial entities will be covered by targeted sensitivity analysis. A more pronounced interest rate shift will also be captured by the solvency sensitivity analysis. A partial credit and market risk analysis exercise on Development banks and the twenty largest credit-providing NBFIs are attempted to increase the coverage of the solvency analysis. The FSAP adverse macroeconomic scenario is used to produce top-down estimates for PDs and LGDs for these entities using CNBV’s TD models and infrastructure. Market risk impact will also be simulated using data and models developed internally at CNBV.
4. Risks and Buffers	Risks/factors assessed	Credit risk captures all on-balance/off-balance sheet exposures at amortized cost by regulatory exposure sector. Exposures are largely domestic; therefore, no scenarios and parameter paths would be required for geographies outside Mexico. Market risk is reflected in valuation effects of FVTPL and FVOCI positions, as well as net open financial positions (i.e., equities, funds, and inflation-linked instruments exposures). Scenario-based Interest rate curves are used to infer reference interest rate changes. The adverse macro scenario is further augmented to include financial variables that are needed to produce accurate projections for fair value positions (like corporate spread rate shock or bank issued bonds spread shock). Net interest income is affected by projecting effective interest rates by asset/liability class. Policy rates and wholesale/interbank rates will directly follow the macroeconomic scenario paths and a panel econometric approach will be used to define the velocity of passthrough rates to all remaining asset and liability segments. Shocks to non-interest income are simulated to capture varying degrees of market-sensitive components of non-interest income. Projected RWA densities are also capturing a twofold impact: deterioration of credit quality and partial/full unwinding of relevant policy support measures.
4. Risks and Buffers	Behavioral adjustments	Under the static balance sheet assumption exposures remain constant and do not evolve in accordance with credit growth assumptions of scenarios. For NII, maturing assets/liabilities are assumed to be replaced by instruments of the same type, maturity but at current rates. There is no recognized interest on non-performing exposures. If banks’ capital falls below regulatory requirements, no prompt corrective action is assumed. Banks are assumed to pay 30 percent of their profits as tax. Dividend payout ratio is assumed to be the maximum of 40 percent or the payout ratio of the cut-off year unless the capital conservation buffer falls below 2.5 percent.
5. Regulatory and Market Based Standards and Parameters	Calibration of risk parameters	Currently the banking system is regulated under a full Basel III prudential framework. Accounting provisions are set by CNBV regulations (IFRS 9 was only implemented in January 2022 and CNBV has the mandate to set requirements for the accounting loan loss provisioning). In this context the stress test analysis will follow regulatory definitions of PDs and LGDs where applicable. Currently credit exposure portfolios are under the Standardized (STA) and the Advanced Internal Rating Based (A-IRB) regulatory approach. Risk-weighted asset densities are either assumed to remain constant for STA portfolios and following the PD PIT path (making use of a smoothening factor for the TTC effect).
5. Regulatory and Market Based Standards and Parameters	Regulatory/accounting and market-based standards	In the baseline, hurdle rates include the regulatory minimum (CET1: 4.5 percent, Tier1: 6 percent, Total Capital: 8 percent) and any applicable capital buffers (CCB, D-SIB surcharge, P2R). D-SIB charge ranges from 0.6 percent to 1.5 percent for the banks within scope. In the adverse scenario, the regulatory minimum (including D-SIB surcharge and P2R) is assumed to be the hurdle rate, as banks can draw down the CCB. Note that D-SIB surcharge is not considered as a buffer in Mexico. Hurdle rates are based on the CET1, Tier1, and Total Capital ratios.
6. Reporting Format for Results	Output presentation	System-wide evolution of aggregate CET1 and capital ratios. Distribution of banks’ capital positions Contribution to key drivers to system-wide net income and capital position, including differences between the baseline scenario and the adverse scenario. Share of institutions with capital below the hurdle rates.
Banking Sector: Liquidity Risk
1. Institutional Perimeter	Institutions included	The fifty commercial banks in Mexico at the highest level of consolidation.
	Market share	100 percent of commercial banking sector assets.
	Data and baseline date	Banxico’s regulatory reports monitoring the Liquidity Coverage Ratio and the Net Stable Funding Ratio and the additional (synthetically constructed) monitoring report capturing liquidity contractual maturity ladder. Data as of December 2021; December 2019 data will also be used to highlight the impacts of the pandemic on liquidity positions of banks. Scope of financial consolidation: group-wide at the highest level.
2. Channels of Risk Propagation	Methodology	The exercise is based on three types of tests—LCR test, cash-flow analysis and NSFR test. The LCR test is in line with the standard Banxico (and Basel compliant) monitoring tool, featuring total consolidated liquidity and liquidity in significant currencies (mainly USD). A set of scenarios for LCR outflows and HQLA haircuts is used to produce stressed LCR ratios (by currency and at the consolidated level). For the LCR test, the stress test horizon is 30 days. The cash-flow analysis analyzes the net cash balance (as a proxy of banks’ resiliency to liquidity stress events), accounting for available unencumbered assets, contractual cash inflows and outflows, and behavioral flows. For the cash-flow analysis, a range of scenarios featuring funding run-off rates, liquid assets haircuts and assumptions on inflows and outflows of increased severity for different durations of liquidity stress are explored (a stress-horizon of 3 months is used as the central assumption). Positive counterbalancing capacity post-scenario implies bank resiliency, negative is an indication of positive bank liquidity stress. For the cash-flow analysis, asset haircuts reflect two components: (i) shocks to interest rates and asset prices as captured the macrofinancial scenarios; and (ii) additional haircuts required by counterparties to accept specific assets as collateral for secured funding transactions. The NSFR became a binding requirement for Mexican banks in March 2022. For monitoring purposes, banks have been reporting NSFR calculations to competent authorities since 2017.
3. Risks and Buffers	Risks	Funding liquidity risk is reflected in funding run-off rates and asset roll-over rates, the latter providing cash inflows related to non-renewal of maturing assets. Market liquidity risk is reflected in asset haircuts, which could be influenced by market movements, potential fire sales and collateral supply considerations.
	Behavioral adjustments	Liquidity from the central bank’s emergency lending assistance (ELA) is not considered. Inflows from maturing loans are ignored (cash-flow analysis, after a certain level of scenario severity) capturing a systemic liquidity stress scenario vs a bank-idiosyncratic one. The cash-flow analysis may consider some behavioral assumptions about a counterparty’s ability or willingness to transact based on banks’ solvency and liquidity conditions.
4. Tail shocks	Scenario analysis	For the LCR test, 12 scenarios are considered as a combination of: (i) three scenarios on liquid assets shocks (regulatory, mild, and severe), and ii) four scenarios on liability outflows; regulatory, one reflecting retail outflows, one reflecting higher wholesale outflows, and one combining the retail and wholesale outflows. For the cash-flow analysis, a series of scenarios are considered, with a range from mild to severely adverse liquidity conditions. The cash-flow analysis considers both funding and market liquidity risks.
5. Regulatory and Market-Based Standards and Parameters	Calibration of risk parameters	LCR tests are based on regulatory and stress parameters. Cash-flow analysis may incorporate relevant second-round effects. Stress funding run-off rates, asset roll-over rates, and asset haircuts are calibrated based on empirical evidence and relevant international experiences.
5. Regulatory and Market-Based Standards and Parameters	Regulatory/accounting and market-based standards	LCR per Basel III; the hurdle at 100 percent. Net cash balance for the cash-flow analysis; to pass, a non-negative net cash balance is required, where the balance reflects net funding outflows and counterbalancing capacity. NSFR per Basel III; the hurdle at 100 percent.
6. Reporting Format for Results	Output presentation	Changes in the system-wide liquidity position, including important drivers for cash outflows, cash inflows and counterbalancing capacity. Distribution of banks’ liquidity positions. Number of institutions with LCR/NSFR below 100 percent and/or negative net cash balance. Amount of liquidity shortfalls, including by currencies.
7. Sensitivity Analysis	Output presentation	The analysis would cover policy support measures and will identify how such measures have impacted regulatory liquidity metrics. As a natural result, the analysis will also assess how the gradual measure unwinding will have affect liquidity positions of banks.
8. Infrastructure	Infrastructure used	For the LCR test, Banxico’s infrastructure to run the scenario developed by IMF staff and Banxico’s Liquidity at Risk tests. For cash flow analysis, fully comprehensive infrastructure developed by IMF staff using Banxico’s regulatory reports as a data repository. MATLAB and Excel based.
Climate Change: Physical Risk
1. Institutional Perimeter	Institutions included	Same set as in solvency stress test (10 largest commercial banks).
1. Institutional Perimeter	Data and baseline date	Sectoral exposure breakdown Source: Supervisory data Data as of December 2021 (cut-off)
2. Channels of Risk Propagation	Methodology	Climate scenario around tropical cyclones and/or floods based on history repeating and/or identification of future acute events reflecting climate change (subject to data/model availability), generating estimation of direct economic losses and damages, i.e., the physical capital damage rates (provided by the WB FSAP team). The adverse physical risk via capital damage rates is used as a layer of shock in a DSGE macro model. This also leads to persistent productivity shocks with additional considerations of investment adjustments costs and/or investment specific technological shocks, The underlying DSGE model is used to calibrate a full macroeconomic scenario.
3. Risks and Buffers	Risks	Credit channel risks are assumed (revised PD paths). All other channels are assumed to remain unaffected. Scenario dependent capital projections are produced based on the physical risk shock dependent PD paths.
3. Risks and Buffers	Buffers	Banks’ own capital
5. Reporting Format for Results	Output presentation	Delta PDs at the bank and system-wide level for corporate credit exposures. System-wide capital path projection under the physical risk scenarios (partial analysis, assuming only corporate credit risk, to be finalized). Comparison with the central baseline scenario. Bank-level capital impact and shortfalls.
Climate Change: Transition Risk
1. Institutional Perimeter	Institutions included	Same set as in solvency stress test (10 largest commercial banks).
1. Institutional Perimeter	Data and baseline date	Sectoral exposure breakdown Source: Supervisory data Firm-specific emission: from Urgentem. Firm balance sheets: DataStream and Capital IQ. Firm-specific historical default rates: Moody’s firm-level EDFs.
2. Channels of Risk Propagation	Methodology	Firm balance sheet stress approach. Step 1 (Bridge equation): establishing a relationship between firm-specific default rates and three firm level balance sheet indicators reflecting viability, liquidity, and solvency conditions (interest coverage ratio, current ratio and leverage ratio called vulnerability indicators). Firm sample restricted to listed companies with available historical default rate estimates. Step 2: Scenario dependent carbon prices and sectoral paths applied to firms’ balance sheets. Multi-year projections for balance sheet and profit components (forward-looking interest coverage ratio, current ratios, and leverage ratios) estimated via micro-simulations. Additional shocks, such as a sudden/unexpected large shift in market’s risk assessment are explored. Step 3: Elasticities from Step 1 are used to infer stressed default rates (using forward looking metrics from Step 2) for the sample of firms. Step 4: Weighted sectoral aggregates scenario dependent PDs are produced by aggregating firm level default rates and using total outstanding debt as weights. Step 5: Bank level sectoral corporate exposure breakdown is used to produce delta PDs using baseline and adverse default rates from Step 4. Step 6: Stressed delta PDs (reflecting transition risk) are fed to the standard solvency ST machinery to produce capital projections.
	Satellite models for macro-financial linkages	Bridge equation linking defaults rates to firm level vulnerability indicators: a fixed effects panel regression on historical firm level default rates; additional stochastic model to be explored for other shocks.
	Horizon	One to five years: multi-year projection of balance sheet dynamics and vulnerability indicators under transition scenarios.
3. Tail Shocks	Scenario analysis	Based on transition risk scenarios anchored to NGFS scenario categories and augmented to obtain sectoral output pathways via CGE model. Hot house world/business as usual is baseline with 1-2 adverse scenarios aligned to orderly and/or disorderly NGFS categories.
3. Risks and Buffers	Risks	Credit channel risks. All other channels are assumed to remain unaffected. Delta PDs relative to the baseline by bank is the envisaged outcome of the analysis.
5. Reporting Format for Results	Output presentation	Delta PDs by sector, by bank and (weighted) system-wide average. Bank-level capital impact and shortfalls (optional).
Financial System: Contagion Risk
1. Institutional Perimeter	Institutions included	All commercial and development banks, brokerage houses, investment and pension funds and the largest credit providing NBFIs (subject to data availability) in Mexico, at the highest level of consolidation
	Market share	Almost the entire system in terms of asset coverage
	Data and baseline date	Source: Supervisory data and ad-hoc data request Data as of December 2021 (random day cut-off, to avoid window dressing effects) BIS consolidated banking statistics, data as of end-Sept 2021
2. Channels of Risk Propagation	Methodology	Interbank and cross-border network model by Espinosa-Vega and Solé (2010)
3. Risks and Buffers	Risks	Credit and funding losses related to interbank/inter-entity cross-exposures (and cross-border banking exposures)
3. Risks and Buffers	Buffers	Banks’ and brokerage houses’ own capital buffers, other entities are not assumed to default in the simulation (internal loss absorption)
4. Tail shocks	Size of the shock	Pure contagion: default of individual institutions Several types of cross-entity exposures considered: secured, unsecured, crossholdings of debt instruments, settlement exposures. Different LGDs might be used, depending on exposure type. Simulation of multiple concurrent defaults may also be examined.
6. Reporting Format for Results	Output presentation	Contagion and vulnerability indicators System-wide capital shortfall Bank-level capital shortfall Number of undercapitalized and/or failed institutions, and their shares of assets in the system Evolution and direction of spillovers.
Financial System: System-Wide Liquidity (SWL) Analysis
1. Institutional Perimeter	Entities included	Most economic agent type present in the financial system: Central Bank Government Commercial Banks State-owned banks Investment Funds NFCs Households Foreign investors
1. Institutional Perimeter	Data and baseline date	Ad-hoc data request template provided by the FSAP team to Banxico, capturing: Available collateral (encumbered and unencumbered) by asset class, remaining maturity bucket and eligibility for CB operations Existing collateralized funding and margin positions for all agents Composition of the most important segments of B/S assets and liabilities by agent type, as well as bilateral exposure between agents informed by who-to-whom holdings. Data as of December 2021, at the aggregate B/S level and on a best effort basis. Scope of financial consolidation: group-wide at the highest level
2. Channels of Risk Propagation	Methodology	The analysis is conducted at the aggregated B/S data for each type of economic agent. For each scenario, the liquidity counterbalancing capacity for each type of economic agent is measured, in response to direct shocks (funding and market) and after considering second round effects due to calls on available collateral for existing funding and margin positions. Shocks are generated based on correlated distributions (copula) with flexibility of adjusting ranges of the distributions and correlation factors between distributions to reflect different level of severity. Cash and unencumbered collateral are considered as accessible liquidity buffers. Pecking order of the utilization of liquid assets: 1. Cash and equivalences 2. Short term assets including short term paper and outstanding reverse repos 3. Repos using unencumbered assets Willingness and capacity to roll-over existing funding positions across agents are assessed after measuring liquidity excess or shortfalls. The resilience of the system (and of individual agents) is assessed based on the net liquidity distribution across the number of simulated scenarios (shortfall probability density). Agents will be classified in accordance with their liquidity shortfall propensity and with respect to their contribution to the overall system-wide resiliency or vulnerability. Existing counterbalancing capacity of unencumbered collateral is measured against severe tail events as the point in the distribution that would force Banxico to increase the perimeter of eligible collateral.
3. Risks and Buffers	Risks	Funding liquidity risk is reflected in funding run-off rates, capital outflows, share redemption and offshore switching. Market liquidity risk is reflected in asset haircuts, influenced by market movements, potential fire sales and collateral supply considerations.
3. Risks and Buffers	Buffers	Available unencumbered collateral (CB eligible and non-eligible), cash position and capacity to absorb pressure in all market segments considered (sovereign, repo, and derivatives markets, etc.)
4. Behavioral Assumptions	Behavioral adjustments	Liquidity from the central bank’s emergency lending assistance (ELA) or any other increase in the perimeter of eligible collateral or eligible counterparts is not considered. Pecking order in the way agents with excess (insufficient) liquidity decide to (not) roll-over funding positions may be important. Binding liquidity requirements (LCR constraints) can be switched on/off.
5. Tail shocks	Scenario analysis	The analysis narrative would entail the simulation of a material number of scenarios consisting of a series of random (but correlated) layers of shocks: Sovereign market repricing shocks due to capital outflows and risk premia reassessment Drawdown of existing credit and liquidity facilities by NFCs due to global tightening funding conditions Run-offs on wholesale and retail deposits and switch to offshore accounts due to rebalancing of funding requirements Investment Fund redemption shocks and associated short-term funding stress (e.g., via the repo market) FX depreciation and shocks attributed to the shortage of sufficient FX reserves (implemented but muted) Shocks attributed to dislocated derivatives markets and margin requirements and derivative basis shocks (implemented but muted)
6. Sensitivity analysis	Shock severity and policy experiment	Single factor sensitivity analysis by increasing of correlation factor between shock parameters Mute repo or pull back other short-term funding (deposits or short-term paper) from commercial banks to other agents as commercial banks reach liquidity regulatory threshold (e.g., LCR) Allow expanded access of investment fund to repo market to assess benefit of repo participation
7. Regulatory and Market-Based Standards and Parameters	Regulatory Standards	LCR and other liquidity constraints are not used for the identification of bank pass/failure since the analysis is performed at the aggregate level (not entity specific).
8. Reporting Format for Results	Output presentation	Probability distribution of excess/shortfall for the system and by agent type Impact attribution by agent type in the overall resiliency or vulnerability Shortfall thresholds for different agents Contribution of each layer of shocks to the overall liquidity shortfalls
9. Infrastructure		Fully comprehensive and novel infrastructure developed by IMF staff using the ad-hoc data request as a data repository. MATLAB based.
Banking Sector: Transition Risk with Digital Money
1. Institutional Perimeter	Institutions included	All D-SIBs (6 banks) and other important banks (4 additional mid-tier commercial banks for top-down ST at the highest level of consolidation.
	Market share	For the 10 commercial banks within scope, approximately 84 percent of banking sector assets.
	Data Source	Banxico’s regulatory returns and supervisory data.
2. Channels of Risk Propagation	Methodology	Balance sheet approach. Projections of key balance sheet, income statement and capital account items. Static balance sheet assumption. Non-interest income and interest expense projections are produced for all banks within scope. Non-interest income is shocked by a fall of in income from payment fees, due to more competition from new forms of payments that contest markets and force banks to compress fees. Given lack of granularity in the data, income from payments fees is proxied by credit cards income from merchants and users. Given the lack of variability in the historical data, the shock is calibrated in a similar order of magnitude than a similar analysis done for the U.K. FSAP. Interest expense increases as banks must increase remuneration to offset competition from new forms of payment that compete with sight deposits. The shock is calibrated to be the mid-point from two theoretical models with different assumptions in terms of banks’ market power and households’ preferences.
	Stress test horizon	Three years (2022 Q1 – 2024 Q4).
	Scenario analysis	Based on two scenarios: private digital money and CBDC. In both scenarios banks lose 20 percent of income from credit card fees at the end of the projection. In the private money scenario, banks have to increase the remuneration of retail sight deposits (here defined as below 1 million Mexican pesos) by 50 basis points at the end of the projection. In the CBDC scenario, banks must increase the remuneration of a smaller retail sight deposit as CBDC is assumed to be designed with a cap of 21000 Mexican pesos per account. The increase in remuneration is also 50 basis points at the end of the projection. All shocks are phased-in as 30 percent in the 2022, 70 percent in 2023, and a full impact in 2024.
3. Results	Output presentation	System-wide evolution of aggregate Core Equity Tier 1 and capital ratios relative to the baseline solvency stress test.

Appendix IV. Cash Flow Analysis Scenario Parameters

Segment Name	Type	Value Min	Value Max	Collateralization
Liabilities resulting from securities issued (if not treated as retail deposits)	Outflows
Unsecured bonds due	Outflows	0	1	1
Regulated covered bonds	Outflows	0	1	1
Securitizations due	Outflows	0	1	1
Other	Outflows	0	1	1
Liabilities resulting from secured lending and capital market driven transactions collateralized by:	Outflows
Level 1 tradable assets	Outflows
Level 1 excluding covered bonds	Outflows	0.1	0.3	1.02
Level 1 central bank	Outflows
Level 1 (CQS 1)	Outflows	0	0.3	1.02
Level 1 (CQS2, CQS3)	Outflows	0.1	0.5	1.02
Level 1 (CQS4+)	Outflows	0.2	0.5	1.02
Level 1 covered bonds (CQS1)	Outflows	0.2	0.5	1.02
Level 2A tradable assets	Outflows	0.2	0.5	1.02
Level 2A corporate bonds (CQS1)	Outflows
Level 2A covered bonds (CQS1, CQS2)	Outflows	0.2	0.5	1.02
Level 2A public sector (CQS1, CQS2)	Outflows	0.2	0.5	1.02
Level 2B tradable assets	Outflows
Level 2B ABS (CQS1)	Outflows	0.2	0.5	1.05
Level 2B covered bonds (CQS1-6)	Outflows	0.2	0.5	1.05
Level 2B: corporate bonds (CQ1-3)	Outflows	0.2	0.5	1.05
Level 2B shares	Outflows	0.35	1	1.5
Level 2B public sector (CQS 3-5)	Outflows	0.35	1	1.5
Other tradable assets	Outflows	0.35	1	1.5
Other assets	Outflows	0.35	1	1.5
Liabilities not reported in 1.2, resulting from deposits received (excluding deposits received as collateral)	Outflows
Stable retail deposits	Outflows	0.05	0.1	1
Other retail deposits	Outflows	0.1	0.2	1
Operational deposits	Outflows	0.05	0.25	1
Non-operational deposits from credit institutions	Outflows	0.2	1	1
Non-operational deposits from other financial customers	Outflows	0.2	1	1
Non-operational deposits from central banks	Outflows	0	0.25	1
Non-operational deposits from non-financial corporates	Outflows	0.2	0.4	1
Non-operational deposits from other counterparties	Outflows	0.2	0.4	1
FX-swaps maturing	Outflows	0	0	1
Derivatives amount payables other than those reported in 1.4	Outflows	0	0	1
Other outflows	Outflows	0	0	1
Total outflows	Outflows
Monies due from secured lending and capital market driven transactions collateralized by:	Inflows
Level 1 tradable assets	Inflows
Level 1 excluding covered bonds	Inflows	0.1	0.3	1.02
Level 1 central bank	Inflows
Level 1 (CQS 1)	Inflows	0	0.3	1.02
Level 1 (CQS2, CQS3)	Inflows	0.1	0.5	1.02
Level 1 (CQS4+)	Inflows	0.2	0.5	1.02
Level 1 covered bonds (CQS1)	Inflows	0.2	0.5	1.02
Level 2A tradable assets	Inflows	0.2	0.5	1.05
Level 2A corporate bonds (CQS1)	Inflows
Level 2A covered bonds (CQS1, CQS2)	Inflows	0.2	0.5	1.05
Level 2A public sector (CQS1, CQS2)	Inflows	0.2	0.5	1.05
Level 2B tradable assets	Inflows
Level 2B ABS (CQS1)	Inflows	0.2	0.5	1.05
Level 2B covered bonds (CQS1-6)	Inflows	0.2	0.5	1.05
Level 2B: corporate bonds (CQ1-3)	Inflows	0.2	0.5	1.05
Level 2B shares	Inflows	0.35	1	1.5
Level 2B public sector (CQS 3-5)	Inflows	0.35	1	1.5
Other tradable assets	Inflows	0.35	1	1.5
Other assets	Inflows	0.35	1	1.5
Monies due not reported in 2.1 resulting from loans and advances granted to:	Inflows
Retail customers	Inflows	0	1	1
Non-financial corporates	Inflows	0	1	1
Credit institutions	Inflows	0	1	1
Other financial customers	Inflows	0	1	1
Central banks	Inflows	0	1	1
Other counterparties	Inflows	0	1	1
FX-swaps maturing	Inflows	0	1	1
Derivatives amount receivables other than those reported in 2.3	Inflows	0	1	1
Paper in own portfolio maturing	Inflows	0	1	1
Other inflows	Inflows	0	1	1
Withdrawable central bank reserves	CBL	0	0	1
Level 1 tradable assets	CBL
Level 1 excluding covered bonds	CBL	0	0.1	1
Level 1 central bank	CBL
Level 1 (CQS 1)	CBL	0	0.1	1
Level 1 (CQS2, CQS3)	CBL	0	0.1	1
Level 1 (CQS4+)	CBL	0	0.1	1
Level 1 covered bonds (CQS1)	CBL	0	0.2	1
Level 2A tradable assets	CBL	0.05	0.2	1
Level 2A corporate bonds (CQS1)	CBL	0.05	0.2	1
Level 2A covered bonds (CQS 1, CQS2)	CBL
Level 2A public sector (CQS1, CQS2)	CBL	0.05	0.2	1
Level 2B tradable assets	CBL	0.1	0.2	1
Level 2B ABS (CQS1)	CBL	0.1	0.2	1
Level 2B covered bonds (CQS1-6)	CBL
Level 2B corporate bonds (CQ1-3)	CBL	0.1	0.2	1
Level 2B shares	CBL	0.1	0.2	1
Level 2B public sector (CQS 3-5)	CBL	0.1	0.2	1
Other tradable assets	CBL	0.1	0.2	1
Central government (CQS1)	CBL
Central government (CQS 2 & 3)	CBL	0	0.2	1
Shares	CBL	0	0.2	1
Covered bonds	CBL	0	0.2	1
ABS	CBL	0	0.2	1
Other tradable assets	CBL	0	0.2	1
Non tradable assets eligible for central banks	CBL	0	0.2	1
Undrawn committed facilities received	CBL
Level 1 facilities	CBL	0.8	1	1
Level 2B restricted use facilities	CBL	0.8	1	1
Level 2B IPS facilities	CBL	0.8	1	1
Other facilities	CBL
From intragroup counterparties	CBL	1	1	1
From other counterparties	CBL	1	1	1
Outflows from committed facilities	Contingencies
Committed credit facilities	Contingencies
Considered as Level 2B by the receiver	Contingencies	0.15	0.3	1
Other	Contingencies	0.15	0.4	1
Liquidity facilities	Contingencies	0.5	1	1
Outflows due to downgrade triggers	Contingencies	0.5	1	1

Segment Name	Type	Value Min	Value Max	Collateralization
Liabilities resulting from securities issued (if not treated as retail deposits)	Outflows
Unsecured bonds due	Outflows	0	1	1
Regulated covered bonds	Outflows	0	1	1
Securitizations due	Outflows	0	1	1
Other	Outflows	0	1	1
Liabilities resulting from secured lending and capital market driven transactions collateralized by:	Outflows
Level 1 tradable assets	Outflows
Level 1 excluding covered bonds	Outflows	0.1	0.3	1.02
Level 1 central bank	Outflows
Level 1 (CQS 1)	Outflows	0	0.3	1.02
Level 1 (CQS2, CQS3)	Outflows	0.1	0.5	1.02
Level 1 (CQS4+)	Outflows	0.2	0.5	1.02
Level 1 covered bonds (CQS1)	Outflows	0.2	0.5	1.02
Level 2A tradable assets	Outflows	0.2	0.5	1.02
Level 2A corporate bonds (CQS1)	Outflows
Level 2A covered bonds (CQS1, CQS2)	Outflows	0.2	0.5	1.02
Level 2A public sector (CQS1, CQS2)	Outflows	0.2	0.5	1.02
Level 2B tradable assets	Outflows
Level 2B ABS (CQS1)	Outflows	0.2	0.5	1.05
Level 2B covered bonds (CQS1-6)	Outflows	0.2	0.5	1.05
Level 2B: corporate bonds (CQ1-3)	Outflows	0.2	0.5	1.05
Level 2B shares	Outflows	0.35	1	1.5
Level 2B public sector (CQS 3-5)	Outflows	0.35	1	1.5
Other tradable assets	Outflows	0.35	1	1.5
Other assets	Outflows	0.35	1	1.5
Liabilities not reported in 1.2, resulting from deposits received (excluding deposits received as collateral)	Outflows
Stable retail deposits	Outflows	0.05	0.1	1
Other retail deposits	Outflows	0.1	0.2	1
Operational deposits	Outflows	0.05	0.25	1
Non-operational deposits from credit institutions	Outflows	0.2	1	1
Non-operational deposits from other financial customers	Outflows	0.2	1	1
Non-operational deposits from central banks	Outflows	0	0.25	1
Non-operational deposits from non-financial corporates	Outflows	0.2	0.4	1
Non-operational deposits from other counterparties	Outflows	0.2	0.4	1
FX-swaps maturing	Outflows	0	0	1
Derivatives amount payables other than those reported in 1.4	Outflows	0	0	1
Other outflows	Outflows	0	0	1
Total outflows	Outflows
Monies due from secured lending and capital market driven transactions collateralized by:	Inflows
Level 1 tradable assets	Inflows
Level 1 excluding covered bonds	Inflows	0.1	0.3	1.02
Level 1 central bank	Inflows
Level 1 (CQS 1)	Inflows	0	0.3	1.02
Level 1 (CQS2, CQS3)	Inflows	0.1	0.5	1.02
Level 1 (CQS4+)	Inflows	0.2	0.5	1.02
Level 1 covered bonds (CQS1)	Inflows	0.2	0.5	1.02
Level 2A tradable assets	Inflows	0.2	0.5	1.05
Level 2A corporate bonds (CQS1)	Inflows
Level 2A covered bonds (CQS1, CQS2)	Inflows	0.2	0.5	1.05
Level 2A public sector (CQS1, CQS2)	Inflows	0.2	0.5	1.05
Level 2B tradable assets	Inflows
Level 2B ABS (CQS1)	Inflows	0.2	0.5	1.05
Level 2B covered bonds (CQS1-6)	Inflows	0.2	0.5	1.05
Level 2B: corporate bonds (CQ1-3)	Inflows	0.2	0.5	1.05
Level 2B shares	Inflows	0.35	1	1.5
Level 2B public sector (CQS 3-5)	Inflows	0.35	1	1.5
Other tradable assets	Inflows	0.35	1	1.5
Other assets	Inflows	0.35	1	1.5
Monies due not reported in 2.1 resulting from loans and advances granted to:	Inflows
Retail customers	Inflows	0	1	1
Non-financial corporates	Inflows	0	1	1
Credit institutions	Inflows	0	1	1
Other financial customers	Inflows	0	1	1
Central banks	Inflows	0	1	1
Other counterparties	Inflows	0	1	1
FX-swaps maturing	Inflows	0	1	1
Derivatives amount receivables other than those reported in 2.3	Inflows	0	1	1
Paper in own portfolio maturing	Inflows	0	1	1
Other inflows	Inflows	0	1	1
Withdrawable central bank reserves	CBL	0	0	1
Level 1 tradable assets	CBL
Level 1 excluding covered bonds	CBL	0	0.1	1
Level 1 central bank	CBL
Level 1 (CQS 1)	CBL	0	0.1	1
Level 1 (CQS2, CQS3)	CBL	0	0.1	1
Level 1 (CQS4+)	CBL	0	0.1	1
Level 1 covered bonds (CQS1)	CBL	0	0.2	1
Level 2A tradable assets	CBL	0.05	0.2	1
Level 2A corporate bonds (CQS1)	CBL	0.05	0.2	1
Level 2A covered bonds (CQS 1, CQS2)	CBL
Level 2A public sector (CQS1, CQS2)	CBL	0.05	0.2	1
Level 2B tradable assets	CBL	0.1	0.2	1
Level 2B ABS (CQS1)	CBL	0.1	0.2	1
Level 2B covered bonds (CQS1-6)	CBL
Level 2B corporate bonds (CQ1-3)	CBL	0.1	0.2	1
Level 2B shares	CBL	0.1	0.2	1
Level 2B public sector (CQS 3-5)	CBL	0.1	0.2	1
Other tradable assets	CBL	0.1	0.2	1
Central government (CQS1)	CBL
Central government (CQS 2 & 3)	CBL	0	0.2	1
Shares	CBL	0	0.2	1
Covered bonds	CBL	0	0.2	1
ABS	CBL	0	0.2	1
Other tradable assets	CBL	0	0.2	1
Non tradable assets eligible for central banks	CBL	0	0.2	1
Undrawn committed facilities received	CBL
Level 1 facilities	CBL	0.8	1	1
Level 2B restricted use facilities	CBL	0.8	1	1
Level 2B IPS facilities	CBL	0.8	1	1
Other facilities	CBL
From intragroup counterparties	CBL	1	1	1
From other counterparties	CBL	1	1	1
Outflows from committed facilities	Contingencies
Committed credit facilities	Contingencies
Considered as Level 2B by the receiver	Contingencies	0.15	0.3	1
Other	Contingencies	0.15	0.4	1
Liquidity facilities	Contingencies	0.5	1	1
Outflows due to downgrade triggers	Contingencies	0.5	1	1

CNBV used the flexibility embedded in the Basel framework to alleviate the pandemic's impact on banks.

Internet banking users have increased 2.5 times from 33 million in 2016 to 84 million in 2020.

https://www.cmegroup.com/market-data/volume-open-interest/fx-volume.html

Some smaller banks operate with LCR closer to the regulatory minimum due to their business models.

FSAPs typically use severe but plausible scenarios further in the tail of the historical distribution of macrofinancial variables, compared to AIV consultations, as FSAPs focus on systemic risk mitigation (Adrian and others, 2020).

Note that the non-recognition of hedging impact assumption tends to amplify market revaluation losses.

Corporate PIT PD would rise from 2.3 percent in 2021 to 4.1 percent in 2024 in the bank solvency STs.

Mexican corporates with international activities manage FX risks with natural and financial hedges.

Droughts and chronic risks are also relevant. However, droughts were not associated with large economic damages in historical data, though this may change in the future with climate change. The data and modelling requirements for assessing chronic risks remain a significant challenge and these hazards were outside the scope of this FSAP.

Due to data availability constraints, income from payments is proxied by income from credit cards.

Good examples include the Czech Republic, Euro Area, Ireland, New Zealand, and South Africa.

Each financial institution (e.g., bank, insurer, and pension fund) is supervised by a separate regulatory and supervisory agency (e.g., CNBV, CNSF, CONSAR) in Mexico.

The Bases of Coordination is a formal agreement signed by public and private stakeholders to improve coordination and cooperation within the financial sector in cybersecurity.

Banxico created a directorate in charge of these topics in 2021 and published climate risk analysis in recent FSRs.

Follow-up reports published in June 2021 and May 2022 concluded that Mexico has made good progress in most of the technical compliance deficiencies identified in the MER, where several re-ratings and upgrades were adopted.

A draft law addressing these issues is currently pending before Senate.

For example, Bank of Canada, Banco Central de Chile, European Central Bank, and Bank of Japan.

The FSAP assessment does not include deposit insurance related to e-wallets and fintech-related activities.

A resolution regime for FHCs would have two key advantages: (i) undertaking resolution at the parent level without affecting the operating companies; and (ii) giving the supervision and resolution authorities the power to force continuity of intragroup services (e.g., for data support).

Banxico introduced CoDi in 2019 as a free-of-charge service that utilizes QR codes for point-of-sale payments and internet/mobile channels for remote transactions. SPEI participants were mandated to offer CoDi to their customers and, despite 18.3 million registered accounts, there were only 1.2 million transactions by June 2022.

Development financial institutions include development banks, development funds, and development trusts.

Nonbank credit institutions include non-deposit taking credit providers, not insurance companies, pension and investment funds.

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Mexico: Financial Sector Assessment Program-Financial System Stability Assessment

Author:

International Monetary Fund. Monetary and Capital Markets Department

Volume/Issue:: Volume 2022: Issue 335

Publisher:: International Monetary Fund

ISBN:: 9798400223686

ISSN:: 1934-7685

Pages:: 64

DOI:: https://doi.org/10.5089/9798400223686.002

Keywords
Background
Financial System Structure
Systemic Vulnerabilities
Systemic Risks and Financial Sector Resilience
Cross-Cutting Themes
Financial Sector Oversight
Systemic Liquidity Management, Financial Safety Net and Crisis Preparedness
- A. Systemic Liquidity Management
- B. Financial Safety Net and Crisis Preparedness
Financial Sector Development
Authorities' Views
Annex I. Credit and Market Risks in Development Banks and Top Twenty Nonbank Credit Institutions
Annex II. Organization of the MFAs
Appendix I. Implementation Status of Key Recommendations in the 2016 FSSA
Appendix II. Risk Assessment Matrix
Appendix III. Stress Testing Matrix (STeM)
Appendix IV. Cash Flow Analysis Scenario Parameters

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Real GDP Growth and Credit Growth

(In percent, y-o-y, average over 2020-2021)

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Nonperforming Loans over Two Decades

(In percent of total loans to private sectors from commercial banks)

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^{Figure 1.}

Mexico: Macroeconomic Developments

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^{Figure 2.}

Mexico: Financial Market Developments

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^{Figure 3.}

Mexico and Selected Countries: Private Sector Leverage and Debt Service

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Structure and Size of Financial System of Selected EMs

(In percent of GDP, 2020)

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^{Figure 4.}

Mexico: Financial and Banking Sector Assets

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Holdings of Sovereign Debt Securities

(In percent of total outstanding balance)

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Outstanding Domestic Debt Securities

(In percent of GDP, 2021Q3)

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^{Figure 5.}

Mexico: Systemic Vulnerability Heatmap

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Distribution of Total CAR and LCR

(In percent, as of 2021Q3)

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Point-in-Time Probability of Defaults by Loan Segment

(In percent)

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Commercial Bank Credit to Private Nonfinancial Corporates^1/

(Dec. 2019 = 100)

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^{Figure 6.}

Mexico and Selected Countries: Financial Soundness Indicators

(As of 2022Q1 or the latest available)

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^{Figure 7.}

Mexico: Repo Market Structure

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^{Figure 8.}

Mexico: Nonfinancial Corporate Sector Performance1/

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^{Figure 9.}

Mexico: Components of Systemic Risk Analysis

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^{Figure 10.}

Mexico: FSAP Stress Test Scenarios

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^{Figure 11.}

Mexico: Bank Solvency Stress Test Results

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^{Figure 12.}

Mexico: Bank Cash Flow Analysis Results^{1/, 2/}

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^{Figure 13.}

Mexico: Results from Cross-border and Domestic Contagion Analysis

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^{Figure 14.}

Mexico: Shapley Value from Random Forest Estimation with Corporate EDFs^{1/, 2/}

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^{Figure 15.}

Mexico: Cross-Sectoral Interlinkage

(In billions of Mexican pesos, 2021, asset claims)

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^{Figure 16.}

Mexico: Results from System-Wide Liquidity Analysis

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^{Figure 17.}

Mexico: Climate Risk Analysis Framework

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Occurrence of Natural Hazards by Type

(In percent of total natural hazards, average over 1980-2020)

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^{Figure 18.}

Mexico: Results from Transition Risk Analysis^1/

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^{Figure 19.}

Mexico: Results from Physical Risk Analysis^1/

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^{Figure 20.}

Mexico: Results from Fintech-Related Risk Analysis

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^{Figure 21.}

Mexico: TLAC Requirements^{1, 2/}

(In percent of RWAs)

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^{Figure 22.}

Mexico: Bank Intervention Continuum

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^{Figure 23.}

Mexico: Financial Inclusion and Competition

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Figure 1.

Mexico: Market and Credit Risks for Commercial Banks, Development banks, and Large NBFIs

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Figure 1.

Mexico: Institutional Structure of Financial Authorities

Foresee

Segment Name	Type	Value Min	Value Max	Collateralization
Liabilities resulting from securities issued (if not treated as retail deposits)	Outflows
Unsecured bonds due	Outflows	0	1	1
Regulated covered bonds	Outflows	0	1	1
Securitizations due	Outflows	0	1	1
Other	Outflows	0	1	1
Liabilities resulting from secured lending and capital market driven transactions collateralized by:	Outflows
Level 1 tradable assets	Outflows
Level 1 excluding covered bonds	Outflows	0.1	0.3	1.02
Level 1 central bank	Outflows
Level 1 (CQS 1)	Outflows	0	0.3	1.02
Level 1 (CQS2, CQS3)	Outflows	0.1	0.5	1.02
Level 1 (CQS4+)	Outflows	0.2	0.5	1.02
Level 1 covered bonds (CQS1)	Outflows	0.2	0.5	1.02
Level 2A tradable assets	Outflows	0.2	0.5	1.02
Level 2A corporate bonds (CQS1)	Outflows
Level 2A covered bonds (CQS1, CQS2)	Outflows	0.2	0.5	1.02
Level 2A public sector (CQS1, CQS2)	Outflows	0.2	0.5	1.02
Level 2B tradable assets	Outflows
Level 2B ABS (CQS1)	Outflows	0.2	0.5	1.05
Level 2B covered bonds (CQS1-6)	Outflows	0.2	0.5	1.05
Level 2B: corporate bonds (CQ1-3)	Outflows	0.2	0.5	1.05
Level 2B shares	Outflows	0.35	1	1.5
Level 2B public sector (CQS 3-5)	Outflows	0.35	1	1.5
Other tradable assets	Outflows	0.35	1	1.5
Other assets	Outflows	0.35	1	1.5
Liabilities not reported in 1.2, resulting from deposits received (excluding deposits received as collateral)	Outflows
Stable retail deposits	Outflows	0.05	0.1	1
Other retail deposits	Outflows	0.1	0.2	1
Operational deposits	Outflows	0.05	0.25	1
Non-operational deposits from credit institutions	Outflows	0.2	1	1
Non-operational deposits from other financial customers	Outflows	0.2	1	1
Non-operational deposits from central banks	Outflows	0	0.25	1
Non-operational deposits from non-financial corporates	Outflows	0.2	0.4	1
Non-operational deposits from other counterparties	Outflows	0.2	0.4	1
FX-swaps maturing	Outflows	0	0	1
Derivatives amount payables other than those reported in 1.4	Outflows	0	0	1
Other outflows	Outflows	0	0	1
Total outflows	Outflows
Monies due from secured lending and capital market driven transactions collateralized by:	Inflows
Level 1 tradable assets	Inflows
Level 1 excluding covered bonds	Inflows	0.1	0.3	1.02
Level 1 central bank	Inflows
Level 1 (CQS 1)	Inflows	0	0.3	1.02
Level 1 (CQS2, CQS3)	Inflows	0.1	0.5	1.02
Level 1 (CQS4+)	Inflows	0.2	0.5	1.02
Level 1 covered bonds (CQS1)	Inflows	0.2	0.5	1.02
Level 2A tradable assets	Inflows	0.2	0.5	1.05
Level 2A corporate bonds (CQS1)	Inflows
Level 2A covered bonds (CQS1, CQS2)	Inflows	0.2	0.5	1.05
Level 2A public sector (CQS1, CQS2)	Inflows	0.2	0.5	1.05
Level 2B tradable assets	Inflows
Level 2B ABS (CQS1)	Inflows	0.2	0.5	1.05
Level 2B covered bonds (CQS1-6)	Inflows	0.2	0.5	1.05
Level 2B: corporate bonds (CQ1-3)	Inflows	0.2	0.5	1.05
Level 2B shares	Inflows	0.35	1	1.5
Level 2B public sector (CQS 3-5)	Inflows	0.35	1	1.5
Other tradable assets	Inflows	0.35	1	1.5
Other assets	Inflows	0.35	1	1.5
Monies due not reported in 2.1 resulting from loans and advances granted to:	Inflows
Retail customers	Inflows	0	1	1
Non-financial corporates	Inflows	0	1	1
Credit institutions	Inflows	0	1	1
Other financial customers	Inflows	0	1	1
Central banks	Inflows	0	1	1
Other counterparties	Inflows	0	1	1
FX-swaps maturing	Inflows	0	1	1
Derivatives amount receivables other than those reported in 2.3	Inflows	0	1	1
Paper in own portfolio maturing	Inflows	0	1	1
Other inflows	Inflows	0	1	1
Withdrawable central bank reserves	CBL	0	0	1
Level 1 tradable assets	CBL
Level 1 excluding covered bonds	CBL	0	0.1	1
Level 1 central bank	CBL
Level 1 (CQS 1)	CBL	0	0.1	1
Level 1 (CQS2, CQS3)	CBL	0	0.1	1
Level 1 (CQS4+)	CBL	0	0.1	1
Level 1 covered bonds (CQS1)	CBL	0	0.2	1
Level 2A tradable assets	CBL	0.05	0.2	1
Level 2A corporate bonds (CQS1)	CBL	0.05	0.2	1
Level 2A covered bonds (CQS 1, CQS2)	CBL
Level 2A public sector (CQS1, CQS2)	CBL	0.05	0.2	1
Level 2B tradable assets	CBL	0.1	0.2	1
Level 2B ABS (CQS1)	CBL	0.1	0.2	1
Level 2B covered bonds (CQS1-6)	CBL
Level 2B corporate bonds (CQ1-3)	CBL	0.1	0.2	1
Level 2B shares	CBL	0.1	0.2	1
Level 2B public sector (CQS 3-5)	CBL	0.1	0.2	1
Other tradable assets	CBL	0.1	0.2	1
Central government (CQS1)	CBL
Central government (CQS 2 & 3)	CBL	0	0.2	1
Shares	CBL	0	0.2	1
Covered bonds	CBL	0	0.2	1
ABS	CBL	0	0.2	1
Other tradable assets	CBL	0	0.2	1
Non tradable assets eligible for central banks	CBL	0	0.2	1
Undrawn committed facilities received	CBL
Level 1 facilities	CBL	0.8	1	1
Level 2B restricted use facilities	CBL	0.8	1	1
Level 2B IPS facilities	CBL	0.8	1	1
Other facilities	CBL
From intragroup counterparties	CBL	1	1	1
From other counterparties	CBL	1	1	1
Outflows from committed facilities	Contingencies
Committed credit facilities	Contingencies
Considered as Level 2B by the receiver	Contingencies	0.15	0.3	1
Other	Contingencies	0.15	0.4	1
Liquidity facilities	Contingencies	0.5	1	1
Outflows due to downgrade triggers	Contingencies	0.5	1	1

Monetary Policy Decisions
Decisions	Details
• Policy rate cut	Seven times from March 2020 through May 2021, 300 basis points in total.
• Policy rate hike	Ten times since June 2021, 525 basis points so far.

Monetary Policy Decisions
Decisions	Details
• Policy rate cut	Seven times from March 2020 through May 2021, 300 basis points in total.
• Policy rate hike	Ten times since June 2021, 525 basis points so far.

Central Bank Facilities During the COVID-19 Crisis (In billions of Mexican peso)
Type of Support	Envelope (A)	Disbursed (B)	Percent (B/A)	Expiration date
Liquidity support
• Government securities term repurchase window	150	465	310	Sep. 2021
• Reduction of the Monetary Regulatory Deposit	50	50	100	Nov 2020
• Temporary securities swap window	50	63	126	Sep. 2021
• Swap of government securities	100	15	15	Feb. 2021
• Corporate Securities Repurchase Facility	100	45	45	Sep. 2021
Credit support
• Provision of resources to banking institutions to channel credit to MSMEs and individuals affected by the COVID-19 pandemic	250	14	6	Sep. 2021
• Collateralized financing facility for commercial banks with corporate loans to finance MSMEs	100	40	40	Sep. 2021
Total	800	692	86
Total (percent of GDP)	3.1	2.7

Central Bank Facilities During the COVID-19 Crisis (In billions of Mexican peso)
Type of Support	Envelope (A)	Disbursed (B)	Percent (B/A)	Expiration date
Liquidity support
• Government securities term repurchase window	150	465	310	Sep. 2021
• Reduction of the Monetary Regulatory Deposit	50	50	100	Nov 2020
• Temporary securities swap window	50	63	126	Sep. 2021
• Swap of government securities	100	15	15	Feb. 2021
• Corporate Securities Repurchase Facility	100	45	45	Sep. 2021
Credit support
• Provision of resources to banking institutions to channel credit to MSMEs and individuals affected by the COVID-19 pandemic	250	14	6	Sep. 2021
• Collateralized financing facility for commercial banks with corporate loans to finance MSMEs	100	40	40	Sep. 2021
Total	800	692	86
Total (percent of GDP)	3.1	2.7

Amount of Total Commercial Bank Loans and Loans Under Deferred Loan Category (In millions of Mexican pesos, at the end of 2021)
	Total	Commercial	Consumer	Mortgage
Total bank loans ^1/	5,459,257	2,560,732	837,478	1,118,610
Bank loans benefitted from loan deferral program	1,067,334	499,978	243,083	324,273
Amount of loans voluntarily reduced by banks	358,674	272,226	26,421	60,027
Amount of loans under deferred loan category	708,660	227,752	216,662	264,246
- Performing	553,424	166,428	156,518	232,478
- Restructured	121,024	51,895	48,048	21,081
- Nonperforming	34,212	9,429	12,096	12,687
Share of Loans Under Deferred Loan Category (In percent of total commercial bank loans, at the end of 2021)
	Total	Commercial	Consumer	Mortgage
Bank loans benefitted from loan deferral program	19.6	19.5	29.0	29.0
Amount of loans voluntarily reduced by banks	6.6	10.6	3.2	5.4
Amount of loans under deferred loan category	13.0	8.9	25.9	23.6
- Performing	10.1	6.5	18.7	20.8
- Restructured	2.2	2.0	5.7	1.9
- Nonperforming	0.6	0.4	1.4	1.1
Performance of Loans Under Deferred Loan Category (In percent of total loans under deferred loan category, at the end of 2021)
	Total	Commercial	Consumer	Mortgage
Amount of loans under deferred loan category	100.0	100.0	100.0	100.0
- Performing	78.1	73.1	72.2	88.0
- Restructured	17.1	22.8	22.2	8.0
- Nonperforming	4.8	4.1	5.6	4.8

Topics

Countries

Series

About

Resources

Abstract

Background

Financial System Structure

Systemic Vulnerabilities

Systemic Risks and Financial Sector Resilience

A. Standard Assessment of Systemic Risks

B. System-Wide Liquidity Analysis

C. Climate-Related Risk Analysis

D. Fintech-Related Risk Analysis

E. Recommendations

Cross-Cutting Themes

Financial Sector Oversight

A. Macroprudential Framework

B. Banking Regulation and Supervision

C. Cybersecurity Regulation and Supervision

D. Oversight of Climate-Related Risks

E. Digital Money and CBDC

F. Financial Integrity (AML/CFT)

Systemic Liquidity Management, Financial Safety Net and Crisis Preparedness

A. Systemic Liquidity Management

B. Financial Safety Net and Crisis Preparedness

Financial Sector Development

Authorities' Views

Annex I. Credit and Market Risks in Development Banks and Top Twenty Nonbank Credit Institutions

Annex II. Organization of the MFAs

Appendix I. Implementation Status of Key Recommendations in the 2016 FSSA

Appendix II. Risk Assessment Matrix

Appendix III. Stress Testing Matrix (STeM)

Appendix IV. Cash Flow Analysis Scenario Parameters

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