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Compliance with the AM+L4776L/CFT International Standard

Author(s):
Concha Verdugo Yepes
Published Date:
July 2011
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I. Introductions

Country compliance with the AML/CFT international standard plays an important role in enhancing the world’s financial system integrity. As money laundering and terrorist financing can occur through many different avenues in different sectors of the economy, the standard itself has become equally broad in scope. The scope and depth of AML/CFT assessments also reflect the natural evolution of the FATF’s peer review process, which over twenty years, has prompted the gradual expansion and refinement of the standard.

The paper argues that the compliance with the AML/CFT standard is low. It therefore becomes more necessary than ever to better understand the factors that challenge compliance with the standard. Once these factors are better understood, addressing them should be part of a comprehensive policy reform agenda. In particular, domestic governance has received considerable attention in the recent past as one of the factors hampering compliance. However, the empirical evidence on the effect of domestic factors on countries’ compliance with regulatory standards is absent in the literature.

This paper attempts to provide an answer to these questions by using an entirely new analytical approach to understanding the factors affecting countries’ compliance with AML/CFT international standard. The purpose of this approach is threefold: (i) review how well countries2 have complied with the AML/CFT international standard during 2004–2011; (ii) analyze what factors explain countries’ compliance with the AML/CFT standard; and (iii) discuss the implications of these findings for the policy agenda.

The paper finds that few countries—in particular, advanced countries3— comply to a larger degree with the AML/CFT standard. The results analyzed in the paper also reveal a widespread weak compliance by financial institutions and the adverse impact on financial transparency created by the cumulative effects of poor implementation of standards on customer identification in the financial sector and FATF-designated non-financial businesses and professions (e.g., trust and company service providers), as well as standards on entity transparency (i.e., ownership and control of companies and trusts).

Moreover, evidence was found that the quality of the domestic regulatory framework helps boost compliance. On the contrary, high net interest margin and prevalence of corruption have the opposite effect. Other sets of factors, such as financial depth, country openness, and illegal activities, do not seem to have an impact on compliance.

Compliance is correlated with the countries’ economic development reflecting a designed weakness in the AML/CFT standard and the assessment of countries’ compliance with it. This is notwithstanding the fact that the approach in measuring compliance has evolved from the traditional “one-size-fits-all” basis into a more risk-based approach. We observe that the relevance of the implementation of AML/CFT measures in countries varies according to their ML/FT risk levels. These levels are not always a factor of the relative low level of development of jurisdictions and their financial systems. While some low-income countries are also at low risk for ML, this is not always the case.

Our findings carry potentially significant policy implications. At the national level, achieving high compliance requires implementing a combination of reforms, including strengthening domestic governance, and improving the coordination of efforts against ML/FT between countries, regulators and private actors. At the international level, the standard and the assessment of countries’ compliance with it need to be better designed to capture countries’ risk for ML/FT (by capturing threats as well as vulnerabilities).4

In the next section, the paper describes the theoretical framework on which this research is based. Section III analyzes the degree of compliance of 161 countries with the AML/CFT standard. Based on cross-country analysis, Section IV explores the determinants of countries’ compliance for 116 countries during 2004–2008.5Section V describes the caveats of the methodology that we employ in this paper. Section VI presents our conclusions and policy recommendations.

II. Literature Review

The international standard is particularly rigorous and detailed. Established by the Financial Action Task Force (FATF) in 1990, the standard has been updated several times and now consists of 40 Recommendations dealing with anti money laundering and 9 Special Recommendations dealing with combating terrorist financing (the FATF 40+9). To assess a country’s compliance with the FATF 40+9, a team of 4–5 assessors will typically take two weeks on-site to evaluate over 285 essential criteria and judge not only if the legal and regulatory system conforms to the standard, but also if it is being effectively implemented. Each recommendation is rated on a four point scale - non compliant, partially compliant, largely compliant, and compliant. The methodology provides that a rating of compliant shall only be given if all essential criteria are fully met.

How well do countries meet the AML/CFT standard? Interest in this question has grown as the international community (the FATF, the FATF- Style Regional Bodies, and the International Financial Institutions) reached the end of the third round6 of peer assessments and the completion of 161 mutual evaluation reports. This paper examines countries’ compliance with the AML/CFT standard, and the effect of domestic factors on countries’ compliance with the AML/CFT standard. While the literature on how well do countries meet the AML/CFT standard is large, the literature on the effect of domestic factors on countries’ compliance with the AML/CFT is sparse. In the following, we discuss a subset of this literature.

A report on the overall compliance with FATF recommendations was prepared in 2005.7 For that paper, the overall compliance with the recommendations of 18 countries (seven high income, six middle income, and five low income) was assessed.8

Putnam (1988) argues that the effectiveness of an international AML/CFT regime largely depends on the effectiveness of its constituents and vice versa.9 Due to the global nature of ML/FT phenomena, the compliance of domestic regimes with the AML/CFT international standard is seen as the first mechanism for achieving the global effectiveness of AML/CFT regime against a global phenomenon.10

Several authors argue that domestic factors determine the likelihood for implementing international standards. A typical explanation often cited for the absence of countries’ convergence in international rules is that domestic differences persist.11 The literature emphasizes the role of framework conditions such as cultural, institutional and socioeconomic settings as determining the likelihood of change to implement and harmonize international standards.12

Most of these studies consider that cultural factors determine the domestic opportunity for change. Political discourses—the ideas and narratives behind policies and policy change— are set within the broader culture of a country. 13 At the root of the problem of ML are governments’ attitudes towards ML, which dictate its level of acceptance and the extent of the involvement of the banking sector in this activity. Governments must recognize that ML poses a serious threat to democracy and to the soundness of the financial system (Johnson et al., 2002).

Another strand of the literature has examined how institutional factors create both opportunities for and impediments to change. Some authors stress that institutions provide the context in which policy changes are defined. There are limits to institutional explanations, of course. Institutions may accommodate, constrain, or refract policies but can never function as the sole “cause” of policy change.14 An effective domestic AML/CFT regime requires that certain structural elements be in place, such as a good regulatory framework, appropriate measures to prevent corruption, rule of law, and government effectiveness, culture of compliance, an effective judicial system. 15 The lack of such elements, or significant weaknesses or shortcomings in the general framework, may significantly impair the implementation of an effective AML/CFT framework.

The relationship between some economic and financial domestic conditions is somewhat less clearly established. Some socioeconomic and financial domestic conditions are rarely mentioned in the literature but are especially relevant for compliance with the AML/CFT regime. This paper examines the effects of domestic factors, specifically domestic economic and financial factors, on countries’ compliance with the AML/CFT standard.

III. How Well do Countries meet the AML/CFT Standard from 2004 TO 2011 ?

The countries’ compliance has been analyzed for the 161 countries assessed since the revision of the AML/CFT assessment methodology in 2004. Table 2 (Annex 1) shows the countries selected for this section. 16 The scores reflect the levels of compliance at the time these countries were assessed and do not take into account any progress made in addressing deficiencies since then.

Country compliance with each of the FATF 40 + 9 Recommendations is rated according to four categories: compliant (C), largely compliant (LC), partially compliant (PC), and non- compliant (NC). Another category, non-applicable (N/A), is not a rating. It reflects instead situations wherein “…a requirement or part of a requirement does not apply, due to the structural, legal or institutional features of a country.”17 These ratings represent per-recommendation summary assessments of the findings of detailed assessment missions of assessor bodies.

In general, progress has been made in each of the seven components of the AML/CFT compliance: (A) legal; (B) institutional; (C) financial institutions’ prevention; (D)DNBFPs’ prevention; (E) informal sector prevention; (F) entity transparency; and (G) international cooperation. Although there has been substantial improvement in recent years in many countries’ compliance with the AML/CFT components, the analysis indicates that the countries’ degree of compliance remains low (see Figure 1 in Annex 1).18 We can summarize the degree of compliance with the AML/CFT as follows:

Assessed countries’ compliance with the FATF Forty Recommendations—the FATF 40+9— is low. Applying a scale under which a score of 49 represents full compliance with each of the FATF 40+9,19 the average compliance score for the 161 countries assessed using the current methodology from 2004 to 2011 was 20.8 or 42.5 percent. Full compliance on any FATF Recommendation was rare, occurring in only 12.3 percent of the almost 7,889 observations in this dataset.20 Countries achieved the second highest score, largely compliant, 25.5 percent of the time, partially compliant, 35.6 percent of the time, and noncompliant 24.9 percent of the time.21

Different elements of the standard pertain to different components of a country’s AML/CFT regimes. Figure 1 summarizes the AML/CFT compliance with its seven components during 2004-2011.22 See also Table 2 in Annex 1 on jurisdictions’ compliance with the various groups of recommendations.

One clear conclusion is that elements of the standard that have been in place longer have higher compliance ratings, for example:

  • The AML Recommendations, which have been in place since 1990, were more highly rated than the CFT Special Recommendations which were introduced in October 2001.23 The degree of compliance24 for the 40 AML Recommendations was 45 percent and 31.5 percent for the 9 Special Recommendations on CFT.
  • Recommendations concerning designated nonfinancial businesses and professions, which were made subject to the standard only in 2003, have had some of the lowest compliance scores, averaging only 12.1 percent of the theoretical maximum.

It also appears to be easier to enact legislation and set up government institutions than to ensure that the system functions well on an ongoing basis.

  • The degree of compliance for those Recommendations evaluating the criminalization of ML and TF were relatively high at 45.1 percent, and a somewhat broader measure of the strength of the legal system was 41.4 percent. The legal measures are not sufficiently harmonized with the international standard. The wording of the Conventions is rarely transposed fully into domestic legislation.25
  • The Recommendations that assess the strength of AML/CFT institutions (financial intelligence units (FIU), the specialized supervisory bodies, the police, and the judiciary) show a degree of compliance at 50.6 percent. However, some countries fail to provide adequate resources for financial intelligence units (FIU) and regulatory authorities to supervise financial and other institutions for AML/CFT purposes.
  • Compliance with the Recommendations that assess the strength of preventive measures in the financial institutions was lower at 40.1 percent, and, as noted above, compliance was much lower for designated nonfinancial businesses and professions. In particular, some countries maintain weak customer identification policies for preventing access by money launderers and terrorism financiers to financial systems through financial institutions, DNFBPs, and the informal sector.
  • One particular weakness in system functionality was indicated by the significantly low compliance (22.1 percent of the theoretical maximum) that all countries received on Recommendation 5 which concerns customer due diligence measures in financial institutions.
  • Countries were also relatively strong in the area of international cooperation, showing a degree of compliance at 56.3 percent on applicable Recommendations. However, some countries have made inadequate provisions for mutual legal assistance, information sharing, and cooperation both domestically and cross-border.
  • Compliance with the Recommendations that call on countries to have adequate transparency of legal persons and arrangements is relatively high at 40.1 percent. However, in many countries the prevention of ML/FT is still hampered by difficulties in identifying or lack of commitment to identify the ultimate beneficial owners of funds/assets.
  • A higher degree of compliance appears to be associated with a higher level of economic development. In the 46 advanced economies in our sample, the degree of compliance with the AML/CFT is 56.8 percent, whereas, in the 115 emerging economies in our sample, the degree of compliance was lower (37 percent), indicating that wealthy countries have more resources to devote to constructing and implementing complex AML/CFT systems.
  • In many cases it does reflect the measures they have taken to strengthen their supervisory and regulatory systems in advance of, or as a result of, the mutual assessment reports. The financial sector makes an important contribution to the economies of many of the higher-income jurisdictions, and these jurisdictions have taken steps to protect the integrity of their financial industry and their reputations. In general countries seek to avoid the stigma of being perceived to be AML/CFT havens and possibly identified by the ICRG as having strategic AML/CFT deficiencies.26
  • The AML/CFT domestic policies have generally grown more alike over time, in the same group, but at the same time they have moved in an upward direction. For example, in the case of European countries, accession to and membership in the EU seems to be more effective for harmonizing the AML/CFT because the countries have similar regulatory frameworks,27 and the majority of them have participated in the design of the standards, so that they already have similar regulatory frameworks in place. East and South Asian countries and sub-Saharan countries have the lowest degree of overall compliance.
  • While the standard has evolved from a one-size-fits-all basis into a more risk-based approach, it still appears to have been designed mainly for formal financial systems, but the relevance of the AML/CFT measures implementation varies by risk of countries to ML/FT. The risk does not always depend only on the level of development of jurisdictions and financial systems, but rather also on the level of proceeds of crime in the country. While some low-income countries are also at low risk for ML, this is not always the case.
  • Assessing the effectiveness of countries’ implementation of the AML/CFT standard is quite challenging for a number of reasons. In practice, the assessment of effectiveness depends on what the supervised entities and countries’ authorities tell the assessors and the measurement of effectiveness by the existing assessment tools continues to be quite rudimentary. The assessors’ judgment is heavily dependent upon the quality and quantity of the information that the entities and authorities are willing to share. Furthermore, there are other factors undermining the evaluation of effectiveness, including the absence of agreed definitions of effectiveness and rudimentary measurements including, for example, the correlation between suspicious transactions reports, investigations, and convictions. Overall, the entire assessment apparatus suffers from a lack of data and the difficulty of interpreting data meaningfully.
  • The challenges in strengthening the effectiveness of the global AML/CFT regime result from four tensions. Three of these tensions operate at a domestic level: the first lies between financial regulation and political will; the second arises from the difficult interaction between the international standard and its domestic implementation, and the third occurs between government and financial and non-financial institutions. At the international level, the tension lies in the difficulties cash-based economies continue to face in implementing the standard. However, the low compliance with the standard achieved by cash-based economies does not mean that they face a higher risk for money laundering or terrorist financing than do formal economies.

However, all of these results do at least raise the question of whether focusing on AML/CFT compliance ensures progress toward mitigating real ML/TF risk. Fund staff has been working with the FATF to better understand ML and TF risks on the basis of analyzing threat, vulnerability, and consequence. In this connection, future research should include the development of different, broader metrics for analyzing the level of ML/TF risks and the level of criminal activity in a given jurisdiction as well as better methods of capturing and presenting cross-border flows.

In this regard, we have analyzed the relationship between our level of jurisdictions’ compliance with the AML/CFT standard (2004–2011)—as a measure of financial sector vulnerability—and staff’s ranking on systemically-important financial sectors (2009). Figures 2 and 3 in Annex 1 present that relationship. The negative relationship indicates that, in general, smaller, less-connected financial systems are also less compliant with the standard, which is consistent with the rest of the analysis. Looking more closely at the scatter plot, however, helps identifying those relatively large and interconnected financial systems that are also relatively vulnerable to ML based on their low compliance with the standard. This, in turn, can provide a basis for prioritizing the TA and surveillance agenda of the Fund in the area of AML/CFT.

These pictures contribute to the Fund’s analysis of risk, although, of course, they are only a point of departure. A more complete analysis would require both a better proxy for systemic vulnerability than can be provided by compliance scores and other variables which add to the threat dimension. In general, work remains to be done in testing the relationship of compliance to ML/TF risks and on measuring the effectiveness of AML/CFT regimes. Continued work in these directions could open the door to a more nuanced understanding of where the ML/TF-related threats to the international financial system lie than can be derived from simple comparisons of countries’ ratings on their AML/CFT assessments.

IV. Empirical Evidence: Determinants of the AML/CFT Compliance

A. Specification

The AML/CFT Compliance Index (AML/CFT CI) comprises seven components that serve to capture seven groupings of recommendations (legal measures, institutional measures, preventive measures for financial institutions, preventive measures for DNBFPs, preventive measures for the informal sector, entity transparency, and international cooperation).

We used the original compliance rating data, where the measure of compliance was defined as C, ‘Compliant,’ LC, ‘Largely Compliant,’ PC, ‘Partially Compliant,’ NC, ‘Non Compliant,’ and NA, ‘not applicable.’ In order to provide a quantitative measure of AML we replaced existing ratings with the following numbers: C-‘1’, LC-‘0.66’, PC-‘0.33’ and NC‘0’, NA-‘1.’. Each component is demeaned (using the arithmetic mean28) and divided by its standard deviation; that is, each grouping is standardized. For convenience, we rescaled values to a scale of ‘0’ to ‘100.’ 100 equals the best score. To yield the aggregate AML/CFT International Standards Compliance Index for an individual country, the seven components are summed up as follows:

The Compliance Index = Legal+ Institutional+ Financial Institutions Prevention + DNBFPs Prevention+ Informal Sector Prevention+ Entity Transparency +International Cooperation.

Further details on the seven standardized components for each country are provided in annex 2. The Compliance Index is constructed for 116 countries from October 2004 to 2008. The exact availability period of a published MER or a DAR, the body membership, and the assessor body is provided in Table 4 in Annex 2. Details on the recommendations included in every component are also provided in Table 2 in Annex 2.

In this research, the Compliance Index has also been compared with the Principal Component Analysis (PCA) of the 40+9 Recommendations.29 This is a multivariate dimension reduction technique to form a new variable as a linear combination of the variables in the multivariate set. We used the same original rating data used for the AML/CFT Compliance Index. For convenience, we also rescaled PCA values to ‘0’ to ‘100’ scale.

Before estimating the determinants of countries’ compliance, we use simple bivariate cross-correlations between the AML/CFT Compliance Index and cultural, institutional, and economic factors that are associated with high compliance. The analysis uses one observation for each independent variable, represented by the average over the period 2005–2007 for each country when available. The cross-correlations between the AML/CFT Compliance Index and the independent variables (Table 7 in Annex 2) confirm most of the findings in the theoretical literature. Cultural factors and institutional factors matter: countries’ criminalization of ML/FT is associated with high compliance. A high level of governance, that is, better regulatory quality framework and control of corruption, and participation in FATF are usually associated with high compliance. We also find a relatively high negative correlation between net interest margin and the AML/CFT Compliance Index and a positive correlation with financial depth, trade openness, and GDP per capita.

We now propose to estimate a standard a multivariate cross-country compliance-determinant model with an original sample of 116 countries30 assessed from 2004 to 2008 using an OLS regression as a first attempt to econometrically identify the determinants of compliance31. Table 7 (Annex 2) shows that PPP GDP32 per capita is highly correlated with cultural, institutional, and the economic factors that explain the level of development of the economy, therefore we exclude it. We estimate the AMLT/CFT compliance index as follows:

AMLT/CFT Compliance Indexi0+ β1CrimML/FTi2RQi+ |β3COi4BFATE Memberi5IDIi6M2/GDPi7TradeOpi8FDI/GDPi+ DUMMY YEAR 2007+εi

Where Crim is ML/FT criminalization and represents a cultural factor. RQ is the regulatory quality framework, CO is corruption, and BFATF is the FATF membership, all represent institutional factors. Socioeconomic factors are represented by trade openness (TradeOp) and the UNODC Illicit Drug Index (IDI). Financial factors are represented by net interest margin (Nim), financial depth (M2/GDP), and foreign direct investment net inflows in percent of GDP (FDI/GDP).

Alternative specifications are considered. The ratio of net financial services exports (RNFSE) substitutes M2/GDP in the baseline regression (Specification 2 thereafter). Bank Concentration (Baco) substitutes net interest margin in the baseline regression (Specification 3 thereafter). The ratio of net exports of financial services and the Bank Concentration variables are only used for robustness test purposes.

In addition, we are also going to replicate the regression substituting the AML/CFT Compliance Index with the PCA Index using the same dependent variables. Finally, we are going to replicate the baseline regression using the seven components of the AML/CFT Index as dependent variables.

B. Definition of Variables

Cultural Factors

  • ML/FT Criminalization: This variable captures three issues: (i) whether a country has enacted laws criminalizing the offense of money laundering related to drug trafficking; (ii) whether the country has extended anti-money laundering statutes and regulations to include nondrug-related money laundering; and (iii) it captures whether a country has criminalized the provision of material support to terrorist and/or terrorist organizations. For this variable the value is 3 if the country or jurisdiction has criminalized all of these offenses.

Institutional Factors

  • RQ: The regulatory quality is an indicator that measures the ability of governments to formulate and implement sound policies and regulations that permit and promote private sector development. This variable is selected as an average from 2005 to 2007.
  • CO: The control of corruption is an indicator that takes into account the patterns of official corruption as well as it takes into consideration a laissez-faire attitude toward the business and banking communities that makes a jurisdiction vulnerable to ML/FT. This variable is selected as an average from 2005 to 2007.
  • BFATF: This variable measures if the country is member of the FATF, this dummy captures if the country has participated in the design of the international standards. It measures if the country is a FATF member in the year of the assessment.

Socioeconomic and Financial Factors

Although there has been increasing recognition in recent years of the importance of cultural and institutional factors to explain compliance with the AML/CFT standard at the theoretical level, economic and financial factors are missing in explaining the determinants of compliance. For instance, country openness (trade, FDI, ratio of net export services), financial depth (M2/GDP), banking efficiency (net interest margin and bank concentration) could be also conducive to compliance.

  • Nim: The net interest margin33 captures the accounting value of the bank’s net interest revenue as a share of its interest-bearing (total earning) assets. This variable is calculated as an average from 2005 to 2007.
  • M2/GDP: The ratio measures the overall size of the financial intermediary sector. This is the best available general measure of financial development to compare countries. This variable is calculated as an average from 2005 to 2007.
  • TradeOp: The trade openness ratio measures the significance of the foreign sector as the share of exports and imports of goods and services in percent of GDP. This variable is calculated as an average from 2005 to 2007.
  • FDI/GDP: This indicator measures the net inflows of FDI as a sum of equity capital, reinvestment of earnings, and other short- and long-term capital. This variable is calculated as an average from 2005 to 2007. This variable allows us to measure whether the entrance of capitals is a factor explaining compliance. In principle it seems that FDI is associated to more stable and reputated countries.
  • IDI: The UNODC Illicit Drug Index (IDI 2005) measures each country’s contribution to the global drug problem. This index comprised three components: consumption, production, and trafficking. It is very important to use this index, because the money laundering associated to drugs has been addressed by FATF since 1996. This variable allows us to measure whether there is any relationship between the country compliance and the country contribution to the global problem of drugs.
  • RNFSE: The ratio of net exports of financial services proposed by Zoromé (2007) is an operational and measurable indicator of Offshore Centers (OFCs). This variable tries to capture the characteristics of an OFC— “a country or jurisdiction that provides financial services to nonresidents on a scale that is incommensurate with the size and the financing of its domestic economy”— and leads to a list of countries/jurisdictions that could be classified as an OFC’s.
  • Baco: Bank concentration34 measures the assets of the three largest banks as a share of assets of all commercial banks. It is a measure of lack of competition.

Table 3 in Annex 2 provides a list of the variables and their sources.

C. Empirical Findings

Econometric Results

The main result of our analysis is that, economic, institutional, and financial domestic factors are all critical for boosting the countries’ compliance with the AML/CFT regime. (Table 8, column 2 in Annex 2).35

In particular:

  • A higher degree of compliance appears to be associated with a higher level of economic development. GDP per capita expressed in PPP, used as a proxy for overall financial and economic development, is a significant explanatory variable of compliance, and the parameter estimates have the expected positive sign. However, a somewhat more direct measure of financial sector development, M2/GDP, was not statistically significant to explain compliance. While the general trends of compliance are clear, some interesting features are worth emphasizing. Figure 2.1 shows how close the level of compliance is related to the level of income. In addition we built a scatterplot AML compliance predicted values vs. log of PPP per capita GDP for 116 countries where data were available (Figure 3.1 in Annex 2). Our results show that there is a positive relationship in these countries between the level of economic development and the AML/CFT Compliance Index.
  • Stronger domestic governance36 is associated with higher compliance with the AML/CFT standard. A better regulatory quality framework is estimated to have a positive and statistically significant impact on the country’s compliance with the AML/CFT standard. Also, countries with a low level of control over corruption tend to have lower compliance scores, and the parameter estimates have the expected negative sign. It is necessary to strengthen domestic governance and improve the coordination between state authorities, regulators, and private actors of their efforts against ML/FT.
  • Jurisdictions with high net interest margins37 show lesser overall compliance with the AML/CFT regime. An increase in net interest margin is estimated to have a negative and statistically significant impact on a country’s compliance with the AML/CFT standard, indicating that more competitive banking systems tend to have higher levels of AML/CFT compliance.
  • However, compliance levels do not correlate with a country’s involvement in the global drug economy, which can be seen as a rough proxy for ML/TF risk. 38 In other words, there are countries with high levels of AML/CFT compliance and low levels of involvement in the drug trade and countries with high AML/CFT compliance and that contribute a great deal to the global drug problem. Similarly, low compliance countries are randomly distributed over the UNODC index. The model fits better high-income economies. Figure 3.2 shows the AML/CFT Compliance Index vs. AML/CFT predicted values. The predicted values track the actual compliance Index. The low income countries are those that the real values are far from the perfect fit line. One explanation could be that the majority of the regressors that we use better capture the formal economies for which the AML/CFT standard was designed.

Furthermore, in table 9 in Annex 2 the regressions with the 7 components of the AML/CFT as dependent variables also show that:

  • ML/FT criminalization increases the compliance with legal, institutional, and DNFBP measures.
  • Regulatory quality framework increases compliance with legal, institutional, financial institutions, and informal sector prevention measures.
  • Economies showing a high net interest margin tend to have less compliance with legal, DNFBPs, informal sector, and entity transparency measures.
  • FDI increases compliance with DNFBPs prevention and entity transparency measures. In particular the economies reporting higher FDI net inflows are the ones showing higher compliance with DNFBPs and entity transparency. This could be explained by the evidence that capital is usually invested in sound economies.
  • M2/GDP affects negatively DNFBPs and entity transparency compliance. Economies reporting higher M2/GDP are the ones showing the lesser compliance in these components.

The predicted values for the Legal, Institutional, International Cooperation, and Financial Institution Prevention measures track well the actual compliance with these measures (See Figures 4.4, 5.4, 6.4 and 10.4 in Annex 2). However, the predicted values for DNFBPs, Informal Sector and Entity Transparency measures do not track the compliance with these measures (See Table 9 and Figures 7.4, 8.4, 9.4 in Annex 2). In general, low income countries actual values are far from the perfect fit line.

We have used the PCA to compare the results with the AML/CFT index. The results for the PCA index are shown in Table 8 in Annex 2, columns 6 and are as follows:

  • The criminalization of the money laundering variable appears as a significant determinant in PCA.
  • We failed to find regulatory quality as a determinant of PCA.
  • The control of corruption is not significant for the PCA compliance index.
  • Net interest margin is significant (negative for explaining PCA).

The PCA index is not a good indicator of compliance because by definition does not include the 40+9 AML/CFT measures. It consists of 10 principal components, representing about 67.7 percent of the total variance. The first component captures 38 percent of the variance of the legal, institutional, and part of the financial institutions prevention measures ratings. Each of the rest of the components explains between 6.3 and 2.2 percent of the variance of the rest of the measures. Therefore, it suffers from a number of shortcomings:

  • The PCA does not capture very well the variance of financial institutions measures. In particular, it only captures the 53 percent of variance of the financial secrecy laws ratings (R.4) and 56 percent of the variance of the implementation of sanctions ratings (R.17).
  • The PCA only captures 54 percent of the variance of the supervisory powers to monitor and inspect the AML/CFT regime ratings (R.29).
  • It captures well the variance of DNFBPs’ prevention ratings.
  • It does not provide the best information on the variance of the informal sector prevention. In particular it only captures the 49 percent of the variance of the use of bearer instruments measures ratings (R.33).
  • It only captures the 55 percent of variance of the R.35 concerning the implementation of the international conventions.

Turning to specification 2, no evidence was found to support the theory that the offshore centers are negatively correlated with the overall compliance with the AML/CFT:

  • The ratio of net financial services exports (the measure of the offshore centers financial services) does not explain compliance.
  • It is worth emphasizing that the 28 countries excluded from the original sample due to data limitations include countries considered as important exporters of financial services.
  • Regulatory quality increases compliance when substituting M2/GDP with RNFSE in the main specification.
  • NIM and FDI also matters for compliance when substituting M2/GDP with RNFSE in the main specification.

Finally in specification 3,

  • Regulatory quality increases compliance when substituting NIM with Bank concentration in the main specification.
  • Crim also explains compliance when substituting NIM with Bank concentration in the main specification.

Confirming Theories

Our findings support the literature that emphasizes the importance of institutional structures as both opportunities for and impediments to change.39 Institutions provide the context in which policy changes are defined and therefore accommodate, constrain, or refract their implementation. In addition, findings are consistent with previous studies, such as IMF (2004a), concluding that some preconditions of governance have a significant influence on the implementation of financial sector regulation. Boosting domestic governance is essential for improving compliance and consequently the effectiveness of an international regime.

V. Caveats

The caveats of this research may be grouped as follows: (i) caveats derived from the 2004 methodology40; (ii) caveats that affected the sample, such as bias and self-endogeneity; and (iii) the difficulties encountered in when comparing different domestic data.

  • The 2004 methodology is the main limitation to overall compliance analysis. First, we are assuming that all the reports have the same quality and consistency. However, in accordance with the requirements of the 2004 methodology assessors often base their judgment of effectiveness, on statistical information, which is open to divergent interpretations.
    • Some Recommendations, such as those relating to customer due diligence or supervision, require a single aggregated rating for compliance, but the aggregated score covers considerable information.
    • The great variety in the operational rules and guidelines adopted by countries in the implementation of the AML/CFT measures to DNFBPs should require assessors to review the issues in a more disaggregated manner; strengths or weaknesses observed under one Recommendation can have a cascading effect on a country’s compliance with other Recommendations.
    • Some features of the AML/CFT regime are rated under more than one Recommendation; some criteria have proven difficult to assess in largely cash-based economies.

These factors call for the exercise of caution in interpreting the data produced by assessments.

  • Bias and self-selection limit the validity of the results. 41
    • The sample is not randomly selected. The 116 countries in the sample are countries that have voluntarily submitted themselves to mutual evaluations, through their membership in FATF or a FATF-style regional body, or to an assessment by the IMF or the World Bank.
    • The scientific challenge created by this situation presents certain challenges for which there is not an obvious solution at this stage. Therefore, caution is required in interpreting and extrapolating the results, as there may be unobservable factors involved and the available data is representative of countries that are motivated to report differently than some other countries.
    • Accordingly, the estimator is biased and does not, on average, predict the population parameter correctly. However, based on the expected systematic error that will be present due to the configuration of the sample (high compliance countries are probably reporting more often and more accurately than are noncompliant countries), the curves can still be considered as accurate depictions of the simultaneous relationships of the variables for the countries in the sample.
    • Notwithstanding their weaknesses, the analysis of the findings produced by the tests is necessary and relevant in the absence of an alternative source of data.
  • The aggregation of cross-cultural and cross-country data limits a meaningful result.Each country displays its own peculiarities in defining criminal behavior, elaborating policies, and implementing the international standard, including the recording and reporting of suspicious activity. This creates significant challenges in accurately interpreting the resulting aggregation.

VI. Conclusions and Policy Recommendations42

The paper contains two main conclusions: (i) a comprehensive assessment of countries’ ML/FT risk is overdue. Although some countries have initiated a dynamic process through which all the key components of compliance are improving, it is necessary to evaluate to what extent countries’ compliance with the AML/CFT international standard is effective to lessen countries’ vulnerability to ML and FT and (ii) the standard itself should incorporate more comprehensively the underlying risk of ML/FT, including all sectors that are vulnerable to ML and FT —the financial sector and the real sector (e.g., trade) particularly in relation to international trade. This in turn would allow countries to respond more effectively to existing risks and to adapt its AML/CFT policies to address those risks changes in ML/FT typologies.

The paper proposes that when a country’s compliance with the standard is insufficient and/or the country’s risk to ML/FT is high, the Fund should pay attention to the economic effects of ML/FT on both the domestic economy and across borders. Currently, the assessment of country compliance with the AML/CFT standard is not sufficient to establish the economic risks and consequences of ML/FT. The Fund should devote the resources necessary to better understand the phenomena of ML and FT, including through the development of a holistic ML/FT vulnerability assessment that would evaluate in addition to the existing areas, the more opaque areas of the financial and real sectors, the transmission channels, and the propagation mechanisms that could affect macroeconomic performance and financial stability.

Existing departmental fora—the preparatory processes for the World Economic Outlook (WEO), the Global Financial Stability Report (GFSR) work, and the Vulnerability Exercise (VE) for advanced economies and emerging market economies—could be adapted to this end. Moreover, these fora have the particular advantage of bringing global and regional developments to bear on the analysis of individual countries.43 The VE44 could serve as a central forum for interdepartmental discussion of emerging market economies that would ultimately feed into the selection and prioritization of AML/CFT issues into Article IV discussions. These exercises could contribute efficiently to the Fund’s macroeconomic analysis as it takes into account criminal and underground market developments. For countries vulnerable to ML/FT, the Fund could elaborate concise analytical briefs on ML/FT that would feed into the broader surveillance agenda. The briefs could serve to identify and prioritize key ML/FT issues to be covered in successive Article IV consultation cycles.

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Annex 1. How Well do Countries Meet the AML/CFT Standard during 2004–2011?

Figure 1.Overall Compliance with AML/CFT from 2004–2011 1/

Source: Author calculations.

1/The degree of compliance with the AML/CFT is measured along the vertical axis. The further from the origin (0.0), the higher the degree of compliance. The other axes represent each component of the AML/CFT Standard. Compliance is presented as share of the real and theoretical maximum ratings.

Figure 2.Relationship between Jurisdictions with Systemically Important Financial Sectors and Compliance with the AML/CFT International Standard

Source: Author calculations based on:

1. Table 2 of this annex.

2 Stability Assessments under the Financial Sector Assessment Program into Article IV Surveillance; IMF Policy Paper; August 27, 2010.

Note: Note that the ranking might change over time (Staff used 2008 data for the paper) when data on size and interconnectedness are updated and/or methodology gets revisited.

The following countries, among the 33 jurisdictions identified by the ICRG as having AML/CFT deficiencies, are not included in this chart due to the fact that there was no assessment conducted during the period of 2004-2011: Angola, The Democratic Popular Republic of Korea, Ethiopia, Iran, Kenya, Sao Tome and Principe, and Turkmenistan.

Figure 3.Relationship between Jurisdictions with Systemically Important Financial Sectors and Compliance with the AML/CFT Recommendations on Preventing Financial Institutions from ML/TF

Source: Author calculations based on:

1. Table 2 of this annex.

2 Stability Assessments under the Financial Sector Assessment Program into Article IV Surveillance; IMF Policy Paper; August 27, 2010.

Note:

Note that the ranking might change over time (Staff used 2008 data for the paper) when data on size and interconnectedness are updated and/or methodology gets revisited.

The following countries, among the 33 jurisdictions identified by the ICRG as having AML/CFT deficiencies, are not included in this chart due to the fact that there was no assessment conducted during the period of 2004–2011: Angola, The Democratic Popular Republic of Korea, Ethiopia, Iran, Kenya, Sao Tome and Principe, and Turkmenistan.

Table 1.The AML/CFT Groupings
AML/CFT GroupingsAbbreviationRecommendations

included in each

grouping
Definition
Legal MeasuresLegalR.1,R.2,R.3,S.R.I,S.R.II, and S.R.IIIThe “Legal” component captures whether countries have an adequate legal framework, which should include laws that create money laundering (ML) and terrorist financing (FT) offenses and provide for the freezing, seizing, and confiscation of the proceeds of crime and terrorist funding. In particular, the assessment measures the sufficiency of the ML and FT offense definition in the country, the scope of criminal liability for ML/FT, and the existence of criminal sanctions for ML/FT.
Institutional MeasuresInstitutionalR.26, R.27, R.28, R.29,R.30, R.31, and R.32The “Institutional” component captures how well countries provide for institutional structures like Financial Intelligence Units (FIUs), law enforcement agencies, prosecutors, and supervisors to ensure effective compliance with the AML/CFT standard. The institutional component is comprised of the sum of the following recommendations’ rating values: R.26, R.27, R.28, R.29, R.30, R.31, and R.32.
Preventive Measures for FIFinancial Institutions

Prevention
R.4, R.5, R.6, R.7, R.8, R.9, R.10, R.11, R.13, R.14, R.15, R.17, R.18, R.19, R.21, R.22, R.23, R.25, S.R.IV, SR.VI, and S.R.VIIThe Financial Institutions Prevention component captures how well the countries implement laws, regulations, or, under certain circumstances, other enforceable means that impose the preventive measures on financial institutions.43 The Financial Institutions Prevention component is comprised of the sum of the following recommendations’ rating values: R.4, R.5, R.6, R.7, R.8, R.9, R. 10, R.11, R.13, R.14, R.15, R.17, R.18, R.19, R.21, R.22, R.23, R.25, S.R.IV, SR.VI, and S.R.VII.
Preventive measures for DNFBPSDNFBPs PreventionR.12, R.16, and R.24The “Designated Non-Financial Businesses and Professions (DNFBPs) prevention” component captures the degree to which countries implement laws, regulations, or, under certain circumstances, other enforceable means that impose the required obligations on DNFBPs.44 The DNFBPs Prevention component is comprised of the sum of the following recommendations’ rating values: R.12, R.16, and R.24.
Preventive measures for informal

sector
Informal Sector PreventionR.20, and S.R.IX“The Informal Sector Prevention” component captures the degree to which countries implement laws, regulations, or, under certain circumstances, other enforceable means that impose the required obligations on informal sectors (including controls over large cross-border cash movements and application of proportionate measures to relevant businesses not otherwise captured.
Entity TransparencyEntity TransparencyR.33+R.34+ and S.R.VIIIThe “Entity Transparency” component principally measures the power of competent authorities to obtain adequate information on beneficial ownership of trusts. The entity transparency component is composed by the sum of the following recommendations rating values: R.33, R.34 and S.R.VIII.
International CooperationInternational CooperationR.35, R.36, R.37, R.38, R.39, R.40, and S.R.VThe “International Cooperation” component measures the extent to which countries have laws and other measures that give a country the ability to provide the widest range of international cooperation. The international cooperation component is composed by the sum of the following recommendations’ score values: R.35, R.36, R.37, R.38, R.39, R.40, and S.R.V.
Source: 2004 Methodology
Source: 2004 Methodology
Table 2.Countries’ Compliance with Groupings of AML/CFT Recommendations (2004–2011) Advanced Economies
CountryYear of

Assessment
LegalInstitutionalPreventing

Financial

Institutions
Preventing

DNFBPs
Preventing

Informal Sector
Entity

Transparency
International

Cooperation
AMLCFTTotal AML/CFT
Andorra20072.3347.3310.331.33418.33220.33
Austria20082.644.6412.580.990.990.993.6322.164.326.46
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Belgium20054.675.3317.671.3312.335316.3337.33
Bermuda200733.675.67012.335.3317.673.3321
British Virgin20084.675.6711.67121.336.6726.676.3333
Canada200744.338.67021520525
Cayman Islan20074.335.3312.671.331.332.33628.33533.33
Cyprus20054.335.6714.6711.671.67629635
Czech Republ20051.985.319.920.331.321.334.6320.534.2924.82
Denmark200634.678.670.331.331.335204.3324.33
Estonia20083.335.6712.671.332526.674.3331
Finland2007349.330.331.331674.672033424.33
France20103.674.3314.330.671.672525.336.3331.67
Germany200934.331201.670.674.3320.675.3326
Gibraltar20064513.3324.3325.67530.67
Greece200622.337.3300.67414.672.6717.33
Guernsey20104.336191.671.6725.6733.676.6740.33
Hong Kong Ch200735.3312.6700.671.335.3324.673.6728.33
Iceland20062.67410.330.671.331.33421.672.6724.33
Ireland20053.675110.671.336.67254.3329.33
Isle of Man20082.645.315.250.991.321.984.6527.514.6232.13
Israel200745.6711.6701.335.67245.3329.33
Italy200545.3310.67022.336.3324.67630.67
Japan2008359.670.670.33319.333.3322.67
Jersey20084.35.6415.251.321.662.665.329.856.2836.13
Korea20081.673.67801.670.334.6717.332.6720
Liechtenstein20072.675.3310.331.333.3322.332.6725
Luxembourg200923.336.3300.330.674.3314.672.3317
Macau, SAR20063.33413.331.331.332.6723427
Malta200545.6712.671.331.3326.6728.67533.67
Monaco20062.674.33100.331.331.33318.674.3323
Netherlands20103.334.6712.331.671.333225.3327.33
New Zealand20094.334.675.6701.330.335174.3321.33
Norway200544.3313.331.671.331.674.6727.673.3331
Portugal20063.334.67141.671336.67284.6732.67
San Marino20072.332.67400.670.33311.671.3313
Singapore20073.675.6715.670.331.331.335.6727.336.3333.67
Slovakia200523.336.330.330.671.333.6715.332.3317.67
Slovenia20054.675.3313.671.331.672.336.33296.3335.33
Spain20053.673.6713.330.671.3326255.6730.67
Sweden20053.674.33100.671.675.6723.333.6727
Switzerland20054512.331.330.671.675.33264.3330.33
Taiwan, POC20071.335.3311.3300.331.333.67212.3323.33
UK200665.6712.671.331.671.336.67287.3335.33
USA20054.675.6715.330.3325.3327.33734.33
no. of Recommendations6.07.021.03.02.03.07.040.09.049.0
Total countries46.046.046.046.046.046.046.046.046.046.0
Theoretical Compliance276.0322.0966.0138.092.0138.0322.01840.0414.02254.0
Real Compliance157.2217.9521.730.958.066.6226.91072.1207.11279.2
Degree of Compliance57.067.754.022.463.048.270.558.350.056.8
Average Compliance3.44.711.30.71.31.44.923.34.527.8
Albania20112.673910.671.333.6718.672.6721.33
Anguilla200944.3311.3310.331.67624.67428.67
Antigua & Bar20072.333.6730.331.330.335.67151.6716.67
Argentina20091.671.674.6700.6702.679.671.6711.33
Armenia20092.673.3313.670.330.671.673.6722.673.3326
Aruba20081.651.654.9700.6612.9812.580.3312.91
Azerbaijan20081.332500.671.333.3311.67213.67
Baham as20063.675911.331.675.3322.674.3327
Bahrain200524120.670.332522426
Bangladesh20081.652.316.2800.990.332.3111.891.9813.87
Barbados20063.335.338.6701.671.334.3320.334.3324.67
Belarus20083.333.6790.3312.334.3320.673.3324
Benin20091.672.334.33001312.33012.33
Bolivia2006225.33000.33312.330.3312.67
Bosnia and He200922.338.6700.671334.3316.672.6719.33
Botswana20072.335.6700.330312.33012.33
Brazil20093.6713011.334.3321.672.6724.33
Brunei201022.335.3300.3313.6712.332.3314.67
Bulgaria20073.675.3312.6711.3326.3326.675.6732.33
Burkina Faso20091.672.3311.3300.670.672.3316.672.3319
Cam bodia2007013.330.3301.67170.337.33
Cape Verde20071.671.671.6700.331.671.678.330.338.67
Chile20102.974.9611.250.660.990.334.3123.162.3125.47
China2006259.3301.3315.3320.333.6724
Colombia20084.33615.3311.671.33630.335.3335.67
Comoros20091.671.67200.3302.33718
Cook Islands20091.331.33200138.6708.67
Costa Rica20061.333.676.33000.33313.67114.67
Croatia200625600.671.33417.331.6719
Djibouti20071.661.322.64001.333.319.930.3310.26
Dominica20082.31.653.3100.660.333.9710.581.6512.23
Dominican Re20051.332.677.33010.332.6713.33215.33
Ecuador200512.332.33000.671.67808
Egypt200834.3310.330.6712.33522.334.3326.67
El Salvador20094.6739.6701.331.334.6720.334.3324.67
Fiji200623.671011.3313.6720.332.3322.67
Gambia200831.677001313.332.3315.67
Georgia2006246.670.670.671.674.3318220
Ghana20081.652.314.6300.330.332.319.581.9811.56
Grenada20081.983.632.9800.3304.9813.240.6613.9
Guatemala200933.6713.3301.331522.674.6727.33
Guinea Bissau20081.3212.3100.3312.317.940.338.27
Haiti20070.671.67400.3312.339.670.3310
Honduras20072.642.656.6500.3302.6412.592.3214.91
Hungary201035.3317.331.671.3325.3331.674.3336
India20092.67513010.674.3322.67426.67
Indonesia20071.333.337.6701.331316.331.3317.67
Jam aica200544.6711011.67421.33526.33
Jordan20081.673.339.330.3301.672.6717.671.3319
Kyrgyz Republ20070.6739.3301.331.333.3317.671.3319
Latvia20063.675.3310.670.67125253.3328.33
Lebanon20093.673.67131114.6723528
Lithuania20062.674.671311.331.675.6726430
Macedonia20072.333.676.33011.333.6716.33218.33
Maawi20082.672.679.67010.674182.6720.67
Malaysia20073.675141114.3325.674.3330
Mali20081.330.671.670011.6760.336.33
M auritania20051.6725.6700.671.67412.67315.67
Mauritius20072.333.6710.330.331.331.334.33212.6723.67
Mexico20082.334.3312.3300.3314.33222.6724.67
Moldova2005236.33011.674.3315.672.6718.33
Mongolia200612.33601.3313.6714.3315.33
Montenegro20082.675120.6711.335252.6727.67
Morocco200721.334.67001.674.3312.331.6714
Myanmar20081.33360.330.671.671.6713.67114.67
Namibia2005123.33010.3339.67110.67
Nepal20050.331.653.98011.990.337.291.999.28
Nicaragua20082.641.988.2700.991.334.3116.882.6419.52
Niger20081.321.332.6400.331.333.9710.260.6610.92
Nigeria20071.333.334.670.330.6712.6713.330.6714
Pakistan200901.672.330101.676.6706.67
Palau20082.6734.6701.3313.6713.672.6716.33
Panama20054515.331115.6727.675.3333
Paraguay200811.33400028.3308.33
Peru20083.6759.67112523.673.6727.33
Philippines20081.652.979.600.991.323.9718.521.9820.5
Poland20062.334.337.670.331.671.33419.67221.67
Qatar200723.335.670.330.331.672.6714.671.3316
Romania2007359.330.33125.67233.3326.33
Russian Feder200744.679.67111.675.6724.333.3327.67
Rwanda20050.661.664.32002.322.329.31.9811.28
Samoa20061.332.336110.331.6712.331.3313.67
Saudi Arabia20092.334.331301.3323.3322.673.6726.33
Senegal20072.974.636.630.330.991.334.9819.881.9821.86
Serbia20092.333.67110.3311.333.6720.33323.33
Seychelles20061.981.325.6300.3302.6410.251.6511.9
Sierra Leone2006113.3300.330.330.676.6706.67
Solomon Islan20093.334900.330.334.33183.3321.33
South Africa200844.6780.671.330.675.3320.334.3324.67
Sri Lanka200622.334.6700.3313.33121.6713.67
St. Kitts & Nev20082.312.319.280.3311.654.6519.222.3121.53
St. Lucia20081.331.33200.330.331.336.330.336.67
St. Vincent & t20092.674.338.670114.3319.672.3322
Sudan200420.333.33011.332.338.671.6710.33
Suriname20091.332.671.6700.331310010
Syria20062.333.339.330.670.671.67319221
Tajiskitan20070.671.3330010606
Tanzania200901.672.330101.676.6706.67
Thailand20072.672.675.6700.331.332.6713.33215.33
Tonga200913.335.33000.332.33111.3312.33
Trinidad and T20050.672.67201.670.3339.33110.33
Tunisia20063.33480.671.332.674.33204.3324.33
Turkey20062.673.336.3301.671.673.6716.33319.33
Turks & Caico200733.335.3300.330.674142.6716.67
UAE2007347.3300.3324.3318.332.6721
Uganda20050.670.673.67000.33151.336.33
Ukraine20081.673.679.33011.673.6718.332.6721
Uruguay20094612.330.671.331.675.6726.67531.67
Uzbekistan20093.334.3311.3311.331.67523.674.3328
Vanuatu20062.331.338.3300.330.333.67142.3316.33
Venezuela20082.312.988.94000.334.9717.551.9819.53
Vietnam20080.992.645.9700.990.661.9812.570.6613.23
Yemen200711.673.330.330.671.67210.330.3310.67
Zam bia20070.661.982.97000.331.657.260.337.59
Zimbawe200612.6790.670.670.671.6715.33116.33
no. of Recommendations6721323740949
Total countries115115115115115115115115115115
Theoretical Compliance6908052415345230345805460010355635
Real Compliance243.3352.6839.928.085.2126.9407.61833.2250.32083.5
Degree of Compliance35.343.834.88.137.036.850.639.924.237.0
Average Compliance2.13.17.30.20.71.13.515.92.218.1
Source: Staff calculations.The table is not meant to describe a jurisdiction’s current level of compliance with the AML/CFT standard, but rather the level of compliance at the time of its most recent DARs and MERs, indicated in the column “Year of Assessment.” Where DARs and MERs are not published the cells are left blank. Staff used the original compliance rating data, where the measure of compliance was defined as C, ‘Compliant,’ LC, ‘Largely Compliant,’ PC, ‘Partially Compliant,’ NC, ‘Non-Compliant,’ and NA, ‘Not Applicable.’ In order to provide a quantitative measure of AML/CFT compliance we replaced existing ratings with the following numbers: C-’1’, LC-’0.66’, PC-’0.33’ and NC-’0’, NA-’1.’ The legal measures include R.1, R.2, R.3, SR.I, SR.II, and SR.III. Concerning the measurement of components of the AML/CFT regime: Institutional measures are evaluated through the scores on R.26, R.27, R.28, R.29, R.30, R.31, and R.32. Preventive financial sector measures through scores for R.4, R.5, R.6, R.7, R.8, R.9, R.10, R.11, R.13, R.14, R.15, R.17, R.18, R.19, R.21, R.22, R.23, R.25, SR.IV, SR.VI, and SR.VII. For preventive DNFBPs measures: R.12, R.16, and R.24. Measures preventing the abuse of the informal sector: R.20, and SR.IX. Entity transparency measures: R.33, R.34, and SR.VIII. International cooperation measures: R.35, R.36, R.37, R.38, R.39, R.40, and SR.V. AML-specific compliance is measured by the scores on FATF Recommendations 1 to 40. CFT-specific compliance through those on FATF Special Recommendations I to IX.For each grouping of recommendations, the level of compliance is the sum of the numbers assigned to each individual rating composing the subset (e.g. for the grouping related to the informal sector, which includes R.20 and SR.IX, if both recommendations are rated PC, the level of compliance would be 0.66. The maximum level of compliance would be 2 if both recommendations are rated C).The list of advanced economies includes those economies defined in the WEO (2011) and major OFCs.
Source: Staff calculations.The table is not meant to describe a jurisdiction’s current level of compliance with the AML/CFT standard, but rather the level of compliance at the time of its most recent DARs and MERs, indicated in the column “Year of Assessment.” Where DARs and MERs are not published the cells are left blank. Staff used the original compliance rating data, where the measure of compliance was defined as C, ‘Compliant,’ LC, ‘Largely Compliant,’ PC, ‘Partially Compliant,’ NC, ‘Non-Compliant,’ and NA, ‘Not Applicable.’ In order to provide a quantitative measure of AML/CFT compliance we replaced existing ratings with the following numbers: C-’1’, LC-’0.66’, PC-’0.33’ and NC-’0’, NA-’1.’ The legal measures include R.1, R.2, R.3, SR.I, SR.II, and SR.III. Concerning the measurement of components of the AML/CFT regime: Institutional measures are evaluated through the scores on R.26, R.27, R.28, R.29, R.30, R.31, and R.32. Preventive financial sector measures through scores for R.4, R.5, R.6, R.7, R.8, R.9, R.10, R.11, R.13, R.14, R.15, R.17, R.18, R.19, R.21, R.22, R.23, R.25, SR.IV, SR.VI, and SR.VII. For preventive DNFBPs measures: R.12, R.16, and R.24. Measures preventing the abuse of the informal sector: R.20, and SR.IX. Entity transparency measures: R.33, R.34, and SR.VIII. International cooperation measures: R.35, R.36, R.37, R.38, R.39, R.40, and SR.V. AML-specific compliance is measured by the scores on FATF Recommendations 1 to 40. CFT-specific compliance through those on FATF Special Recommendations I to IX.For each grouping of recommendations, the level of compliance is the sum of the numbers assigned to each individual rating composing the subset (e.g. for the grouping related to the informal sector, which includes R.20 and SR.IX, if both recommendations are rated PC, the level of compliance would be 0.66. The maximum level of compliance would be 2 if both recommendations are rated C).The list of advanced economies includes those economies defined in the WEO (2011) and major OFCs.
Annex 2. Empirical Evidence: Determinants of the AML/CFT Compliance (2004– 2008)45

Figure 1.Overall Compliance with AML/CFT by Income Groups (2004–2008)1/

Source: Author’s calculations.

1/The degree of compliance is measured along the vertical axis. The further from the origin (0.0), the higher the degree of compliance. The other axes represent each component of the AML/CFT Compliance Index. Compliance is presented as share of the real and theoretical maximum ratings.

Figure 2.Overall AML/CFT Compliance by Income and Regions (2004–2008)

Figure 3.The AML/CFT Index vs. the AML/CFT Predicted Values

Figure 4.Overall Compliance with Legal Measures (2004–2008)

(Statistics, by Income and Region Groups, Predicted Values)

Figure 5.Overall Compliance with Institutional Measures (2004–2008)

(Statistics, by Income and Region Groups, Predicted Values)

Figure 6.Overall Compliance with Preventive Financial Sector Measures (2004–2008)

(Statistics, by Income and Region Groups, Predicted Values)

Figure 7.Overall Compliance with Preventive DNFBPs Measures (2004–2008)

(Statistics, by Income and Region Groups, Predicted Values)

Figure 8.Overall Compliance with Measures Preventing the Abuse of the Informal Sector (2004–2008)

(Statistics, by Income and Region Groups, Predicted Values)

Figure 9.Overall Compliance with Entity Transparency Measures (2004–2008)

(Statistics, by Income and Region Groups, Predicted Values)

Figure 10.Overall Compliance with International Cooperation Measures (2004–2008)

(Statistics, by Income and Region Groups, Predicted Values)
Table 1.Assessed Countries by Income Group
Assessed Countries by income groups
LowLow MiddleUpper MiddleHigh
CambodiaAlbaniaMexicoAustralia
GambiaAzerbaijanRussian FederationBelgium
HaitiBoliviaSouth AfricaCanada
Kyrgyz RepublicCape VerdeTurkeyDenmark
MalawiChinaFijiFinland
MaliColombiaMalaysiaGreece
MauritaniaDjiboutiPalauHong Kong, China
MyanmarDominican RepubCosta RicaIceland
NepalEcuadorJamaicaIreland
NigeriaEgyptPanamaItaly
RwandaGeorgiaSta LuciaJapan
SenegalIndiaBelarusNorway
Sierra LeoneIndonesiaBotswanaPortugal
TajiskitanJordanMauritiusSingapore
UgandaMacedoniaChileSpain
YemenMoldovaUruguaySweden
ZimbaweMongoliaBulgariaSwitzerland
MoroccoCroatiaUK
NamibiaLatviaUSA
ParaguayLithuaniaBrunei
PeruMontenegroMacau, SAR
SamoaPolandKorea
Sri LankaRomaniaTaiwan, POC
SudanAntigua & Barbuda
SyriaBermuda
ThailandBahamas
TunisiaBarbados
UkraineBritish Virgin Islands
VanuatuCayman Islands
Trinidad and Tobago
Turks & Caicos Islands
Bahrain
Qatar
UAE
Andorra
Cyprus
Czech Republic
Estonia
Hungary
Israel
Liechtenstein
Malta
Monaco
San Marino
Slovakia
Slovenia
Gibraltar
Source: World Bank (2007
Source: World Bank (2007
Table 2.The AML/CFT Compliance Index by Components (2004–2008
Compliance Index

Components
AbbreviationRecommendations

included in each

grouping
Definition
Legal MeasuresLegalR.1,R.2,R.3,S.R.I,S.R.II, and S.R.IIIThe “Legal” component captures whether countries have an adequate legal framework, which should include laws that create money laundering (ML) and terrorist financing (FT) offenses and provide for the freezing, seizing, and confiscation of the proceeds of crime and terrorist funding. In particular, the assessment measures the sufficiency of the ML and FT offense definition in the country, the scope of criminal liability for ML/FT, and the existence of criminal sanctions for ML/FT. The sum is demeaned (using the arithmetic mean) and divided by its standard deviation.
Institutional MeasuresInstitutionalR.26, R.27, R.28, R.29,R.30, R.31, and R.32The “Institutional” component captures how well countries provide for institutional structures like Financial Intelligence Units (FIUs), law enforcement agencies, prosecutors, and supervisors to ensure effective compliance with the AML/CFT standard. The institutional component is comprised of the sum of the following recommendations’ rating values: R.26, R.27, R.28, R.29, R.30, R.31, and R.32. The sum is demeaned (using the arithmetic mean) and divided by its standard deviation.
Preventive measures for FIFinancial Institutions PreventionR.4, R.5, R.6, R.7, R.8, R.9, R.10, R.11, R.13, R.14, R.15, R.17, R.18, R.19, R.21, R.22, R.23, R.25, S.R.IV, SR.VI, and S.R.VIIThe “Financial Institutions Prevention” component captures how well the countries implement laws, regulations, or, under certain circumstances, other enforceable means that impose the preventive measures on financial institutions.46 The Financial Institutions Prevention component is comprised of the sum of the following recommendations’ rating values: R.4, R.5, R.6, R.7, R.8, R.9, R.10, R.11, R.13, R.14, R.15, R.17, R.18, R.19, R.21, R.22, R.23, R.25, S.R.IV, SR.VI, and S.R.VII. The sum is demeaned (using the arithmetic mean) and divided by its standard deviation.
Preventive measures for

DNFBPS
DNFBPs PreventionR.12, R.16, and R.24The “Designated Non-Financial Businesses and Professions (DNFBPs) prevention” component captures the degree to which countries implement laws, regulations, or, under certain circumstances, other enforceable means that impose the required obligations on DNFBPs.47 The DNFBPs Prevention component is comprised of the sum of the following recommendations’ rating values: R. 12, R.16, and R.24. The sum is demeaned (using the arithmetic mean) and divided by its standard deviation.
Preventive measures for

informal sector
Informal Sector PreventionR.20, and S.R.IX“The Informal Sector Prevention” component captures the degree to which countries implement laws, regulations, or, under certain circumstances, other enforceable means that impose the required obligations on informal sectors (including controls over large cross-border cash movements and application of proportionate measures to relevant businesses not otherwise captured. The sum is demeaned (using the arithmetic mean) and divided by its standard deviation.
Entity TransparencyEntity TransparencyR.33+R.34+ and S.R.VIIIThe “Entity Transparency” component principally measures the power of competent authorities to obtain adequate information on beneficial ownership of trusts. The entity transparency component is composed by the sum of the following recommendations rating values: R.33, R.34 and S.R.VIII. The sum is demeaned (using the arithmetic mean) and divided by its standard deviation.
International CooperationInternational CooperationR.35, R.36, R.37, R.38, R.39, R.40, and S.R.VThe “International Cooperation” component measures the extent to which countries have laws and other measures that give a country the ability to provide the widest range of international cooperation. The international cooperation component is composed by the sum of the following recommendations’ score values: R.35, R.36, R.37, R.38, R.39, R.40, and S.R.V. The sum is demeaned (using the arithmetic mean) and divided by its standard deviation.
Note: The index is not meant to describe a jurisdiction’s current level of compliance with the AML/CFT standard, but rather the level of compliance at the time of its DARs and MERs during 2004–2008. Staff used the original compliance rating data, where the measure of compliance was defined as C, ‘Compliant,’ LC, ‘Largely Compliant,’ PC, ‘Partially Compliant,’ NC, ‘Non-Compliant,’ and NA, ‘Not Applicable.’ In order to provide a quantitative measure of AML/CFT compliance we replaced existing ratings with the following numbers: C-‘1’, LC-‘0.66’, PC-‘0.33’ and NC-‘0’, NA-‘1’.
Note: The index is not meant to describe a jurisdiction’s current level of compliance with the AML/CFT standard, but rather the level of compliance at the time of its DARs and MERs during 2004–2008. Staff used the original compliance rating data, where the measure of compliance was defined as C, ‘Compliant,’ LC, ‘Largely Compliant,’ PC, ‘Partially Compliant,’ NC, ‘Non-Compliant,’ and NA, ‘Not Applicable.’ In order to provide a quantitative measure of AML/CFT compliance we replaced existing ratings with the following numbers: C-‘1’, LC-‘0.66’, PC-‘0.33’ and NC-‘0’, NA-‘1’.
Table 3.Variables and Data Sources
AbbreviationVariableSource
AMLCFTCIAMLCFT Compliance Index116 country’ s MERs/DARs from 2004 to 2008
LegalLegal Measures116 country’ s MERs/DARs from 2004 to 2008
InstitutionalInstitutional Measures116 country’s MERs/DARs from 2004 to 2008
Financial Institutions

Prevention
Financial Institutions Prevention Measures116 country’s MERs/DARs from 2004 to 2008
DNFPBs PreventionDNFPBs Prevention Measures116 country’s MERs/DARs from 2004 to 2008
Informal Sector

Prevention
Informal Sector Prevention Measures116 country’s MERs/DARs from 2004 to 2008
Entity TransparencyEntity Transparency Measures International Cooperation116 country’s MERs/DARs from 2004 to 2008
International CooperationMeasures116 country’s MERs/DARs from 2004 to 2008
PPP PC GDPAdj PPP GDP per capitaWEO (Average 2005-2007)
Crim ML/FTCriminalization of ML/FTInternational Narcotics Control Strategy Report INCSR (2005,2006,2007, 2008)
RQRegulatory Quality FrameworkWorld Governance Indicators, World Bank. Average (2005-2007)
COControl of corruptionWorld Governance Indicators, World Bank. Average (2005-2007)
BFATFFATF membershipFATF Website
IDI2005International Drugs Index 2005UNODC (2005)
M2/GDPM2/GDP RatioInternational Financial Statistics (IMF), World Economic Outlook, The Economist Intelligence Unit(Country Data), World Development Indicators (World Bank). Average (2005-2007)
TradeopTrade opennessWorld Development Indicators (World Bank) and WEO. Average (2005-2007)
NimNet Interest MarginA New Database on Financial Development and Structure. World Bank.(Average 2005-2007)
Foreign Direct

Investment/GDP
Foreign Direct Investment Net Inflows/GDPWorld Development Indicators. World Bank. Average (2005-2007)
E 2007MER/DAR in 2007MER/DARs
RNFSERatio Net Financial Services ExportsZorome (2007)
Bank concentrationBank ConcentrationA New Database on Financial Development and Structure. World Bank. Average (2005-2007)
Table 4.Selected Countries (2004–2008)
CountryOnsite VisitYearBodyAssessor Body
Australia10-Mar2005FATFFATF
Belgium17-Jan2005FATFFATF
Canada19-Mar2007FATFFATF
China13-Nov2006FATFFATF
Denmark27-Feb2006FATFIMF
Finland16-Apr2007FATFFATF
Greece20-Nov2006FATFFATF
Hong Kong, China12-Nov2007FATFFATF
Iceland24-Apr2006FATFFATF
Ireland27-Jun2005FATFFATF
Italy20-Apr2005FATFIMF
Japan6-Mar2008FATFFATF
Mexico15-Jan2008FATFIMF
Norway17-Jan2005FATFFATF
Portugal6-Mar2006FATFFATF
Russian Federation25-Sep2007FATFFATF
Singapore3-Sep2007FATFFATF
South Africa4-Aug2008ESAAMLGFATF
Spain12-Sep2005FATFFATF
Sweden5-Sep2005FATFFATF
Switzerland4-Apr2005FATFFATF
Turkey4-Sep2006FATFFATF
UK27-Nov2006FATFFATF
USA7-Nov2005FATFFATF
Brunei25-Jan2005APGAPG
Cambodia26-Feb2007APGWB
Fiji20-Feb2006APGWB
India14-Mar2005APGAPG
Indonesia29-Oct2007APGAPG
Macau, SAR4-Dec2006APGAPG
Malaysia29-Jan2007APGAPG
Mongolia4-Dec2006APGAPG
Myanmar7-Jan2008APGAPG
Nepal1-Feb2005APGAPG
Korea3-Nov2008APGFATF
Palau3-Mar2008APGIMF
Samoa6-Feb2006APGAPG
Sri Lanka27-Feb2006APGAPG
Taiwan, POC28-Jan2007APGAPG
Thailand26-Feb2007APGIMF
Vanuatu27-Feb2006APGAPG
Antigua & Barbuda28-May2007CFATFCFATF
Bermuda7-May2007CFATFIMF
Bahamas22-May2006CFATFCFATF
Barbados4-Dec2006CFATFCFATF
British Virgin Islands11-Feb2008CFATFCFATF
Cayman Islands4-Jun2007CFATFCFATF
Costa Rica3-Jul2006CFATFCFATF
Dominican Republic3-Oct2005CFATFCFATF
Haiti24-Sep2007CFATFIMF
Jamaica4-Apr2005CFATFCFATF
Panama1-May2005CFATFIMF
St. Lucia4-Feb2008CFATFCFATF
Trinidad and Tobago30-May2005CFATFCFATF
Turks & Caicos

Islands
27-Sep2007CFATFCFATF
Belarus28-Jul2008EAGWB
Kyrgyz Republic28-Jan2007EAGEAG
Tajiskistan11-Jun2007EAGWB
Botswana26-Feb2007ESAAMLGWB
Malawi25-Feb2008ESAAMLGWB
Mauritius24-Sep2007ESAAMLGEAG
Namibia24-Oct2005ESAAMLGWB
Uganda14-Feb2005ESAAMLGWB
Zimbawe8-May2006ESAAMLGESAAMLG
Bolivia3-Apr2006GAFISUDGAFISUD
Chile24-Sep2006GAFISUDGAFISUD
Colombia30-June2008GAFISUDGAFISUD
Ecuador10-Sep2005GAFISUDGAFISUD
Paraguay24-jun2008GAFISUDGAFISUD
Peru12-April2008GAFISUDGAFISUD
Uruguay3-Nov2005GAFISUDIMF
Cape Verde30-Apr2007GIABAIMF
Gambia14-Apr2008GIABAGIABA
Mali4-Aug2008GIABAWB
Nigeria24-Sep2007GIABAGIABA
Senegal28-Sep2004GIABAWB
Sierra Leone29-May2006GIABAWB
Bahrain17-Apr2005MENAFATFIMF
Egypt12-Oct2008MENAFATFWB
Jordan6-Jul2008MENAFATFMENAFATF
Mauritania14-May2005MENAFATFWB
Morocco29-Jan2007MENAFATFMENAFATF
Qatar4-Feb2007MENAFATFIMF
Sudan30-Nov2004MENAFATFWB
Syria29-Apr2006MENAFATFMENAFATF
Tunisia16-Jan2006MENAFATFWB
UAE28-Feb2007MENAFATFIMF
Yemen21-Jul2007MENAFATFMENAFATF
Albania12-Sep2005MONEYVALMONEYVAL
Andorra17-Oct2007MONEYVALMONEYVAL
Azerbaijan12-Apr2008MONEYVALMONEYVAL
Bulgaria22-Apr2007MONEYVALMONEYVAL
Croatia25-Sep2006MONEYVALMONEYVAL
Cyprus3-Apr2005MONEYVALMONEYVAL
Czech Republic10-Apr2005MONEYVALMONEYVAL
Estonia3-Feb2008MONEYVALMONEYVAL
Georgia23-Apr2006MONEYVALMONEYVAL
Hungary21-Feb2005MONEYVALIMF
Israel11-Apr2007MONEYVALMONEYVAL
Latvia8-Mar2006MONEYVALIMF
Lithuania8-Jan2006MONEYVALMONEYVAL
Liechtenstein21-Mar2007MONEYVALIMF
Macedonia25-Mar2007MONEYVALMONEYVAL
Malta13-Nov2005MONEYVALMONEYVAL
Moldova24-Jan2005MONEYVALMONEYVAL
Monaco6-Nov2006MONEYVALMONEYVAL
Montenegro15-Sep2008MONEYVALMONEYVAL
Poland14-May2006MONEYVALMONEYVAL
Romania6-May2007MONEYVALMONEYVAL
San Marino4-Mar2007MONEYVALMONEYVAL
Slovakia8-May2005MONEYVALMONEYVAL
Slovenia30-Jan2005MONEYVALMONEYVAL
Ukraine21-Sep2008MONEYVALMONEYVAL
Djibouti16-Oct2007NONFSBRIMF
Gibraltar1-Mar2006NONFSRBIMF
Rwanda7-Mar2005NONFSBRWB
Sources: MERs/DARs
Sources: MERs/DARs
Table 5.Variables: Descriptive Statistics (2004–2008)
Variable#CountriesMeanStd.Dev.MinMax
AMLCFT Compliance Index11647.4425.280100
Legal11642.9119.760100
Institutional11658.7225.690100
Financial Institutions

Prevention
11642.6723.530100
DNFBPs Prevention11624.4828.040100
Informal Sector Prevention11645.2526.990100
Entity Transparency11649.6723.040100
International Cooperation11659.6123.550100
PCA Compliance Index11644.2323.520100
Log GDP PPP per capita1163.980.5482.27645.071
Criminalization ML/FT1162.590.8003
Regulatory Quality

Framework
11060.2426.400.8199.67
Control Corruption11057.8627.450.7999.83
FATF Member1160.190.4001
IDI11613.8211.721.3852.67
M2/GDP10065.2955.520.34347.28
Trade Openness10691.6362.110.445443.20
Net Interest Margin1060.0440.0260.0060.125
Foreign Direct

Investment/GDP
1000.060.065-0.0540.378
Country Assessment 20071160.280.4501
Ratio of Net Financial

Services Exports
730.995.30-0.4242.08
Bank Concentration1110.680.200.0141
Sources: Author’s calculations.
Sources: Author’s calculations.
Table 6.Profile of Overall Compliance with the FATF 40+ 9 Special Recommendations 2004–2008
FATF 40+9 Special

recommendations
Non-

Compliant

In Percent
Partially

Compliant

In Percent
Largely

Compliant

In Percent
Compliant

In Percent
Not

Applicable

In percent
Assessed

Countries/

Jurisdic.
1.ML offence6.9050.8638.373.450.00116
2.ML offence-mental element and corporate liability3.4529.3146.5520.690.00116
3.Confiscation and provisional measures5.1741.3842.2411.210.00116
4.Secrecy laws consistent with the Recommendations0.0016.3831.0352.590.00116
5.Customer due diligence36.2156.037.760.00116
6.Politically exposed persons62.9322.4113.790.860.00116
7.Correspondent banking54.3119.8318.976.900.00116
8.New technologies & non face-to face business34.4835.3417.2412.930.00116
9.Third parties and introducers22.4128.4510.347.7631.03116
10.Record keeping9.4832.7638.7918.970.00116
11.Unusual transactions25.8648.2820.695.170.00116
12.DNFBP- R.5,6,8-1166.3832.760.860.000.00116
13.Suspicious transaction reporting22.4150.8624.141.720.00116
14. Protection no tipping-off7.7626.7224.1441.380.00116
15.Internal controls, compliance & audit15.5255.1727.591.720.00116
16.DNFBP-R.13-15 &2160.3436.213.450.000.00116
17.Sanctions18.1055.1725.001.720.00116
18.Shell Banks12.0743.1023.2821.550.00116
19.Other forms of reporting20.696.036.9066.380.00116
20.Other NFBP & secure transaction techniques21.5518.9723.2836.210.86116
21.Special attention for higher risk countries46.5534.4813.795.170.00116
22.Foreign Branches & subsidiaries40.5225.0018.107.7610.34116
23.Regulation, supervision and monitoring20.6955.1723.280.860.00116
24.DNFBP-regulation,supervision and monitoring60.3434.485.170.000.00116
25.Guidelines & feedback36.2138.7921.553.450.00116
26.The FIU19.8327.5940.5212.070.00116
27.Law enforcement authorities6.9032.7637.0723.280.00116
28.Powers of competent authorities0.8612.0719.8367.240.00116
29.Supervisors9.4844.8333.6212.070.00116
30.Resources, integrity and training17.2449.1431.032.590.00116
31.National Co-operation10.3436.2137.9315.520.00116
32.Statitstics31.9039.9627.590.860.00116
33.Legal persons beneficial owners22.4150.8619.836.900.00116
34.Legal arrangements beneficial owners13.7925.869.487.7643.10116
35.Convention7.7649.1437.935.170.00116
36.Mutual Legal Assistance(MLA)4.3129.3148.2818.100.00116
37.Dual Criminality3.4519.8332.6243.100.00116
38.MLA on confiscation and freezing9.4835.3443.9711.210.00116
39.Extradition11.2115.5245.6927.590.00116
40.Other forms of cooperation
6.9035.3432.7625.000.00116
SR.I. Implement UN Instruments28.4548.2820.692.590.00116
SR.II. Criminalize Terrorist Financing27.5937.9327.596.900.00116
SR.III. Freeze/confiscate terror assets39.6643.9714.661.720.00116
SR.IV. Suspicious transaction report41.3826.7225.866.030.00116
SR.V. International Cooperation24.1427.5939.668.620.00116
SV.V.I. Requirements for money

transfer
33.6237.0721.556.900.86116
SR.VII. Wire transfer rules49.1432.7614.663.450.00116
SR.VIII. Non-profit organisations36.2143.9714.665.170.00116
SR.IX. Bearer instruments38.7937.9313.794.315.17116
Source: Author Calculations; DARs; MERs.Note: Not applicable is considered as compliant in this research
Source: Author Calculations; DARs; MERs.Note: Not applicable is considered as compliant in this research
Table 7.Correlations Between Variables (2004–2008)
CorrelationsAML/CFT

Comliance

Index
PCAAdj PPP

GDP per

capita
Crim

ML/FT
RQCOFATF

Member
IDIM2/GDPTrade

Op
NIMFDI/GDPA

2007
RNFSEBaco
AMLCFT Index1
PCA0.78*1
Adj PPP GDP

per capita
0.62*0.42*1
Criminalization

ML/FT
0.38*0.29*0.48*1
Regulatory

Quality

Framework
0.64*0.40*0.86*0.44*1
Control

Corruption
0.57*0.35*0.82*0.43*0.92*1
FATF Member0.39*0.110.41*0.22*0.47*0.45*1
IDI0.07830.070.20*0.130.010.09-0.011
M2/GDP0.38*0.160.37*0.27*0.46*0.45*0.29*-0.011
Trade Openness0.22*0.160.18*0.16*0.21*0.15*0.05-0.130.32*1
Net Interest

Margin
-0.44*-0.36*-0.58*-0.30*-0.48*-0.53*-0.26*-0.10-0.42-0.21*1
Foreign Direct

Investment/GDP
0.190.20*0.170.20*0.26*0.26*-0.08-0.020.28*0.42*-0.101
Country

Assessment

2007
-0.12-0.080.090.080.010.02-0.070.050.150.20*-0.160.141
Ratio Net

Financial

Services Exports
0.040.090.27*0.080.170.18-0.08-0.020.37*0.30*-0.150.33*0.28*1
Bank

concentration
0.010.050.05-0.010.110.15-0.050.050.020.130.000.25*0.0070.181
Sources: Author’s calculations.Note: One asterisk denotes statistical significance at 5% percent level.
Sources: Author’s calculations.Note: One asterisk denotes statistical significance at 5% percent level.
Table 8.Cross-Sectional OLS Regressions: Determinants of AML/CFT Compliance and PCA Indices (2004–2008)
DEPENDENT VARIABLES:AML/CFT Compliance Index and PCA
Independent VariablesAMLCFT

Compliance

Index (1)
AMLCFT

Compliance

Index (2)
AMLCFT

Compliance

Index (3)
AMLCFT

Compliance

Index (4)
PCA

Compliance

Index (5)
PCA

Compliance

Index (6)
PCA

Compliance

Index (7)
PCA

Compliance

Index(8)
PPP GDP per capita US dollars28.64***

[3.45]
18.27***

[3.07]
Criminalization ML/FT4.90*

[2.89]
2.56

[5.41]
5.59*

[3.01]
5.05**

[2.58]
4.56

[5.33]
5.79*

[2.71]
Regulatory Quality Framework0.72 ***

[0.25]
0.60**

[0.31]
0.67*

[0.25]
0.25

[0.23]
0.28

[0.33]
0.31

[0.26]
Control Corruption-0.40*

[0.21]
-0.25

[0.27]
-0.23

[0.21]
-0.18

[0.23]
-0.06

[0.34]
-0.03

[0.325]
FATFMember6.09

[5.41]
4.42

[6.42]
5.74

[5.22]
-5.45

[7.15]
-11.69

[8.22]
-6.62

[6.75]
0.12

[0.16]
-0.02

[0.21]
0.20

[0.17]
-0.05

[0.17]
-0.21

[0.18]
0.07

[0,20]
IDI 2005 M2/GDP0.004

[0.037]
0.03

[0.03]
-0.02

[0.04]
0.007

[0.041]
Trade Openness0.016

[0.039]
-0.03

[0.03]
0.04

[0.03]
-0.25

[0.43]
-0.07

[0.04]
0.02

[0.042]
Net Interest Margin-231.74**

[117.44]
-272.86**

[114.88]
-356.24***

[108.16]
-250.01*

[129.53]
Foreign Direct Investment/GDP55.48

[61.92]
132.34**

[61.91]
8.67

[45.01]
126.34

[62.91]
130.45*

[76.18]
40.63

[53.99]
Country Assessment 2007-8.62**

[4.37]
-3.23

[6.06]
-9.53**

[4.37]
-9.18*

[5.16]
-1.86

[7.33]
-8.81*

[4.94]
Ratio Net Financial Services Exports2.01

[3.49]
5.54

[4.23]
Bank concentration-7.55

[10.72]
-13.09

[10.98]
Observations116886791116886791
R-squared0.380.550.520.530.180.340.360.26
Sources: Author’s calculations.Note: The dependent variables are the compliance index or the PCA index. Robust errors are in brackets. One, two, and three asterisks denote statistical significance at the 10, 5, and1 percent level, respectively.
Sources: Author’s calculations.Note: The dependent variables are the compliance index or the PCA index. Robust errors are in brackets. One, two, and three asterisks denote statistical significance at the 10, 5, and1 percent level, respectively.
Table 9.Cross-sectional OLS Regressions: Determinants of AML/CFT Compliance Index Components 2004–2008
Dependent Variables: Components AML/CFT Compliance Index
Independent

Variables
Legal MeasuresInstitutionalFinancial

Institutions

Prevention
DNFBP’s

Prevention
Informal Sector

Prevention
Entity

Transparency
International

Cooperation
Log adj. PPP GDP

per capita in US

Dollars
22.00*** (2.64)32.5***

[3.37]
21.19***

[3.65]
20.91***

[4.52]
21.91***

[4.19]
7.63**

[3.64]
25.93

[3.45]
obv 116 R-squared:0.37obv 116 R-squared:0.48obv 116 R-squared:0.24obv 116 R-squared:0.16obv 116 R-squared:0.18obv 116 R-squared:0.03obv 116 R-squared:0.36
Criminalization

ML/FT
4.44**

[2.25]
7.94***

[2.74]
3.49

[2.72]
6.46**

[3.06]
-1.89

[3.56]
0.90

[6.16]
3.23

[3.03]
Regulatory

Quality

Framework
0.32*

[0.18]
0.72***

[0.23]
0.74***

[0.23]
0.10

[0.25]
0.67**

[0.31]
-0.24

[0.28]
0.69

[0.23]**
Control

Corruption
-0.04

[0.17]
-0.32

[0.20]
-0.5**

[0.20]
0.09

[0.27]
-0.38

[0.28]
0.009

[0.28]
-0.35*

[0.19]
FATF Member6.24

[4.85]
1.17

[5.49]
4.46

[5.04]
-0.67

[9.36]
10.24

[7.57]
2.43

[5.78]
8.36*

[5.15]
IDI0.002

[0.14]
0.16

[0.18]
0.18

[0.14]
-0.08

[0.17]
-0.32

[0.22]
-0.09

[0.18]
0.16

[0.17]
M2/GDP0.004

[0.037]
0.02

[0.03]
0.02

[0.03]
-0.08*

[0.05]
-0.02

[0.04]
-0.06*

[0.04]
0.002

[0.038]
Trade Openness-0.364

[0.032]
0.01

[0.03]
0.05

[0.03]
-0.03

[0.04]
-0.06

[0.04]
-0.03

[0.03]
0.011

[0.032]
Net Interest

Margin
-149.00*

[82.13]
-130.57

[110.37]
-143.01

[112.01]
-240.19

[136.04]*
-268.28**

[122.7]
-519.67***

[103.36]
-187.24

[116.14]
Foreign Direct

Investment/GDP
30,31

[42.44]
32.64

[56.76]
37.11

[57.84]
145.27**

[70.7]
11.28

[54.29]
160.77***

[53.99]
20.95

63.33[]
Country

Assessment 2007
-4.81

[4.11]
-5.97

[4.621]
-9.21

[3.92]
-12.85**

[6.01]
-2.044

[5.90]
-4.54

[5.22]
-4.686

4.718
Observations[88]888888888888
R-squared0.490.570.480.300.320.280.50
Dependent Variables: Components AML/CFT Compliance IndexSources: Author’s calculations. ssNote: The dependent variables are the compliance index components. Robust errors are in brackets. One, two, and three asterisks denote statistical significance at the 10, 5, and 1 percent level, respectively.
Dependent Variables: Components AML/CFT Compliance IndexSources: Author’s calculations. ssNote: The dependent variables are the compliance index components. Robust errors are in brackets. One, two, and three asterisks denote statistical significance at the 10, 5, and 1 percent level, respectively.

List of factors underlying country compliance with components of the AML/CFT standard (2004–2008)

The Legal Measures:

  • The analysis shows that the legal measures are not harmonized worldwide. In some countries, the predicate offenses does not fully comply with the international standards, and there are only a limited number of predicate crimes48 for ML. Less than 3.45 percent of the countries in the sample are compliant with R.1.While the upper-middle and high-income countries have criminalized ML, low-income countries do not fully comply with the standards, and they are still in the process of passing legislation. Criminalization of ML is not fully consistent with the Vienna and Palermo Conventions. Some countries, especially in low- and low-middle-income groups, still have legislation focused solely on drug-related ML. High-income countries have developed sound legal frameworks; however, one area that remains problematic is the criminalization of insider trading and market manipulation49. Countries still need to pass legislation considering them to be distinct offenses. In addition, other predicate offenses such as corruption still remain a widespread problem for compliance with legal measures. Also, only 6.9 percent of the countries have criminalized FT according to R.3 requirements. Furthermore, in some countries, the ML offense does not apply to self- launderers and/or the ML/FT offenses do not apply to legal persons.
  • The lack of ML prosecutions, in some countries, indicates that the international standard has not been effectively implemented, there is a tendency to stop prosecutions at the predicate offenses without pursuing it to identify any money launder offenses.
  • In some countries the enforcement of AML/CFT legal measures is inadequate, weak, and selective. The analysis shows few convictions in 116 countries and a low rate of confiscation, mainly due to the fact that confiscation regime is not clear and effective enough. Only 11.21 percent of the sample is compliant with the R.3. The freezing strategy has perhaps not been successful due to the difficulty in finding the assets hidden by the suspected money laundering. Finally, in the majority of countries, no sanctions regime exists for ML offenses committed by natural persons acting as a front or on behalf of a trustee.

Figure 4.1 reveals that the average in compliance with legal measures is very low in low middle-income countries, and that the mean of compliance in high-income and upper middle-income countries is very similar. The maximum ratings in compliance are found in high-income countries; this is normal because they have designed and developed the standards that better fit into formal economies.

Figure 4.2 shows that low-income countries are still below 20 percent of compliance in percent of the theoretical value; this means that in some of these countries the essential legal measures that a country needs to protect itself from money laundering are far from met. In the rest of the income groups, the degree of compliance is 40 to 60 percent. In the case of high-income countries, the average shows lower than the real because a few countries in the high- income group have less strong legal frameworks, thus reducing the compliance of the group. In the future we should consider weighting countries according to their relevance.

The standard deviation in legal measures by income groups is the following, the high-income countries shows the higher standard deviation (1.02) followed by low income (0.93), upper middle income (0.90) and low middle income (0.83). The standard deviation for all the countries in the sample is 1.18 for legal measures.

Figure 4.3 depicts that Western countries are almost fully compliant followed by countries within Europe and Asia group (ECA), Latin American and Caribbean, and Middle Eastern countries. Sub-Saharan, South Asian and East Asian countries have made progress in implementing the international standards; some of them are still partially- or noncompliant with the legal measures. Some of these countries have weak governance, and the international community should support them in strengthening their regulatory frameworks, avoiding the spillovers that their weak regulatory status could create in other countries.

The Institutional Measures

  • Lack of adequate resources (human, technological, and financial) hampers the ability of some countries to establish and maintain FIUs and competent supervisory authorities to conduct oversight of AML/CFT matters. In many countries, the lack of these institutional arrangements remains a concern. In fact, some of the countries in the sample have not yet established FIUs in accordance with the standards (19.83 percent), and in others supervision of AML/CFT compliance has not been delegated or assigned to a competent authority. The lack of both institutional structures highlights major shortcomings in the AML/CFT regime.
  • Lack of coordination between competent authorities (regulator, FIU, law enforcement, and prosecutor). In some countries, competent authorities with responsibility for AML/CFT are not coordinating effectively to facilitate ML/FT information analyzed by an FIU to form the basis for an investigation by law enforcement, with views to successful prosecution of offenses.
  • Lack of adequate measures by competent authorities to inform financial institutions and DNFBPs of ML/TF trends, typologies, and other developing ML/FT issues. For example, in the area of analyzing suspicious transaction reports (STR)50, the competent authorities fail to provide adequate feedback to financial institutions and DNFBPs on the results of the STRs analyzed. In addition, in some cases there are legal barriers when two or more jurisdictions are involved in the same case and when the gathering of information in one country is limited due to data privacy and financial secrecy laws in place. Limitations like these preclude some institutions from disclosing data in their possession, e.g., SWIFT information. In the area of ML/FT investigations and prosecutions, even though legal provisions and law enforcement powers are in place, law enforcement agencies face the challenge of compiling evidence around cases of ML/FT. Also, more outreach and guidance to those DNFBPs with reporting obligations is required to explain these reporting obligations.
  • FIUs’ on-site supervision activities do not cover the full range of tools available. The number of formal compliance inspection audits has been very low across the range of supervised entities. The assessment method does not sufficiently take into account AML/CFT risks, therefore there are some concerns about the adequacy of supervision for small firms.

Figure 5.1 shows that the average of countries’ compliance with the institutional measures is higher than countries’ compliance with the legal measures. Although in low- to low-middle income countries the compliance with the institutional measures remains relatively low. The upper middle- and high-income countries have devoted more resources to ensure that AML/CFT compliance is supervised. Figure 5.2 reveals that only high-income countries are largely compliant with the standards.

The standard deviation in institutional measures by income groups is the following, the low middle-income countries shows the higher standard deviation (1.30) followed by upper middle income (0.99), high income (0.96), and low income (0.83). The standard deviation for all the countries in the sample is 1.45 for institutional measures.

Figure 5.3 depicts that Western countries are compliant with institutional measures, followed by Europe and Asia region group, Latin American, Caribbean, and Middle Eastern countries. Although sub-Saharan, South Asian, and East Asian countries having made progress in providing resources for supervising the AML/CFT regime, some of them are still partially- or noncompliant with the institutional measures. Some of these countries have weak governance, and the international community should support their efforts to improve their supervisory structures in order to avoid the spillovers that their weak supervision status could create in other countries.

Preventive Financial Sector Measures

  • Some countries have weak customer identification policies for preventing access by money launderers and terrorism financiers to financial systems through financial institutions. Over 0 percent of the countries in the sample are compliant with the R.5. (See Table 6). Many countries still had no customer due diligence (CDD) measures at all. Although some of the assessed upper-middle and high-income countries have adopted preventive measures, the overall compliance regarding basic preventive measures is extremely low in all income groups. A low level of compliance also makes it very difficult to reduce the quantum of money being laundered globally and its potential impact on the world economy.51
  • Although many countries ensure that financial institution secrecy laws do not inhibit implementation of the FATF recommendations (52.59 percent of countries are compliant), in some countries, it has not been clearly shown that bank secrecy has been fully lifted by the AML domestic law. In some countries, it is still necessary to request that the judicial authority ‘relieve’ the rules of confidentiality, and this can compromise the system’s efficacy. In some other countries, financial institutions are not authorized to share information in the implementation of correspondent banking, third parties, and introducers.
  • Customer’s due diligence measures show moderate improvement when establishing business relations. The results show an improving trend in identifying and verifying the identity of the customers when establishing business relations, carrying out occasional transactions, and when there is a suspicion of ML or FT and the financial institution has doubts about the veracity or adequacy of previously obtained customer identification.
  • Some countries face weaknesses in identifying politically exposed persons (PEPs) or the issues generally involved. Only 0.86 percent of the countries are compliant with R.6. At the time of assessment, some European countries have low ratings in R.6 because they have been waiting for the third EU directive to come into force. In many countries, the law is in compliance with the international standards but there are no instructions that, for the benefit of financial institutions, clarify the conditions applicable to carrying out due diligence with respect to PEPs for the financial institutions.
  • In many countries, the legislative, regulatory, or other enforceable requirement with respect to correspondent banking relationships is not sufficient. Only 6.9 percent of the countries are compliant with the standards. There is no requirement to ascertain that the respondent banking AML/CFT controls are adequate and effective regarding payable through accounts, or regarding the obligation to identify/verify the customer and perform ongoing due diligence.
  • Financial institutions measures to prevent the misuse of technological developments in ML/FT money laundering are insufficient, and effective CDD procedures that apply to non-face-to-face customers are limited. Only 34.48 percent of the countries are compliant. For example, measures to deter ML/FT threats arising from new technologies must be put in place and regulations for insurance and capital markets licensees on non-face-to-face account opening must be developed.
  • The requirements to obtain identification data from third parties and introducers need to be improved. Only 38.76 percent of the sample is compliant with R.9. Many countries do not take adequate steps to confirm that copies of identification data and other relevant documentation relating to CDD requirements will be made available from the third party upon request without delay; or to confirm that the third party is regulated and supervised according to the standards.
  • The transaction records are limited to nonfinancial institutions. The cash dealers, securities and insurance entities, foreign exchange dealers, and money remitters are not often reporting. The provisions for record keeping do not specifically require that all account files and business correspondence be retained. Only 18.97 percent of the countries in the sample are compliant with R.10.
  • Some countries lack explicit prohibition on the establishment of shell banks. In many countries, there is no provision that prohibits some domestic banks from entering or requiring operations with shell banks. In addition, there are no requirements for financial institutions to ensure that their respondent banks do not have relationships with shell banks. Only 21.55 percent of the countries are compliant with R.18.
  • The financial institutions reports on large cash transactions are not sufficient. Only 5.17 percent of the countries are compliant with R.11.
  • There is no clear legal requirement to report funds suspected to be linked or related to financing of terrorism. In general, more guidance and outreach are required to ensure that all financial institutions are reporting suspicious transactions in some countries. Sometimes the obligation to report suspicious reports related to FT does not extend to investment fund and credit card companies. At present, the vast majority of STRs have been filed by a small number of financial institutions.
  • Administrative sanctions system does not clearly cover the overall AML/CFT standard in most countries. Only 1.72 percent of the sample is compliant with R.17. There are also limitations on the ability of the authorities to apply the sanctions or requirements under AML law. There is a lack of administrative sanctions, which means that formal sanctions are generally not applied. In countries where sanctions are available for legal persons that do not fulfil the AML obligations, it is too early to assess their effectiveness. Insufficient sanctions are available for senior staff in institutions where violations occur.
  • There is not effectively control of the recording of wire transfers and the detection of couriers in some countries. Only 3.45 percent of the countries are compliant with the wire transfer rules (SR.VII), and only 6.49 percent of the countries are compliant with the requirements for money transfer (SR.VI).

Figure 6.1 shows that the average of countries’ compliance with the financial institutions prevention measures is low in all the income groups. The mean is still very low in low- and low-middle income countries. In addition, figure 6.2 reveals that high-income countries are also only partially compliant with the standards. The standard deviation in financial institutions prevention by income groups is the following, the high-income countries shows the higher standard deviation (3.59) followed by upper middle income (3.41), low middle income (2.95), and low income (2.51). The standard deviation for all the countries in the sample is 3.76 for institutional measures.

Figure 6.3 depicts that Western countries are still partially compliant with financial prevention measures followed by Europe and Asia region group (ECA), Latin-American, Caribbean, and Middle Eastern countries. South and East Asian countries are below partially compliant with financial institutions preventions.

Preventive DNFBPs Measures

  • Oversight over the DNFBPs has been assigned in a number of countries to several types of supervisors, who in many cases lack the required expertise. As it is a relatively new grouping, comprehensive information has been difficult to obtain due to the large and diverse composition of DNFBPs. The counterparts are typically far less familiar with issues than in the financial sector. In addition, the different DNFBPs provide very different types of product and serve customers which results in a varied nature and scale of risks.
  • DNFBPs operating in some countries do not have mandatory CDD, record keeping, or other requirements. The existing requirements are ineffective and the internal control procedures are not always fully in place. For example, weaknesses exist in relation to the duty of sectors such as real estate agents,52 casinos, traders in precious metals, attorneys, notaries and independent legal professionals and accountants, in applying CDD.
  • Most DNFBPs are not legally required to pay special attention to transactions involving certain countries or to report related suspicious transactions to their country FIU. There are no specific requirements for financial institutions to record sufficient information to permit the reconstruction of individual transactions so as to provide, if necessary, evidence for prosecution of criminal activity.
  • Most DNFBPs are not required or motivated to develop internal policies, procedures, internal controls, ongoing employee training, and compliance in respect of AML/CFT. In particular, lawyers are typically resistant to being covered under the FATF Recommendations, which accounts for the legal challenges to the application of AML/CFT prevention controls to the legal professions in some countries. Current compliance levels are generally low, but there is greater complexity once implementation starts.

Figure 7.1 shows that the average of country compliance with the DNFBPs prevention measures is very low in all income groups. None of the countries are totally compliant with R.12 and R.16 and R.24. The average is still very low in low- and low-middle income countries. The standard deviation in DNFBPs prevention by income groups is the following, the high-income countries shows the higher standard deviation (0.52) followed by upper middle income (0.41), low middle income (0.35), and low income (0.20). The standard deviation for all the countries in the sample is 0.46 for DNFBPs prevention.

In addition, Figure 7.2 reveals that high-income countries are also less than partially compliant with the standards. Figure 7.3 depicts that Western countries are still below partially compliant with DNFBPs, followed by eastern European, Latin American and Caribbean, and sub- Saharan countries; South Asian and East Asian countries are at the bottom of compliance.

Measures Preventing the Abuse of the Informal Sector

  • Domestic competent authorities encounter difficulties in identifying and classifying the different activities within the informal sector, in particular in cash-based economies. Although these activities may sometimes be covered under the DNFBPs, the lack of definition of the informal sectors continues to undermine the ability of the competent authorities to evaluate the informal sectors’ vulnerability to ML/FT. An important factor related to prevention of ML/FT in the informal sector is the control of cross-border cash movements.
  • The vast majority of the countries have no adequate measures in place to control the physical cross-border transportation of currency and bearer negotiable instruments. There are two main control systems to monitor them, the declarations system and disclosure obligation. The assessment reports show that sometimes when a declaration system is in place for cross-border transportation of currency, there is no mechanism to ascertain origin of the currency and its intended use in relation to ML or terrorist activity. Also, there is no mechanism in place to maintain comprehensive statistics and pass the information on the declaration of cross-border transportation to the FIU.

Figure 8.1 shows that the average of countries’ compliance with the informal sector prevention measures is low in all the income groups. The mean is still low in low and low middle income countries. The standard deviation in informal sectors prevention by income groups is the following, low middle -income countries shows the higher standard deviation (0.50) followed by high income (0.49), upper middle income (0.45), and low income (0.44).

The standard deviation for all the countries in the sample is 0.53 for informal sector prevention. In addition, Figure 8.2 reveals that high-income countries are almost compliant with the standards. Western countries are below partially compliant with DNFBPs, followed by eastern European countries. The Latin American and Caribbean, and East Asian countries are at the bottom of compliance (figure 8.3).

Entity Transparency Measures

  • In many countries the prevention of ML/FT is hampered by difficulties in identifying or lack of commitment to identify the ultimate beneficial owners of funds/assets, which is illustrated by the lack of standardized data on beneficial ownership held in most countries, and the nature of information collected will vary in the absence of any relevant guidance. For example, information on the companies’ register typically pertains only to founders and composition of the board of directors (as opposed to beneficial ownership), which is neither verified nor reliable. In addition, in some countries, providers of trust services who are not lawyers or accountants but members of professional bodies are not monitored for their AML/CFT obligations; it is therefore not clear how reliable the information they maintain would be.
  • In addition, in many countries the prevention of ML is impeded by inadequate laws and regulations, which fail to require the recording of adequate information that would allow the identification and verification of the identity of the beneficial owner of a public or private company, especially when a legal entity is a shareholder or director. Despite the fact that in some countries the use of bearer share certificates is reportedly rare, there are no specific measures to ensure that they are not misused for money laundering. In fact, in countries that permit the issuance of bearer shares, we found it was almost impossible to identify the beneficial owner. As a result, these deficiencies create a domino effect, weakening the effectiveness of other laws and regulations linked to AML/CFT international standards, such as the criminal, administrative, and banking laws. For example, if we do not know who the real beneficial owner of company is, it is nearly impossible to mount a successful prosecution.
  • Mechanisms to provide adequate and timelier access to adequate and accurate information on beneficial ownership and control of legal persons could be improved. While competent authorities have some powers to access information on the beneficial owner and control of some types of legal persons and arrangements, the mechanisms in place appear to be insufficient.

Figure 9.1 shows that the average of countries compliance with the entity transparency measures is low in all the income groups. The mean of compliance is still low in low- and low-middle income countries. In addition, Figure 9.2 reveals that high-income countries are at the same level of compliance with the standards than the rest of income groups. The standard deviation in entity transparency by income groups is the following, low middle-income countries shows the higher standard deviation (0.66) followed by upper middle income (0.61), low income (0.59), and high income (0.58). The standard deviation for all the countries in the sample is 0.61 for entity transparency. Figure 9.3 depicts that Middle Eastern countries and South Asian countries are more compliant with Entity Transparency than Western and the Europe and Asia region group (ECA). The Latin American and Caribbean, and east Asian countries are at the bottom of compliance with entity transparency.

International Cooperation Measures

  • The authorities’ ability to cooperate is limited by the absence of clear rules, as illustrated by the failure of some countries have failed to enhance mutual legal assistance, information sharing, and cooperation both domestically and abroad. In general, low- and upper-middle-income countries have only limited legal frameworks for international cooperation. Some countries lack official gateways or mechanisms specifying the information that can be requested and establish controls and safeguards to ensure that the information is used in an authorized manner. For instance, despite the existence of an FIU some countries lack gateways or mechanisms that authorize cooperation and exchanges of information with its foreign counterparts.
  • The lack of clear rules in mutual legal assistance renders international cooperation and sharing of information and domestic level less systematic. Because of a lack of clear rules in mutual legal assistance, prosecutors in some cases of international financial fraud cannot get information from certain institutions. In addition, concerns remain regarding the ability of some domestic authorities to handle mutual legal assistance requests in a timely and effective manner, even for routine requests. Some countries refuse MLA requests where dual criminality requirements are not met. There are statistics for extradition requests for only high-income countries, and it is difficult to assess whether the legislation has been fully implemented. Additionally, some countries have no measures or procedures that will allow extradition requests and proceedings for ML to be handled without undue delay.
  • Some countries have limited mechanisms for international cooperation on FT. To enhance international cooperation, these countries need to allow other countries — on the basis of a treaty, arrangement, or other mechanism— mutual legal assistance and information exchange, as well as ensure that they do not provide safe havens for individuals involved with FT, terrorist acts, or terrorist organizations. A number of countries should have procedures in place to extradite such individuals wherever possible. In some countries, there needs to be introduced an MLA Order that contains all of the necessary elements with respect to AML/CFT. International cooperation with a foreign counterpart is sometimes limited and given on an ad hoc basis. Also, there is limited regulatory cooperation with overseas regulators of financial institutions.

Figure 10.1 shows that the average in countries’ compliance with the international cooperation measures is higher in high- and upper-middle income groups. The mean of compliance is still low in low-income countries. The standard deviation in international cooperation by income groups is the following, high-income countries shows the higher standard deviation (1.29) followed by low income (1.18), low middle income (1.17), and upper middle-income (1.11). The standard deviation for all the countries in the sample is 1.57 for informal sector prevention. In addition, Figure 10.2 reveals that high-income countries are also almost compliant with the standards. Figure 10.3 depicts that the countries in East Asia have achieved the lower compliance with the international cooperation measures.

1I thank Joseph Mark Myers, Nadim Kyriakos-Saad, Paul Ashin, Emmanuel Mathias, Gianluca Esposito, Nicoletta Batini, Manuela Goretti, Maria Angeles Oliva, and an anonymous referee for their helpful comments, and Erik Lobato and Amy Kuhn for research assistance. All remaining errors are my own.
2For the sake of brevity, in this study the term “countries” is used to designate any territorial entity that is a country or a jurisdiction.
3A list of advanced and developing countries used in this research are provided in Annex 1.
4The FATF is undertaking a process of review of the standard and the methodology. This process is ongoing; as the paper is being finalized we need to wait for outcome to see at what extent it will address the shortcomings pointed out in this work.
5The paper examines compliance issues from 2004–2011. However, the paper explores the effects of domestic factors on compliance from 2004–2008.
6The period for the third round of mutual reports evaluation started in 2004. The round is not still finished for some FATF associated members and FATF regional bodies.
7IMF and World Bank, Anti-Money Laundering and Combating the Financing of Terrorism: Observations from the Work Program and Implications Going Forward, Supplementary Information, August 31, 2005, pp. 5–11. The IMF focused its analysis on the results of the assessments by 18 countries on compliance with sAML/CFT standard using the 2004 methodology, later comparing results obtained in these countries in 2001 and 2004. The report shows that overall compliance with FATF Recommendations in the revised standard is lower across all the assessed countries compared to the earlier 1996 standard. Compliance with the CFT special recommendations is particularly weak. Compliance with main AML/CFT preventive measures has become more difficult. Countries are just beginning to address AML/CFT obligations for designated non-financial businesses and professions (DNFBPs) and non-profit organizations (NPOs) See also, Howell (2007) and Johnston (2008), for literature review, the later also reports low level of compliance during the third round of evaluations.
8Prior to 2005, countries were assessed by a previous methodology which related 27 of the 40 Recommendations, and seven of the (then) 8 Special Recommendations.
9To link domestic and international regimes more closely, we turn to Putnam (1988), who has suggested that episodes of international cooperation must be viewed as “two-level games.”
10Compliance could be defined as the actual behavior of a given subject conforming to prescribed behavior, and noncompliance or violation, occurs when actual behavior departs significantly from prescribed behavior (Young 1979). While compliance may be necessary for effectiveness, there is no reason to consider it sufficient (Simmons 1998). An effective regime presupposes the compliance achieved (Young 1980).
11Busch 2002; Bissessar 2002; Bleiklie 2001; Coleman et al.,1998; De Bandt et al., 2000; Eyre et al., 2000; K. Harrison 2002; Howlett 1994; Lutz 2004, as cited in Heichel et al., 2005
13Some studies emphasize that we can only have indirect evidence of norms just as we can only have indirect evidence of most other motivations for political action interests or threats (Finnemore et al., 1998). Culture indicates the political will that lends “legitimacy to some social interest more than others” (Lenschow et al., 2005).
15Other elements are defined in the 2004 Methodology.
16For the purposes of this paper, we avoid country names by referring to country characteristics or groupings. The full analytical and statistical exercise will be repeated in 2013 and at four-yearly intervals thereafter in order to update and refresh data and results and review methods.
17See guidance on the essential criteria in 2004 Methodology.
18This reflects the lag in countries’ compliance between the introduction of more demanding standards from 2003/2004 and countries’ eventual implementation of these.
19For the period 2004–2011, staff used the original compliance rating data, where the measure of compliance was defined as C, ‘Compliant,’ LC, ‘Largely Compliant,’ PC, ‘Partially Compliant,’ NC, ‘Non- Compliant,’ and NA, ‘not applicable.’ In order to provide a quantitative measure of AML/CFT, staff replaced existing ratings with the following numbers: C-‘1’, LC-‘0.66’, PC-‘0.33’ and NC-‘0’, NA-‘1.
20161 assessments multiplied by 49 Recommendations.
21Not Available occurs 1.59 percent of the time.
22Note that the degree of compliance on the overall AML/CFT for all the countries for the period 2004–2011 (as depicted in figure 1 in Annex 1) is similar to the period 2004–2008 (as depicted in figure 1 in Annex 2).
23The AML Recommendations were revised substantially in 1996 and, again, in 2003. The Special Recommendations on CFT were originally eight until a ninth Recommendation was adopted in October 2004.
24For any given recommendation or grouping of recommendations, the degree of compliance is measured as a share of the real and theoretical maximum ratings.
25Countries should criminalize money laundering on the basis of the United Nations Convention against illicit traffic in Narcotic Drugs and Psychotropic Substances, 1988 (The Vienna Convention) and the United Nations Convention against Transnational Organized Crime, 2000 (the Palermo Convention). The basis for criminalizing terrorist financing should be the United Nations International Convention for the Suppression of the Financing of Terrorism, 1999.
26At present, the non-cooperative countries and jurisdictions list is reviewed by the International Review Cooperation Group within FATF.
27As a result of the 3rd EU Directive on AML/CFT (200/60/EC) that was adopted 26 October 2005, to be transposed by 15 December 2007, replaces 1991 directive, as amended in 2001. It reflects updated FATF Recommendations in 2003.
28We selected the mean for the standardization. However, we also studied the median of each grouping. The median and the mean are very close in all groupings. We finally decided to select the mean as is standard in this kind of work. For example, see WEO April (2009) Chapter 4 “How Linkages Fuel the Fire: The Transmission of Financial Stress from Advanced to Emerging Economies.” It employs an index created for advanced economies in the October 2008 World Economic Outlook using the same methodology of demeaned and standarization.
29The Principal Component Analysis (PCA) is a statistical method to reduce multidimensional data sets to lower dimensions in order to find patterns. The PCA summarizes a p-dimensional dataset into a smaller number, q, of dimensions while preserving the variation in the data on the maximum extent possible. The q new dimensions are constructed such that (i) they are linear combinations of the original variables; (ii) they are independent of each other; and (iii) each dimension captures a successively smaller amount of the total variation in the data. The p original variables are combined into q linear combinations, which form the new principal components of the system. A standardized lineal combination Zi of the data vector, Xi=(X, X…,X ,) of length p is defined as Z= wi xi; where the sum of the squares of the weights, W, is equal to 1. PCA chooses the weights by determining the linear combinations of all p variables in the transformed dataset that maximizes the variance of the data. Each principal component provides a set of factors loadings of the indicators, which correspond to their importance for the component.
30Due to data limitations, only 88 countries have all variables needed for the analysis.
31To our knowledge, this is the first paper that tries to estimate econometrically the relationship between AML/CFT compliance and cultural, institutional, and economic factors in a multivariate regression. In this paper, we use OLS regressions since we treat the dependent as a continuous variable. In future work, other methodologies will be contemplated.
32Grossman and Helman (1991) and Barro, Sala-i-Marti (1995), and Edwards (1997) among others, have argued that countries that are more open have a greater ability to benefit from technology diffusion and its boosting effect on productivity growth. FDI stimulates economic growth by improving technology and productivity (Borensztein et al.,1998). Recent empirical studies highlight the importance of good institutions to promote productivity and long-term growth (Acemoglu et al., 2004).
33Beck Demirgurc-Kunt and Levine (2000) have suggested two indicators to measure banking efficiency. These are the overhead cost and net interest margin. Other studies show that there appears to be a negative relationship between net interest margin and the index of overall BCP compliance (Podpiera, 2004).
34The entry of foreign banks has been found to have generally favourable competitive effects on the development and efficiency of domestic, host banking systems. See Bayraktar and others (2006). Foreign banks have also been found to stimulate improvements in the quality of local regulation and supervision (Levine, 1996)
35Compliance with the AML/CFT International Standards depends on countries’ income level in this sample. Introduced alone in the basic regression, GDP per capita is positive and statistically significant in both the PCA and the AML/CFT Compliance Index (Table 2, column 1 for the AML/CFT compliance Index). Figure 3.1 shows the positive relationship between AML/CFT fitted values and the log GDP. This means that countries with higher income are more likely to be compliant.
36When controlled for GDP per capita.
37Net interest margin can be interpreted as a measure of the efficiency of banking sector performance, because it indicates the cost of banking intermediation that needs to be paid by banks’customers. Large net interest margins often indicate inefficient banking operations, high risks in lending, and monopoly power of banks; thus, lower margins would be preferable. The margin captures the accounting value of the bank’s net interest revenue as a share of its interest-bearing (total earning) assets.
38UNODC’s index of contribution to the global drug problem is a proxy for proceeds of crime related to drugs only. However, this proxy does not account for other crimes and the financing of terrorism as well as the international dimension of ML/TF.
40The 2004 methodology is a common instrument elaborated by the FATF, the IMF, the World Bank and other assessor bodies to guide the assessment of a jurisdiction’s compliance with the AML/CFT standard.
41Some governments are more prone to make agreements that comport with the kinds of activities they were willing to engage in anyway, and from which they foresee little incentive to defect. See, Simmons 1998; Fisher 1982, Coplin 1968, and Schwartzenberger 1945, for literature review.To overcome the caveats created by the selection bias in studying compliance, in this study we propose a way to address the endogeneity and bias of self-selection. One such way is to view mutual evaluation assessments as a tool for evaluating the compliance process, and for determining how states and private actors respond in the long negotiation process of implementing AML/CFT standard. We take this constructivist approach to measure the compliance of 116 countries with the AML/CFT standard by using the mutual evaluation report (MER) that a country requests to evaluate its compliance.
42More detailed and elaborated policy and recommendations are contained in the staff paper on Anti-Money Laundering and Combating the Financing of Terrorism (AML/CFT)—Report on the Review of the Effectiveness of the Program, June 2011.
43Financial institutions means any person or entity who conducts as a business one or more of the following activities or operations for or on behalf of a customer such as: acceptance of deposits and other repayable funds from the public; lending, financial leasing; the transfer of money or value; issuing and managing means of payment (e.g. credit and debit cards, checks, traveller’s checks, money orders and bankers’ drafts, electronic money); financial guarantees and commitment; trading in: (a) money market instruments (checks, bills, CDs, derivatives, etc.), (b) foreign exchange, (c) exchange, interest rate, and index instruments, (d) transferable securities, (e) commodity futures trading: participation in securities issues and the provision of financial services related to such issues; individual and collective portfolio management; safekeeping and administration of cash or liquid securities on behalf of other persons; otherwise investing, administering, or managing funds or money on behalf of other persons underwriting and placement of life insurance and other investment related insurance; money an0d currency changing. When a financial activity is carried out by a person or entity on an occasional or very limited basis (having regard to quantitative and absolute criteria) such that there is little risk of money laundering activity occurring, a country may decide that the application of anti-money laundering measures is not necessary, either fully or partially. In strictly limited and justified circumstances, and based on a proven low risk of money laundering, a country may decide not to apply some or all of the Recommendations to some of the financial activities stated above.
44Designated non-financial businesses and professions (DNFBPs) means: (a) casinos (which also includes internet casinos); (b) real estate agents; (c) dealers in precious stones; (e) lawyers, notaries, other independent legal professionals and accountants (this refers to sole practitioners, partners or employed professionals within professional firms); (f) trust and company service providers (persons or businesses that are not covered elsewhere under the Recommendations, and which, as a business, provide any of the following services to third parties: acting as a formation agent of legal persons; acting as (or arranging for another person to act as) a director or secretary of a company, a partner of a partnership, or a similar position in relation to other legal persons; providing a registered office, business address or accommodation, correspondence, or administrative address for a company; a partnership or any other legal person or arrangement; acting as (or arranging for another person to act as) a trustee of an express trust; acting as (or arranging for another person to act as) a nominee share holder for another person.)
45Note that this annex was developed at the end of 2009. Updates on the level and degree of compliance are provided in Annex 1.
46Financial institutions means any person or entity who conducts as a business one or more of the following activities or operations for or on behalf of a customer such as: acceptance of deposits and other repayable funds from the public; lending, financial leasing; the transfer of money or value; issuing and managing means of payment (e.g. credit and debit cards, checks, traveller’s checks, money orders and bankers’ drafts, electronic money); financial guarantees and commitment; trading in: (a) money market instruments (checks, bills, CDs, derivatives, etc.), (b) foreign exchange, (c) exchange, interest rate, and index instruments, (d) transferable securities, (e) commodity futures trading: participation in securities issues and the provision of financial services related to such issues; individual and collective portfolio management; safekeeping and administration of cash or liquid securities on behalf of other persons; otherwise investing, administering, or managing funds or money on behalf of other persons underwriting and placement of life insurance and other investment related insurance; money and currency changing. When a financial activity is carried out by a person or entity on an occasional or very limited basis (having regard to quantitative and absolute criteria) such that there is little risk of money laundering activity occurring, a country may decide that the application of anti-money laundering measures is not necessary, either fully or partially. In strictly limited and justified circumstances, and based on a proven low risk of money laundering, a country may decide not to apply some or all of the Recommendations to some of the financial activities stated above.
47Designated non-financial businesses and professions (DNFBPs) means: (a) casinos (which also includes internet casinos); (b) real estate agents; (c) dealers in precious stones; (e) lawyers, notaries, other independent legal professionals and accountants (this refers to sole practitioners, partners or employed professionals within professional firms); (f) trust and company service providers (persons or businesses that are not covered elsewhere under the Recommendations, and which, as a business, provide any of the following services to third parties: acting as a formation agent of legal persons; acting as (or arranging for another person to act as) a director or secretary of a company, a partner of a partnership, or a similar position in relation to other legal persons; providing a registered office, business address or accommodation, correspondence, or administrative address for a company; a partnership or any other legal person or arrangement; acting as (or arranging for another person to act as) a trustee of an express trust; acting as (or arranging for another person to act as) a nominee share holder for another person.).
48Designated categories of offenses means: participation in an organized criminal group and racketeering; terrorism, including terrorist financing, trafficking in human beings and migrant smuggling; sexual exploitation, including sexual exploitation of children; illicit trafficking in narcotic drugs and psychotropic substances; illicit arms trafficking; illicit trafficking in stolen and other goods; corruption and bribery; fraud; counterfeiting currency; counterfeiting and piracy of products; environmental crime; murder, grievous bodily injury; kidnapping, illegal restraint and hostage-taking; robbery or theft; smuggling; extortion; forgery; piracy; insider trading, and market manipulation.
49The FATF conducted a global study in June 2008 in order to better understand the ML/FT vulnerabilities in the security industry. The comprehensive results are now available as Money Laundering and Terrorist Financing in the security sector. See FATF (2009) in references.
50Suspicious Transaction Report (STR) is commonly used throughout the world. Some countries use the term Suspicious Activity Report (SAR), denoting the same.
51The 3rd European Directive has hugely influenced either the implementation of preventive recommendations in those countries belonging to the EU or those countries belonging to the EU or those countries involved in economic relationships with the EU (e.g., countries in Central Asia and North Africa).
52FATF has produced many reports making reference to the fact the real-estate sector may be one of the main vehicles used by criminal organizations to launder their illicitly obtained money. See FATF (2007) in References.

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