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Middle East and Central Asia > Qatar

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Cover Staff Discussion Notes
Broadening the Gains from Generative AI: The Role of Fiscal Policies
Fernanda Brollo
,
Era Dabla-Norris
,
Ruud de Mooij
,
Daniel Garcia-Macia
,
Tibor Hanappi
,
Li Liu
, and
Anh D. M. Nguyen
Generative artificial intelligence (gen AI) holds immense potential to boost productivity growth and advance public service delivery, but it also raises profound concerns about massive labor disruptions and rising inequality. This note discusses how fiscal policies can be employed to steer the technology and its deployment in ways that serve humanity best while cushioning the negative labor market and distributional effects to broaden the gains. Given the vast uncertainty about the nature, impact, and speed of developments in gen AI, governments should take an agile approach that prepares them for both business as usual and highly disruptive scenarios.
Keywords:
Artificial intelligence; AI; technological change; labor market; fiscal policy; social protection systems; tax systems; IMF Staff Discussion Note SDN2024/002; gen AI; advance public service delivery; role of fiscal policies; replacement ratio; job displacement; income support; tax treatment; market power; Labor markets; Corporate income tax; Automation; Capital income; Global
Cover Technical Notes and Manuals
Налоговое администрирование: основные возможности аналитики для управления комплаенс-рисками
Joshua Aslett
,
Gustavo González
,
Stuart Hamilton
, and
Miguel Pecho
В этой технической справке представлена аналитика для управления комплаенс-рисками в рамках налогового администрирования. Вместе с сопровождающим ее набором инструментов эта справка предназначена для использования в качестве стартового набора для содействия развитию потенциала в области комплаенс-планирования , оценки рисков и работы групп по сбору аналитических данных. В этой справке, разработанной в первую очередь для начинающих аналитиков, которые только приступают к работе в области налогового администрирования, представлены как теоретические, так и практические аспекты аналитики. Его инструментарий состоит из первоначального набора аналитических форм, призванных помочь реализовать представленную здесь теорию на практике в таких областях, как: 1) комплаенс-планирование; 2) составление профиля налогоплательщика; и 3) отбор кандидатов для проведения проверок.
Keywords:
налоговое администрирование; управление комплаенс-рисками; комплаенс-стратегия; анализ рисков; аналитические данные; данные; аналитика; цифровизация; информационные технологии
Cover Staff Climate Notes
Key Challenges Faced by Fossil Fuel Exporters during the Energy Transition
Diego Mesa Puyo
,
Augustus J Panton
,
Tarun Sridhar
,
Martin Stuermer
,
Christoph Ungerer
, and
Alice Tianbo Zhang
The global energy transition is affecting fossil fuel exporters from multiple angles. It is adding to longstanding uncertainties on relative movements of fossil fuel demand and supply—which impact fossil fuel-related exports, fiscal flows, investment and subsequently external and fiscal accounts, economic growth, and employment. While policymakers are very familiar with these challenges, they now also face expectations of a permanent decline in the long-run global demand for fossil fuels. Key factors that could determine country-level impacts include (i) the type of fossil fuel a country exports (ii) extraction costs and (iii) country characteristics. The monitoring and mitigation of fiscal risks will need to be stepped up. Fiscal policy also has a role in reducing domestic emissions, encouraging adoption of low-carbon technologies, and helping those most vulnerable to changes from the transition. Broader macroeconomic risks can be reduced by accelerating ongoing structural reforms that support alternative engines of growth. Low- or zero-carbon emission energy industries could offer new avenues that build on existing fossil fuel knowledge and infrastructure. Concurrently, improved financial regulation and supervision could reduce financial sector exposures. Finally, international coordination on the design and implementation of climate policy as well as international transfer schemes (financing and capacity development) could reduce uncertainties surrounding the transition path and associated adverse economic consequences.
Keywords:
Macroeconomic policy; climate change; energy transition; fossil fuel exporters; commodity market; climate mitigation; economic diversification; international coordination; IMF staff Climate note; IMF staff Climate Note 2024/001; fossil fuel exporter; building financial asset buffer; cost exporter; Non-renewable resources; Exports; Oil; Renewable energy; Global
Cover Technical Notes and Manuals
Tax Administration: Essential Analytics for Compliance Risk Management
Joshua Aslett
,
Gustavo González
,
Stuart Hamilton
, and
Miguel Pecho
This technical note introduces analytics for compliance risk management in tax administration. Together with its accompanying toolkit, the note is intended as a starter kit to support capacity development in compliance planning, risk, and intelligence groups. Developed primarily for emerging analysts new to tax administration, the note presents both theory and practical aspects of analytics. Its toolkit is comprised of an initial collection of analytics templates designed to assist in turning the theory presented into practice in the areas of: (1) compliance planning; (2) taxpayer profiling; and (3) audit case selection.
Keywords:
tax administration; compliance risk management; compliance strategy; risk analysis; intelligence; data; analytics; digitalization; information technology; analytics support compliance risk management; support CRM analytics capability; CRM theory; IMF Library; data quality; Tax administration core functions; Machine learning; Value-added tax
Cover Staff Discussion Notes
Gen-AI: Artificial Intelligence and the Future of Work
Mauro Cazzaniga
,
Florence Jaumotte
,
Longji Li
,
Giovanni Melina
,
Augustus J Panton
,
Carlo Pizzinelli
,
Emma J Rockall
, and
Marina Mendes Tavares
Artificial Intelligence (AI) has the potential to reshape the global economy, especially in the realm of labor markets. Advanced economies will experience the benefits and pitfalls of AI sooner than emerging market and developing economies, largely due to their employment structure focused on cognitive-intensive roles. There are some consistent patterns concerning AI exposure, with women and college-educated individuals more exposed but also better poised to reap AI benefits, and older workers potentially less able to adapt to the new technology. Labor income inequality may increase if the complementarity between AI and high-income workers is strong, while capital returns will increase wealth inequality. However, if productivity gains are sufficiently large, income levels could surge for most workers. In this evolving landscape, advanced economies and more developed emerging markets need to focus on upgrading regulatory frameworks and supporting labor reallocation, while safeguarding those adversely affected. Emerging market and developing economies should prioritize developing digital infrastructure and digital skills
Keywords:
Artificial Intelligence; Labor Market; Job Displacement; Income Inequality; Advanced Economies; Emerging Market Economies; Low-Income Developing Countries; AI preparedness index; AI benefit; AI exposure; ICT employment share; AI adoption; Emerging and frontier financial markets; Income; Global; Africa
Cover FinTech Notes
Generative Artificial Intelligence in Finance: Risk Considerations
Mr. Ghiath Shabsigh
and
El Bachir Boukherouaa
In recent years, technological advances and competitive pressures have fueled rapid adoption of artificial intelligence (AI) in the financial sector, and this adoption is set to accelerate with the recent emergence of generative AI (GenAI). GenAI is a significant leap forward in AI technology that enhances its utility for financial institutions that have been quick at adapting it to a broad range of applications. However, there are risks inherent in the AI technology and its application in the financial sector, including embedded bias, privacy concerns, outcome opaqueness, performance robustness, unique cyberthreats, and the potential for creating new sources and transmission channels of systemic risks. GenAI could aggravate some of these risks and bring about new types or risks as well, including for financial sector stability. This paper provides early insights into GenAI’s inherent risks and their potential impact on the financial sector.
Keywords:
artificial intelligence; embedded bias; cybersecurity; fintech; financial risks; financial sector policy and analysis; financial stability; generative; hallucination; machine learning; privacy; synthetic data; sample generative AI application; AI-machine learning; IMF Library; IMF Fintech Note 2023/006; generative artificial intelligence in finance; Financial sector; Global
Cover FinTech Notes
Keeping Pace with Change: Fintech and the Evolution of Commercial Law
José Garrido
,
Ms. Yan Liu
,
Joseph Sommer
, and
Juan Sebastián Viancha
This note explores the interactions between new technologies with key areas of commercial law and potential legal changes to respond to new developments in technology and businesses. Inspired by the Bali Fintech Agenda, this note argues that country authorities need to closely examine the adequacy of their legal frameworks to accommodate the use of new technologies and implement necessary legal reform so as to reap the benefits of fintech while mitigating risks. Given the cross-border nature of new technologies, international cooperation among all relevant stakeholders is critical. The note is structured as follows: Section II describes the relations between technology, business, and law, Section III discusses the nature and functions of commercial law; Section IV provides a brief overview of developments in fintech; Section V examines the interaction between technology and commercial law; and Section VI concludes with a preliminary agenda for legal reform to accommodate the use of new technologies.
Keywords:
fintech, commercial law, technological innovations, distributed ledger technology, tokens, artificial intelligence, Internet of Things, automated conrtracting, smart contracts, registries, contract law, securities and negotiable instruments, company law, secured transactions, insolvency, digital technology; FINTECH note; B. contract law; evolution of commercial law; publication order; DLT network; Blockchain and DLT; Smart contracts; Technological innovation; Emerging technologies; Securities
Cover FinTech Notes
Blockchain Consensus Mechanisms: A Primer for Supervisors
Parma Bains
Technology plays an increasingly important role in financial services. With the pace of technological inno-vation moving ever faster, the role new technology plays in the provision of financial services is becoming increasingly fundamental. New technology can generate efficiencies for firms, lowering costs that can be passed on to end users. It can increase access to financial services and products for consumers, particularly the most vulnerable; however, new technology can also create new risks and unintended consequences that can harm financial stability, consumer protection, and market integrity. This primer is designed for financial supervisors at central banks, regulatory authorities, and government departments. It adds to existing literature by summarizing key aspects of popular consensus mechanisms at a high level, with a specific focus on how such mechanisms may impact the mandates of supervisors and policymakers when deployed in financial services markets. It could also help inform IMF staff on policy development and technical assistance related to crypto assets, stablecoins, and blockchains.
Keywords:
fintech, blockchain, distributed ledger technology, proof-of-stake, proof-of-work, crypto assets, stablecoins, central bank digital currencies, Bitcoin, BigTech; Blockchain consensus mechanism; bitcoin mining; FINTECH note; A. consensus mechanism; B. consensus mechanism; Blockchain and DLT; Virtual currencies; Technological innovation; Global
Cover Staff Discussion Notes
Toward a Global Approach to Data in the Digital Age
Mr. Vikram Haksar
,
Mr. Yan Carriere-Swallow
,
Emran Islam
,
Andrew Giddings
,
Kathleen Kao
,
Emanuel Kopp
, and
Gabriel Quiros
The ongoing economic and financial digitalization is making individual data a key input and source of value for companies across sectors, from bigtechs and pharmaceuticals to manufacturers and financial services providers. Data on human behavior and choices—our “likes,” purchase patterns, locations, social activities, biometrics, and financing choices—are being generated, collected, stored, and processed at an unprecedented scale.
Keywords:
Data, finance, bigtech, competition, privacy, trade, policy coordination, global principles; data portability; DATA policies country; privacy trade-off; policy divergence; data availability divide; data economy; Digital economy; Competition; Financial sector stability; Artificial intelligence; Global
Cover Technical Notes and Manuals
How to Assess Country Risk: The Vulnerability Exercise Approach Using Machine Learning
International Monetary Fund. Strategy, Policy, & Review Department
The IMF’s Vulnerability Exercise (VE) is a cross-country exercise that identifies country-specific near-term macroeconomic risks. As a key element of the Fund’s broader risk architecture, the VE is a bottom-up, multi-sectoral approach to risk assessments for all IMF member countries. The VE modeling toolkit is regularly updated in response to global economic developments and the latest modeling innovations. The new generation of VE models presented here leverages machine-learning algorithms. The models can better capture interactions between different parts of the economy and non-linear relationships that are not well measured in ”normal times.” The performance of machine-learning-based models is evaluated against more conventional models in a horse-race format. The paper also presents direct, transparent methods for communicating model results.
Keywords:
Risk Assessment; Supervised Machine Learning; Prediction; Sudden Stop; Exchange Market Pressure; Fiscal Crisis; Debt; Financial Crisis; Economic Crisis; Economic Growth; VE modeling toolkit; ML technique; Vulnerability Exercise approach using machine learning; IMF's Vulnerability Exercise; ML tool; crisis risk indices; Early warning systems; Global financial crisis of 2008-2009; Sudden stops; Banking crises; Global