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5. VaR Mapping
- b. Explain how the mapping process captures general and specific risks, and calculate these risks in a portfolio given a set of primitive risk factors
23. Introduction to Credit Risk Modeling and Assessment
- c. Estimate risk-weighted assets and capital adequacy ratio of a financial institution
48. Integrated Risk Management
- b. Explain and differentiate between regulatory capital and economic capital requirements as prescribed in Basel regulations
84. Illiquid Assets
- f. Evaluate the impact of allocating illiquid assets to a portfolio, including the impact on rebalancing and trading and on optimizing the proportion of illiquid assets
88. Portfolio Construction
- a. Describe the inputs to the portfolio construction process and explain challenges faced when using these inputs
89. Portfolio Risk-Analytical Methods
- d. Explain and calculate the risk-minimizing position and position that maximizes the ratio of expected return to risk
4. Backtesting VaR
- c. Evaluate the accuracy of a VaR model based on exceptions or failure rates by using a model verification test
- c. Verify a model based on exceptions or failure rates
6. Validation of Risk Management Models for Financial Institutions
- a. Describe some important considerations for a bank in assessing the conceptual soundness of a VaR model during the validation process
- b. Explain how to conduct sensitivity analysis for a VaR model, and describe the potential benefits and challenges of performing such an analysis
- c. Describe the challenges a financial institution could face when calculating confidence intervals for VaR
- d. Discuss the challenges in benchmarking VaR models and various approaches proposed to overcome them
7. Beyond Exceedance-Based Backtesting of Value-at-Risk Models
- a. Identify the properties of an exceedance-based backtest that indicate a VaR model is accurate, and describe how these properties are reflected in a PIT-based backtest
- b. Explain how to derive probability integral transforms (PITs) in the context of validating a VaR model
- c. Describe how the shape of the distribution of PITs can be used as an indicator of the quality of a VaR model
- d. Describe backtesting using PITs, and compare the various goodness-of-fit tests that can be used to evaluate the distribution of PITs: the Kolmogorov-Smirnov test, the Anderson-Darling test, and the Cramér-von Mises test
11. Regression Hedging and Principal Component Analysis
- g. Explain why and how a regression hedge differs from a hedge based on a reverse regression
13. Expectations, Risk Premium, Convexity, and the Shape of the Term Structure
- d. Identify the components into which the return on a bond can be decomposed, and calculate the expected return on a bond for a risk-averse investor
16. The Vasicek and Gauss Models
- a. Describe the structure of the Gauss+ model and discuss the implications of this structure for the model’s ability to replicate empirically observed interest rate dynamics
- b. Compare and contrast the dynamics, features, and applications of the Vasicek model and the Gauss+ model
- c. Calculate Changes in the short-term, medium-term, and long-term interest rate factors under the Gauss+ model
- d. Explain how the parameters of the Gauss+ model can be estimated from empirical data
81. The US Dollar Shortage in Global Banking and the International Policy Response
- c. Describe the policy response by international central banks to alleviate the US dollar shortage and assess its effectiveness
96. 2023 Bank Failures, Preliminary lessons learnt for resolution
- a. Evaluate the Credit Suisse case and its implications for the international resolution framework
- b. Evaluate the US bank failures of 2023 and their implications for the international resolution framework
- c. Identify and describe the strengths and weaknesses of the resolution framework as demonstrated by Credit Suisse case and the US bank failures of 2023
- d. Describe the uncovered issues for bank resolution that require further studies and development for future improvements on the implementation of the international resolution framework
97. Generative Artificial Intelligence in Finance-Risk Considerations
- a. Compare generative AI and traditional AI/ML algorithms
- b. Explain the challenges generative AI systems pose for the financial sector, including those related to data privacy, embedded bias, model robustness, and explainability
- c. Examine the use of synthetic data to enhance AI models and the potential risks associated with synthetic data generation and application
- d. Evaluate the cybersecurity threats and potential impact on financial stability posed by the use of generative AI in the financial sector
98. Artificial intelligence and the economy-implications for central banks
- a. Identify and describe the risks arising from the widespread use of AI applications in the financial sector
- b. Describe how central banks can harness AI to fulfill their policy objectives
- c. Explain the macroeconomic impact of AI, including implications for firms’ productive capacity and investment, labor productivity, household consumption, economic output, inflation, and fiscal sustainability
- d. Explain how the use of AI presents new opportunities and challenges for central banks, including the central banks’ role as users and providers of data, and the trade-offs posed by their use of both internally-developed and external AI models
99. Interest Rate Risk Management by EME Banks
- a. Describe the mechanisms through which Changes in market interest rates affect a bank’s economic value and the key methods banks use to manage interest rate risk
- b. Compare the methods banks in emerging market economies (EME) and banks in advanced economies have historically used to manage their interest rate risk and how these methods affected their vulnerability to Changes in interest rates
- c. Explain the recent Changes in EME banks’ exposure to interest rate risk and the importance of hedging this risk
100. Laying a robust macro-financial foundation for the future
- a. Explain why the sudden increase in inflation that reached a peak in 2022 following the Covid-19 pandemic did not result in a full-scale global recession
- b. Identify and describe key factors that played a role in the process of disinflation around the world over the past year
- c. Describe policy measures introduced and implemented by different central banks aimed at driving their economies toward meeting inflation targets
- d. Discuss how monetary policy Changes enacted by central banks to reduce inflation impacted equity prices, credit spreads, bond and equity volatilities, and bank lending
- e. Describe monetary, fiscal, prudential, and structural policies that need to be adopted to promote (long-term) sustainable economic growth and low inflation
101. The Rise and Risks of Private Credit
- a. Describe characteristics of private credit, including its typical investors and borrowers, and compare private credit to other types of loans and fixed-income instruments
- b. Explain the return profile and growth profile of the private credit asset class, and compare the historical returns of private credit to those of other asset classes
- c. Describe and assess the risks and vulnerabilities related to private credit, and explain how private credit can pose risks to financial stability
- d. Assess potential policy recommendations that could help mitigate the risks associated with private credit
102. Monetary and fiscal policy-safeguarding stability and trust
- a. Compare and contrast the channels through which fiscal policy and monetary policy influence a country’s economic activity and financial markets, and define the “region of stability” in terms of their joint policy stances
- b. Describe the consequences of breaching the boundaries of the region of stability, and how these consequences have evolved over time in advanced economies and in emerging market economies
- c. Describe the risks that global economies face as a result of high public debt levels, including the potential for these high debt levels, in combination with other factors, to drive tension between fiscal policy and monetary policy
103. Regulating the Crypto Ecosystem-The Case of Unbacked Crypto Assets
- a. Define and describe crypto assets, including the categories broadly used by global financial regulators to classify them
- b. Evaluate the key components within the crypto ecosystem, the potential risks generated by these components, and potential regulatory responses to address those risks
- c. Identify and describe some of the global approaches to the regulation of unbacked crypto assets, including the BCBS’ proposed treatment of banks’ exposures to crypto assets
- d. Examine the considerations and steps introduced by the Bali Fintech Agenda (BFA) for developing a regulatory framework for crypto assets
6. Basel Committee on Banking Supervision
- a. Explain the following lessons on VaR implementation: time horizon over which VaR is estimated, the recognition of time-varying volatility in VaR risk factors, and VaR backtesting
- b. Describe exogenous and endogenous liquidity risk and explain how they might be integrated into VaR models
- c. Compare VaR, expected shortfall, and other relevant risk measures
- d. Compare unified and compartmentalized risk measurement
- e. Compare the results of research on top-down and bottom-up risk aggregation methods
- f. Describe the relationship between leverage, market value of asset, and VaR within an active balance sheet management framework
12. The Evolution of Short Rates and the Shape of the Term Structure
- d. Evaluate the impact of Changes in maturity, yield, and volatility on the convexity of a security
- e. Calculate the price and return of a zero-coupon bond incorporating a risk premium
68. Liquidity and Reserves Management-Strategies and Policies
- d. Summarize the process taken by a US bank to calculate its legal reserves
- e. Differentiate between factors that affect the choice among alternate sources of reserves
79. The US Dollar Shortage in Global Banking and the International Policy Response
- c. Discuss how central bank swap agreements overcame challenges commonly associated with international lenders of last resort
94. Review of the Federal Reserves Supervision and Regulation of Silicon Valley Bank
- a. Describe the events leading up to the failure of Silicon Valley Bank
- b. Describe shortfalls and deficiencies in the Federal Reserve’s supervisory oversight of Silicon Valley Bank during the period that the bank transitioned from the Fed’s Regional Banking Organization (RBO) portfolio to its Large and Foreign Banking Organization (LFBO) portfolio
- c. Identify Silicon Valley Bank’s specific risk issues which led to and accelerated its failure including deposit concentration, type of deposits, held-to-maturity securities, available-for-sale securities, the bank’s contingent funding plan and capacity, and its capital raising efforts
- d. Identify and describe the failures and shortfalls of Silicon Valley Bank in the areas of governance and risk management including those related to the CRO position and the bank’s internal audit function
- e. Identify the scope of Silicon Valley Bank’s liquidity risk management deficiencies and shortfalls, including its modeling and stress testing of its 30-day liquidity buffer, as well as the actions that management and regulators considered to address these specific liquidity issues
- f. Describe the deficiencies in Silicon Valley Bank’s interest rate risk management process, including its modelling process, and explain how proper use of metrics such as net interest income (NII) at risk and economic value of equity (EVE) could have improved its management of interest rate risk
95. The Credit Suisse CoCo Wipeout-Facts, Misperceptions, and Lessons for Financial Regulation
- a. Describe the features and mechanics of contingent convertible bonds (CoCos) and explain the rationale for banks to issue them
- b. Explain the rescue of Credit Suisse by Swiss regulators in 2023 and compare it to the rescue of Bear Stearns by US regulators during the financial crisis in 2008
- c. Explain the rationale for the write-down of Credit Suisse CoCos that was engineered by regulators during the rescue of Credit Suisse and its takeover by UBS
- d. Describe the reactions by market participants to the write-down of the CoCos, and explain and evaluate different arguments and lessons learned related to the decision to write down the CoCos
96. Artificial Intelligence and Bank Supervision
- a. Describe historical evolution and common types of AI-based applications used in the financial sector
- b. Explain the advantages of implementing AI-based applications to the banking services companies and their customers
- c. Discuss the disadvantages and difficulties for financial companies using AI
- d. Clarify the specific issues faced by banks and regulators arising from utilizing AI in modeling and valuation
97. Financial Risk Management and Explainable, Trustworthy, Responsible AI
- a. Describe the challenge posed by potential model bias and the ethical and responsible considerations surrounding the implementation of AI-driven solutions in financial risk management
- b. Analyze the potential benefits and challenges of utilizing AI while maintaining fairness and preventing biases in risk assessment and decision-making
- c. Explain the proposed considerations for the technical validation of decision-making algorithms to check for potential unfairness
- d. Describe the approaches and technologies that should be considered in the implementation and assessment of Trustworthy AI
- e. Examine the application of Explainable AI (XAI) in the field of credit risk management as presented in the use case of a European insurance group
98. Artificial Intelligence Risk Management Framework
- a. Describe how organizations can frame the risks related to AI and explain the challenges that should be considered in AI risk management
- b. Identify AI actors across the AI lifecycle dimensions and describe how these actors work together to manage risks and achieve the goals of trustworthy and responsible AI
- c. Describe the characteristics of trustworthy AI and analyze the proposed guidance to address them
- d. Explain the potential benefits of periodically evaluating AI risk management effectiveness
- e. Describe specific functions applied to help organizations address the risks of AI systems in practice
99. Climate-Related Risk Drivers and their Transmission Channels
- a. Describe climate-related risk drivers and explain how those drivers give rise to different types of risks for banks
- b. Compare physical and transition risk drivers related to climate change
- c. Assess the potential impact of different microeconomic and macroeconomic drivers of climate risk
- d. Describe and assess factors that can amplify the impact of climate-related risks on banks as well as potential mitigants for these risks
100. Climate-Related Financial Risks-Measurement Methodologies
- a. Describe main issues in identifying and measuring climate-related financial risks
- b. Identify unique data needs inherent in the climate-related risks and describe candidate methodologies that could be used to analyze these types of data
- c. Describe current and developing methodologies for measuring climate-related financial risks employed by banks and supervisors
- d. Compare and contrast climate-measuring methodologies utilized by banks, regulators, and third- party providers
- e. Identify strengths and weaknesses of the main types of measurement approaches
- f. Assess gaps and challenges in designing a modeling framework to capture climate-related financial risk
101. Principles for the Effective Management and Supervision of Climate-Related Financial Risks
- a. Describe the principles for managing climate-related financial risks related to corporate governance and internal control framework
- b. Describe the principles for managing climate-related financial risks related to capital and liquidity adequacy and the risk management process
- c. Describe the principles for the management of climate-related financial risks related to management, monitoring, and reporting, comprehensive management of credit risk and other risks, and scenario analysis
- d. Describe the principles for the supervision of climate-related financial risks related to prudential regulatory and supervisory requirements for banks and responsibilities, powers, and functions of supervisors
102. The Crypto Ecosystem-Key Elements and Risks
- a. Describe the key elements of the crypto ecosystem, including unbacked crypto, stablecoins, smart contracts, and DeFi services
- b. Describe the structural flaws inherent in various elements of the crypto ecosystem
- c. Describe the risks crypto poses to parties including crypto investors, governments, regulators, and traditional financial institutions; and identify potential policy actions that can be taken to mitigate these risks