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25. Estimating Default Probabilities
- d. Describe a rating migration matrix and calculate the probability of default, cumulative probability of default, and marginal probability of default
- a. Compare agencies’ ratings to internal credit rating systems
- e. Define the hazard rate and use it to define probability functions for default time as well as to calculate conditional and unconditional default probabilities
- f. Describe recovery rates and their dependencies on default rates
- g. Define a credit default swap (CDS) and explain its mechanics including the obligations of both the default protection buyer and the default protection seller
- h. Describe CDS spreads and explain how CDS spreads can be used to estimate hazard rates
- i. Define and explain CDS-bond basis
- j. Compare default probabilities calculated from historical data with those calculated from credit yield spreads
- k. Describe the difference between real-world and risk-neutral default probabilities and determine which one to use in the analysis of credit risk
- l. Using the Merton model, calculate the value of a firm’s debt and equity, the volatility of firm value, and the volatility of firm equity
- m. Using the Merton model, calculate distance to default and default probability
- n. Assess the quality of the default probabilities produced by the Merton model, the Moody’s KMV model, and the Kamakura model
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
17. Fundamentals of Credit Risk
- a. Define credit risk and explain how it arises using examples
- b. Explain the distinctions between insolvency, default, and bankruptcy
- c. Identify and describe transactions that generate credit risk
- d. Describe the entities that are exposed to credit risk and explain circumstances under which exposure occurs
- e. Discuss the motivations for managing or taking on credit risk
18. Governance
- a. Define risk management responsibilities in an organization and explain the three lines of defense framework for effective risk management and control
- b. Explain the processes that lead to risk taking including credit origination, credit risk assessment, and credit approval processes
- c. Discuss the following key principles underlying best practice for the governance system of credit risk: Guidelines, Skills, Limits, and Oversight
- d. Describe the most common parameters of a credit-sensitive transaction
- e. Describe the roles of the credit committee in an organization
19. Credit Risk Management
- a. Describe key elements of an effective lending or financing policy
- b. Explain the importance and challenges of setting exposure and concentration limits
- c. Describe the scope and allocation processes of a bank’s credit facility and explain bank-specific policies and actions to reduce credit risk
- d. Discuss factors that should be considered during the credit asset classification process
- e. Describe and explain loan loss provisions and loan loss reserves
- f. Identify and explain the components of expected loss and distinguish between expected loss and unexpected loss
- g. Explain the requirements for estimating expected loss under IFRS 9
- h. Describe a workout procedure for loss assets and compare the following two approaches used to manage loss assets: retaining loss assets and writing off loss assets
- i. Explain the components of credit risk analysis
- j. Explain the components of credit risk management capacity, and outline key questions that the board of directors of a bank should ask
21. Introduction to Credit Risk Modeling and Assessment
- a. Explain the capital adequacy, asset quality, management, earnings, and liquidity (CAMEL) system used for evaluating the financial condition of a bank.
- b. Describe quantitative measurements and factors of credit risk, including probability of default, loss given default, exposure at default, expected loss, and time horizon.
- c. Estimate capital adequacy ratio of a financial institution
- d. Describe the judgmental approaches, empirical models, and financial models to predict default
- e. Apply the Merton model to calculate default probability and the distance to default and describe the limitations of using the Merton model.
- f. Compare and contrast different approaches to credit risk modeling, such as those related to the Merton model, Credit Risk Plus (CreditRisk+), CreditMetrics, and the Moody’s-KMV model
- g. Apply risk-adjusted return on capital (RAROC) to measure the performance of a loan
22. Credit Scoring and Rating
- a. Compare the credit scoring system to the credit rating system in assessing credit quality and describe the different types of each system
- b. Distinguish between through-the-cycle and point-in-time credit rating systems
- c. Describe the process for developing credit risk scoring and rating models
- d. Describe rating agencies’ assignment methodologies for issue and issuer ratings, and identify the main criticisms of the credit rating agencies’ ratings
24. Country Risk-Determinants, Measures, and Implications
- a. Identify and explain the different sources of country risk
- b. Evaluate the methods for measuring country risk and discuss the limitations of using those methods
- c. Compare and contrast foreign currency defaults and local currency defaults
- d. Explain the consequences of a country’s default
- e. Discuss measures of sovereign default risk and describe components of a sovereign rating
- f. Describe the shortcomings of the sovereign rating systems of rating agencies
- g. Compare the use of credit ratings, market-based credit default spreads, and CDS spreads in predicting default
26. Credit Value at Risk
- a. Compare market risk value at risk (VaR) with credit VaR in terms of definition, time horizon, and tools for measuring them
- c. Describe the use of rating transition matrices for calculating credit VaR
- d. Describe the application of the Vasicek model to estimate capital requirements under the Basel II internal-ratings-based (IRB) approach
- e. Interpret the Vasicek’s model, Credit Risk Plus (CreditRisk+) model, and the CreditMetrics ways of estimating the probability distribution of losses arising from defaults as well as modeling the default correlation
- f. Define credit spread risk and assess its impact on calculating credit VaR
29. Credit Risk
- b. Define credit valuation adjustment (CVA) and debt valuation adjustment (DVA)
- c. Calculate the probability of default using credit spreads
- e. Describe the significance of estimating default correlation for credit portfolios and distinguish between reduced form and structural default correlation models
- f. Describe the Gaussian copula model for time to default and calculate the probability of default using the one-factor Gaussian copula model
- g. Describe how to estimate credit VaR using the Gaussian copula and the CreditMetrics approach
30. Credit Derivatives
- a. Describe a credit derivative, credit default swap (CDS), total return swap, and collateralized debt obligation (CDO)
- b. Explain how to account for credit risk exposure in valuing a CDS
- c. Identify the default probabilities used to value a CDS
- d. Evaluate the use of credit indices and fixed coupons in pricing CDS transactions
- e. Define CDS forwards and CDS options
- f. Describe the process of valuing a synthetic CDO using the spread payments approach and the Gaussian copula model of time to default approach
- g. Define the two measures of implied correlation: compound (tranche) correlation and base correlation
- h. Discuss alternative approaches used to estimate default correlation
31. Derivatives
- a. Define derivatives and explain how derivative transactions create counterparty credit risk
- b. Compare and contrast exchange-traded derivatives and over-the-counter (OTC) derivatives, and discuss the features of their markets
- c. Describe the process of clearing a derivative transaction
- d. Identify the participants and describe the use of collateralization in the derivatives market
- e. Define the International Swaps and Derivatives Association (ISDA) Master Agreement, the risk-mitigating features it provides, and the default events it covers
- f. Describe the features and use of credit derivatives and discuss potential risks they may create
- g. Describe central clearing of OTC derivatives and discuss the roles, mandate, advantages, and disadvantages of the central counterparty (CCP)
- h. Explain the margin requirements for both centrally-cleared and non-centrally-cleared derivatives
- i. Define special purpose vehicles (SPVs), derivatives product companies (DPCs), monolines, and credit derivatives product companies (CDPCs) and describe the limitations of using them as risk mitigating methods
- j. Describe the approaches used and the challenges faced in modeling derivatives risk
35. Central Clearing
- a. Define a central counterparty (CCP) and describe the mechanics of central clearing
- b. Explain the concept of novation under central clearing
- c. Define netting, multilateral offset, and compression and provide examples of each
- d. Describe the application and estimation of margin and default funds under central clearing
- e. Discuss the risks faced by a CCP and the ways it manages its exposures
- f. Provide examples of a loss waterfall
- g. Explain the different methods of managing the default of one or more members of a CCP
- h. Compare bilateral and central clearing
- i. Compare initial margin and default fund requirements for clearing members in relation to loss coverage, cost of clearing, and moral hazard
- j. Describe the advantages and disadvantages of central clearing
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
103. Digital Resilience and Financial Stability
- a. Describe characteristics of cyber risks and information/communication technology (ICT) risks faced by financial institutions
- b. Assess the interactions between cyber and ICT risks and financial risks and explain how cyber and ICT risk events at financial institutions can lead to systemic financial risk
- c. Describe potential macroprudential tools and policy measures that can be used to address cyber risks and ICT risks and explain challenges to the adoption of each one
17. The Credit Decision
- b. Explain the components of credit risk evaluation
- d. Compare and contrast quantitative and qualitative techniques of credit risk evaluation
- e. Compare the credit analysis of consumers, corporations, financial institutions, and sovereigns
- g. Compare bank failure and bank insolvency
18. The Credit Analyst
- a. Describe the quantitative, qualitative, and research skills a banking credit analyst is expected to have
- b. Assess the quality of various sources of information used by a credit analyst
20. Rating Assignment Methodologies
- a. Explain the key features of a good rating system
- b. Describe the experts-based approaches, statistical-based models, and numerical approaches to predicting default
- d. Describe rating agencies’ assignment methodologies for issue and issuer ratings
- f. Compare agencies’ ratings to internal experts-based rating systems
- g. Distinguish between the structural approaches and the reduced-form approaches to predicting default
- j. Describe the application of a logistic regression model to estimate default probability
- k. Define and interpret cluster analysis and principal component analysis
- l. Describe the use of a cash flow simulation model in assigning ratings and default probabilities and explain the limitations of the model
- m. Describe the application of heuristic approaches, numeric approaches, and artificial neural networks in modeling default risk and define their strengths and weaknesses
- n. Describe the role and management of qualitative information in assessing probability of default
21. Credit Risks and Credit Derivatives
- a. Using the Merton model, calculate the value of a firm’s debt and equity and the volatility of firm value
- b. Explain the relationship between credit spreads, time to maturity, and interest rates and calculate credit spread
- c. Explain the differences between valuing senior and subordinated debt using a contingent claim approach
- d. Explain, from a contingent claim perspective, the impact of stochastic interest rates on the valuation of risky bonds, equity, and the risk of default
- g. Describe a credit derivative, credit default swap (CDS), and total return swap
- h. Explain how to account for credit risk exposure in valuing a swap
22. Spread Risk and Default Intensity Models
- a. Compare the different ways of representing credit spreads
- b. Compute one credit spread given others when possible
- c. Define and compute the Spread ‘01
- d. Explain how default risk for a single company can be modeled as a Bernoulli trial
- e. Explain the relationship between exponential and Poisson distributions
- f. Define the hazard rate and use it to define probability functions for default time and conditional default probabilities
- g. Calculate the unconditional default probability and the conditional default probability given the hazard rate
- h. Distinguish between cumulative and marginal default probabilities
- i. Calculate risk-neutral default rates from spreads
- j. Describe advantages of using the CDS market to estimate hazard rates
- k. Explain how a CDS spread can be used to derive a hazard rate curve
- l. Explain how the default distribution is affected by the sloping of the spread curve
- m. Define spread risk and its measurement using the mark-to market and spread volatility
32. The Credit Transfer Markets-and Their Implications
- a. Discuss the flaws in the securitization of subprime mortgages prior to the financial crisis of 2007-2009
- b. Identify and explain the different techniques used to mitigate credit risk and describe how some of these techniques are changing the bank credit function
- c. Describe the originate-to-distribute model of credit risk transfer and discuss the two ways of managing a bank credit portfolio
- d. Describe covered bonds, funding collateralized loan obligations (CLOs), and other securitization instruments for funding purposes
- e. Describe the different types and structures of credit derivatives including credit default swaps (CDS), first-to default puts, total return swaps (TRS), asset-backed credit-linked notes (CLN), and their applications
34. Understanding the Securitization of Subprime Mortgage Credit
- a. Explain the subprime mortgage credit securitization process in the United States
- b. Identify and describe key frictions in subprime mortgage securitization and assess the relative contribution of each factor to the subprime mortgage problems
- c. Compare predatory lending and borrowing
- d. Describe the various features of subprime MBS and explain how these features are designed to protect investors from losses on the underlying mortgage loans
- e. Distinguish between corporate credit ratings and asset-backed securities (ABS) credit ratings
- f. Explain how through-the-cycle ABS rating can amplify the housing cycle
89. Machine Learning and AI for Risk Management
- a. Explain the distinctions between the two broad categories of machine learning and describe the techniques used within each category
- b. Analyze and discuss the application of AI and machine learning techniques in the following risk areas: - Credit risk - Market risk - Operational risk - Regulatory compliance
- c. Describe the role and potential benefits of AI and machine learning techniques in risk management
- d. Identify and describe the limitations and challenges of using AI and machine learning techniques in risk management
90. Artificial Intelligence Risk and Governance
- a. Identify and discuss the categories of potential risks associated with the use of AI by financial firms and describe the risks that are considered under each category
- b. Describe the four core components of AI governance and recommended practices related to each
- c. Explain how issues related to interpretability and discrimination can arise from the use of AI by financial firms
- d. Describe practices financial firms can adopt to mitigate AI risks
94. Inflation-a look under the hood
- a. Describe how the dynamics of inflation differ between a low-inflation regime and a high-inflation regime
- b. Explain the process of wage and price formation, the role inflation plays in this process, and vice versa
- c. Describe the various channels through which inflation expectations manifest in financial markets and discuss the inference of inflation expectations from financial markets
- d. Describe the operation of a central bank’s monetary policy in a low-inflation regime and evaluate indicators a central bank can use for timely detection of transitions to a high-inflation regime
95. The Blockchain Revolution-Decoding Digital Currencies
- a. Explain how a blockchain-based cryptocurrency system works and compare cryptocurrencies to conventional money and payment systems
- b. Describe elements of a decentralized finance structure, including smart contracts, tokenized assets, decentralized autonomous organizations, and decentralized exChanges
- c. Define stablecoins and assess their advantages and disadvantages, including their potential contribution to systemic risk and regulatory considerations
- d. Explain the advantages, disadvantages, and potential applications of a central bank digital currency
96. The future monetary system
- a. Identify and describe the benefits and limitations of crypto and decentralized finance (DeFi) innovations
- b. Describe the role of stablecoins in DeFi ecosystems and differentiate among the types of stablecoins
- c. Discuss possible advantages and disadvantages of a monetary system based on CBDCs
- d. Understand the risks posed by the centralization that occurs in DeFi ecosystems and crypto exChanges (CEX)
- e. Outline the regulatory actions recommended by the BIS to manage risks in the crypto monetary system