Credit Risk Measurement and Management: FRM® Part II

It is 20% of the 2026 Part II exam. 190+ learning outcomes across 23 learning modules.

1,100+ practice questions and 256 formula cards on this topic in the app.

Fundamentals of Credit Risk

• State what credit risk is and illustrate, with examples, the ways it comes about.
• Distinguish insolvency from default and from bankruptcy.
• Pinpoint the kinds of transactions that give rise to credit risk and characterise each.
• Set out which entities carry credit risk and the situations in which they become exposed to it.
• Talk through why institutions choose to manage credit risk or to accept it deliberately.

Governance

• Set out who is responsible for risk management inside an organisation and show how the three lines of defense model supports sound risk control.
• Account for the steps through which risk is taken on, namely credit origination, credit risk assessment and credit approval.
• Review four principles of best-practice credit risk governance: Guidelines, Skills, Limits and Oversight.
• Outline the parameters that most often define a credit-sensitive transaction.
• Lay out what a credit committee does within an organisation.

Credit Risk Management

• Outline the main building blocks of a sound lending or financing policy.
• Show why exposure and concentration limits matter and what makes them hard to set.
• Outline how the scope and allocation of a bank's credit facility are handled, and the bank-level policies and steps used to cut credit risk.
• Review the considerations that feed into classifying credit assets.
• Set out what loan loss provisions and loan loss reserves are and how they work.
• Break expected loss into its components, then show how it differs from unexpected loss.
• Account for what IFRS 9 requires when expected loss is estimated.
• Outline a workout procedure for loss assets, and weigh the approach of keeping loss assets on the books against that of writing them off.
• Account for the elements that make up credit risk analysis.
• Lay out what makes up a bank's capacity to manage credit risk, and list the questions its board of directors should be asking.

Capital Structure in Banks

• Judge whether a bank's economic capital is adequate given the credit risk it carries.
• Recognise the three main inputs to economic capital for credit risk, namely loss rate, exposure and the chance of default, and describe each.
• State what expected loss (EL) is and compute it.
• State what unexpected loss (UL) is and compute it.
• Under an assumed binomial distribution, derive the variance of the probability of default.
• Compute UL for a portfolio of credit assets, along with each asset's contribution to it, across differing portfolio mixes, asset features and sizes.
• Explain the derivation of economic capital.
• Account for how the distribution of credit losses is modelled.
• Outline what makes credit risk difficult to quantify.

Introduction to Credit Risk Modeling and Assessment

• Use the CAMEL system, built around earnings, liquidity, management, asset quality and capital adequacy, to appraise how sound a bank is financially.
• Characterise how credit risk is quantified and what drives it, covering exposure at default, loss given default, probability of default, expected loss and the time horizon.
• Calculate a financial institution's capital adequacy ratio after estimating its risk-weighted assets.
• Characterise three families of default prediction: judgmental approaches, empirical models and financial (structural) models.
• Use the Merton model to obtain default probability and distance to default, and set out where the model falls short.
• Contrast how the Merton model, CreditRisk+, CreditMetrics and the Moody's-KMV model each approach credit risk modelling, noting similarities as well as differences.
• Measure how a loan is performing by applying risk-adjusted return on capital (RAROC).

Credit Scoring and Rating

• Set credit scoring against credit rating as tools for judging credit quality, and outline the varieties of each.
• Tell apart rating systems that look through the cycle from those that are point-in-time.
• Walk through how credit risk scoring and rating models get built.
• Outline how rating agencies assign issue ratings and issuer ratings, and name the chief complaints made about those ratings.

Credit Scoring and Retail Credit Risk Management

• Analyse the credit exposure, along with the other risks, that retail banking creates.
• Show where retail credit risk and corporate credit risk part ways.
• Discuss the retail credit risk "dark side" and what is being done to deal with it.
• State what types of credit risk scoring model exist, which variables they rely on and how they are used.
• Discuss which variables matter when assessing a mortgage borrower, and how a credit scoring model uses cutoff scores together with default and loss rates.
• Explain how a scorecard is measured and monitored over time, drawing on the cumulative accuracy profile (CAP) and accuracy ratio (AR) techniques.
• Lay out the stages of the customer relationship cycle and the trade-off that arises between how creditworthy a client is and how profitable.
• Review what is gained from pricing financial services according to risk.

Country Risk: Determinants, Measures, and Implications

• Name the various origins of country risk and explain each.
• Weigh up the ways country risk is measured and review the weaknesses of those ways.
• Compare what happens when a sovereign defaults on foreign currency obligations versus local currency ones.
• Account for what follows when a country defaults.
• Review how sovereign default risk is measured and outline what goes into a sovereign rating.
• Outline where the sovereign rating systems used by rating agencies fall short.
• Weigh CDS spreads, market-based credit default spreads and credit ratings against one another as default predictors, judging which is more reliable.

Estimating Default Probabilities

• Contrast external agency ratings with the rating systems that firms build in-house.
• Lay out how Altman's Z-score method works and put it to use in forecasting default for a firm and in sorting a set of firms into credit quality classes.
• Outline how a borrower's rating relates to its probability of default.
• Describe what a rating migration matrix is, and calculate the marginal, cumulative and ordinary probabilities of default from it.
• Introduce the hazard rate, then employ it to form probability functions for when default occurs and to derive default probabilities that are conditional as well as unconditional.
• Lay out what recovery rates are and how they move with default rates.
• State what a credit default swap (CDS) is and set out how it works, including what each of the protection buyer and the protection seller must do.
• Outline CDS spreads and show how they can serve to infer hazard rates.
• Define the CDS-bond basis and explain what it means.
• Set probabilities of default estimated from past experience beside those inferred from credit yield spreads, and weigh them against each other.
• Outline how real-world default probabilities differ from risk-neutral ones and decide which belongs in a given credit risk analysis.
• Use the Merton model to work out the value of a firm's debt and of its equity, together with the volatility of firm value and of firm equity.
• Use the Merton model to compute distance to default and the default probability.
• Assess the quality of default probabilities that come out of the Kamakura model, the Merton model and the Moody's KMV model.

Credit Value at Risk

• Compare credit VaR with market risk value at risk (VaR) by how each is defined, the horizon it covers and the tools used to measure it.
• State what Credit VaR is and compute it.
• Outline how rating transition matrices are used to derive credit VaR.
• Show how Vasicek's model supports the estimation of capital requirements in the internal-ratings-based (IRB) approach of Basel II.
• Explain how each of Vasicek's model, CreditRisk+ and CreditMetrics derives the probability distribution of default losses and models default correlation.
• State what credit spread risk is and weigh its effect on the computation of credit VaR.

Portfolio Credit Risk

• State what default correlation is for credit portfolios and compute it.
• Name the weaknesses of a credit portfolio framework built on correlation.
• Judge the consequences of correlation for a credit portfolio and the Credit VaR figure attached to it.
• Outline how a single factor model gauges portfolio credit risk, correlation effects included.
• State what beta is and use the single factor model to work out the asset return correlation for any two firms.
• Use the single factor model to estimate the joint default probability and the default correlation for any two credits.
• Describe a simulation of joint defaults as a way to calculate Credit VaR.
• Weigh up how granularity influences Credit VaR.

Credit Risk

• Judge how much credit risk derivative contracts involve.
• Give the definitions of debt valuation adjustment (DVA) and of credit valuation adjustment (CVA).
• Use credit spreads to calculate default probability.
• Outline the different credit risk mitigants, set them side by side and show what part they play in credit analysis.
• Outline why estimating default correlation for credit portfolios matters and tell reduced form default correlation models apart from structural ones.
• Outline the Gaussian copula model of time to default and use the one-factor Gaussian copula to compute default probability.
• Describe how the Gaussian copula and the CreditMetrics approach are each used to estimate credit VaR.

Credit Derivatives

• Describe credit derivatives in general along with three specific instruments: the CDS (credit default swap), the total return swap and the CDO (collateralized debt obligation).
• Show how exposure to credit risk is taken into account when valuing a CDS.
• Pick out which default probabilities are used when a CDS is valued.
• Judge how credit indices and fixed coupons are employed when CDS trades are priced.
• Define a forward on a CDS and an option on a CDS.
• Walk through how a synthetic CDO is priced, using both the spread payments method and a Gaussian copula model of default timing.
• Define implied correlation in its two forms, the compound (tranche) version and the base version.
• Review other methods for estimating default correlation.

Derivatives

• Say what a derivative is and show how trading derivatives exposes a party to counterparty credit risk.
• Contrast the exchange-traded and over-the-counter (OTC) segments of the derivatives world, including how each market is structured.
• Outline how a derivative transaction is cleared.
• Name who takes part in derivatives collateralization and outline how collateral is used.
• Define the ISDA (International Swaps and Derivatives Association) Master Agreement, together with the protections it gives against risk and the events of default it covers.
• Describe what credit derivatives look like and how they are employed, and discuss the risks that might stem from them.
• Describe how OTC derivatives are centrally cleared, and discuss the CCP (central counterparty) in terms of its roles, mandate, benefits and drawbacks.
• Account for the margin rules that apply to centrally-cleared derivatives and to those not centrally cleared.
• Say what SPVs, DPCs (derivatives product companies), monolines and CDPCs (credit derivatives product companies) are, and set out why they are limited as means of mitigating risk.
• Outline the methods for modelling derivatives risk and the difficulties met in doing so.

Counterparty Risk and Beyond

• Describe what counterparty risk is and distinguish it from the risk in lending.
• Outline which transactions bear counterparty risk and show how the risk emerges in each.
• Name the institutions that carry substantial counterparty risk and outline their position.
• Spell out the meaning of mark-to-market, replacement cost, credit exposure, credit migration, recovery, recovery rate, default probability and loss given default.
• Outline credit value adjustment (CVA) and contrast CVA with credit limits as tools for assessing and reducing counterparty risk.
• Name and outline the various ways institutions can measure, manage and reduce counterparty risk.
• Name and account for the costs attached to an OTC derivative.
• Account for the pieces that make up the X-Value Adjustment (xVA) term.

Netting, Close-out and Related Aspects

• Explain what an ISDA master agreement is meant to achieve.
• Sum up netting and close-out procedures, multilateral netting included, with their pros and cons, and show where they sit in the ISDA master agreement framework.
• Outline how well netting cuts credit exposure across different scenarios.
• Outline how termination provisions and trade compressions work and account for their strengths and weaknesses.
• Give worked cases of compressing derivative positions, find the net notional exposure figure and say which counterparty ends up holding the net contract position.
• Name and outline termination events and review how they could affect the parties to a transaction.

Margin (Collateral) and Settlement

• Outline why collateral is managed.
• Set out the terms found in a collateral agreement and the main features of a credit support annex (CSA) in an ISDA Master Agreement: credit support amount, credit quality, haircuts, rounding, minimum transfer amount, initial margin and threshold.
• Compute the margin, meaning the credit support amount, under a number of different scenarios.
• Outline what a valuation agent does.
• Outline how collateral operates in practice and the kinds of collateral commonly used.
• Account for how disputes over collateral are reconciled.
• Spell out what a collateralization agreement typically contains.
• Distinguish CSAs that run one way from those that run both ways, and describe how collateral parameters can depend on credit quality.
• Account for collateral-related aspects such as funding, rehypothecation and segregation.
• Show how collateralization can bring about market risk, operational risk and liquidity risk, funding liquidity risk included.
• Set out the assorted capital requirements imposed by regulators.

Central Clearing

• State what a central counterparty (CCP) is and outline how central clearing works.
• Account for novation as it applies in central clearing.
• Explain multilateral offset, compression and netting, illustrating each with a case.
• Outline how margin and default funds are applied and estimated under central clearing.
• Discuss the exposures a CCP bears and how it controls them.
• Show a loss waterfall at work through illustrations.
• Account for the ways losses are absorbed and the default of one or more CCP members is handled.
• Contrast clearing done bilaterally with clearing done through a central counterparty.
• Contrast the initial margin and default fund contributions asked of clearing members, with respect to how losses are covered, what clearing costs and the moral hazard created.
• Outline the strengths and weaknesses of central clearing.

Future Value and Exposure

• Describe and calculate the credit exposure measures of maximum exposure, effective expected positive exposure, expected positive and negative exposure, potential future exposure, expected exposure and expected mark-to-market.
• Set the way credit exposure is characterised against VaR methods and outline further considerations in determining credit exposure.
• Identify what drives the credit exposure profile calculation and summarise how posting collateral alters exposure.
• Recognise the characteristic exposure profiles of the various derivative contracts and of combinations of them.
• Show why the frequency of payments and the dates on which options can be exercised alter the exposure profile of different securities.
• Account for the general effect of aggregation on exposure, and its effect when transaction values are correlated.
• Outline how funding exposure differs from credit exposure.
• Show how exposure changes under collateralization, and judge what risk the remargining period, threshold and minimum transfer amount introduce.
• Weigh up how collateral affects counterparty risk and funding when it is segregated or rehypothecated versus when it is not.

CVA

• Account for why pricing counterparty risk is wanted and what makes it hard.
• Explain the concept of CVA, the adjustment made to a derivative's value for credit risk.
• Work out CVA, plus its expression as a spread, in the simple setting where wrong-way risk, netting and collateralization are all absent.
• Judge how shifts in credit spread and recovery rate assumptions affect CVA.
• Describe bilateral CVA (BCVA) together with debt value adjustment (DVA).
• Account for how unilateral CVA (UCVA) differs from BCVA, and how unilateral DVA (UDVA) differs from BCVA.
• Work out the DVA and the BCVA, then restate BCVA as a spread.
• Explain the way netting enters the computation of CVA.
• State what incremental CVA and marginal CVA are, compute them and show how CVA is turned into a running spread.
• Show how the CVA figure changes once collateralization is built in, paying attention to initial margins, thresholds and the margin period of risk.
• Spell out wrong-way risk and set right-way risk against it.
• Identify illustrations of right-way risk as well as wrong-way risk.
• Review how collateral bears on wrong-way risk.
• Identify cases that illustrate collateral exposed to wrong-way risk.
• Weigh up how wrong-way risk bears on CCPs (central counterparties).
• Outline the methods for modelling wrong-way risk: hazard rate, structural, parametric and jump approaches.
• Account for what central clearing means for wrong-way risk.

The Evolution of Stress Testing Counterparty Exposures

• Distinguish between expected exposure, expected positive exposure, current exposure and peak exposure.
• Account for counterparty credit risk (CCR) being treated as both credit risk and market risk, and outline what this implies for a financial institution's trading and risk management.
• Describe the stress testing that is possible for a portfolio of loans and for a portfolio of derivatives.
• Distinguish a credit portfolio's stress loss from its stressed expected loss, and calculate stress loss for both a loan portfolio and a derivative portfolio.
• Describe how CVA can be stress tested.
• Work out CVA under stressed conditions together with the resulting stress loss on CVA.
• Compute DVA and account for how stressing DVA feeds into combined CCR stress tests.
• Outline the usual mistakes made when stress testing CCR.

Structured Credit Risk

• Outline the usual kinds of structured products.
• Outline how tranching works and how credit losses are spread across tranches in a securitization.
• Describe how a securitization's waterfall is organised.
• Name the chief parties taking part in securitizing assets, and spell out where their interests may clash.
• Work through and evaluate the first iteration or two of interim cashflows for a securitization split into three tiers.
• Spell out how excess spread is dealt with in a securitization structure, and work out the overcollateralization account's value as each year ends.
• Account for the tests a custodian runs on excess spread at each year end to decide what cash flows to the overcollateralization account and to equity noteholders.
• Spell out a simulation-based way of arriving at credit losses for each tranche of a securitization.
• Show why a securitization's credit risk depends on the default probabilities and default correlations of its collateral.
• Account for how tranche default sensitivities are gauged.
• Spell out the factors of risk to which structured products are subject.
• Show what is meant by implied correlation and the way it can be gauged.
• Name the motives behind the use of structured credit products.

An Introduction to Securitisation

• State what securitization is, outline its process and account for what each participant does.
• Explain cash waterfall, equity piece, first-loss piece and over-collateralization as they apply within securitization.
• Analyse how issuing securitized products through a trust works differently from using a special purpose vehicle (SPV), and tell apart the three chief SPV structures: amortizing, revolving and master trust.
• Account for why securitization is undertaken and what it offers.
• Outline the different kinds of credit enhancement and weigh them up.
• Account for the tools used to analyse the performance of securitized structures and name the asset classes each suits best.
• Define and calculate, for relevant securitized structures, the weighted average life (WAL), weighted average maturity (WAM), weighted average coupon (WAC), debt service coverage ratio (DSCR), monthly payment rate (MPR), default ratio and delinquency ratio.
• Cover the techniques for forecasting prepayments, and compute the PSA (Public Securities Association) rate along with the CPR (constant prepayment rate).

Other topics

• Market Risk Measurement and Management
• Operational Risk and Resilience
• Liquidity and Treasury Risk Measurement and Management
• Risk Management and Investment Management
• Current Issues in Financial Markets
• All of FRM Part II