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FRM Part II · FRM Exam Part II

Credit Risk Management for FRM Part II: Chapter Guide

Credit risk management is the measurement, pricing, mitigation and governance of losses from borrowers or counterparties failing to pay. For FRM Part II, you learn the core inputs (PD, LGD, EAD), apply the models, read the results, and name the right Basel concept. Practise with short numerical and interpretive questions.

What this chapter covers

This chapter covers how a bank or investor measures and controls the risk that a borrower or counterparty does not pay. It starts with single-name analysis and ratings, moves to models of default, then to portfolios, counterparty exposure, mitigation, structured products and regulation.

Most questions combine three things: a risk measure (for example expected loss = PD × LGD × EAD), a method to compute it, and an interpretation of what it means for the bank. You need to know the formulas, but you also need to know why a result moves when an input changes.

The chapter links to the rest of the paper. Market Risk uses the same ideas of tail loss and diversification. Liquidity and Treasury Risk shares collateral and funding links with counterparty risk. Risk Management and Investment Management brings in credit spreads and portfolio limits. Current Issues includes private credit, which draws directly on credit analysis, covenants and concentration.

Credit risk is one of the six topics in Part II, and the exam is 80 equally weighted multiple-choice questions in 4 hours, so every credit question is worth the same as any other. The chapter also feeds other topics, because collateral, spreads, capital and private credit show up elsewhere. Strong command here gives you quick, reliable marks on formula-based questions and on precise definition questions, which leaves more time for the longer case-style items.

Credit Risk Management: topics in the order to study them

  1. 1Credit Risk Fundamentals and Credit AnalysisIt defines PD, LGD, EAD, expected and unexpected loss, which every later topic uses.
  2. 2Credit Ratings and Rating Transition MatricesRatings and transition matrices turn credit quality into probabilities you can compute with, including multi-year default.
  3. 3Structural and Reduced-Form Credit ModelsOnce you know PD as an input, you learn the two main ways to model where it comes from.
  4. 4Credit Portfolio Risk and ConcentrationIt extends single-name risk to correlation, diversification and tail loss across a book.
  5. 5Counterparty Credit Risk and Exposure MeasuresIt applies exposure ideas to derivatives, where EAD changes with market moves, and builds on portfolio thinking.
  6. 6Credit Risk Mitigation: Collateral, Guarantees and CovenantsMitigation reduces the exposure or loss you have just learned to measure, so it follows naturally.
  7. 7Credit Derivatives and SecuritizationThese products transfer credit risk and need the earlier models, ratings and mitigation ideas.
  8. 8Credit Risk Governance, Regulation and CapitalIt ties everything to Basel capital and oversight, and is easiest once you know the underlying measures.

How to prepare Credit Risk Management

Credit questions reward a clear chain: define the inputs, compute the measure, then interpret it. Prepare in that order.

  1. Learn the core definitions first: PD, LGD, EAD, expected loss and unexpected loss. Write each formula from memory until it is automatic.
  2. For each topic, solve a few short numerical problems by hand. Check each step, including units and whether an input is annual or multi-year.
  3. After each calculation, say in one sentence what the result means for the bank, such as what happens to loss if correlation rises.
  4. Build a one-page comparison of the models: what each assumes, what it needs as input and where it fails. Questions often ask you to choose or critique.
  5. Learn Basel terms precisely. Know the exact name of each concept and what it measures, and do not swap similar-sounding terms.
  6. Read the private credit reading from Current Issues alongside this chapter, and link it to covenants, concentration and ratings.
  7. Finish with timed mixed sets of questions. Review every wrong answer and note whether the error was a formula, a concept or a misread.

Common mistakes in Credit Risk Management

  • Mixing up PD horizons, such as using a one-year PD in a multi-year calculation.

    Fix: Write the horizon next to every PD, and use the transition matrix or hazard rate to move between horizons.

  • Confusing expected loss with unexpected loss and capital.

    Fix: Remember that expected loss is the average and is priced and provisioned, while unexpected loss is the variation that capital covers.

  • Treating structural and reduced-form models as interchangeable.

    Fix: Ask what drives default in the model: firm asset value, or an exogenous hazard rate. Then check the information each model needs.

  • Assuming collateral or netting always removes exposure.

    Fix: State the conditions: enforceable agreements, collateral value changes, haircuts and the time to liquidate.

  • Using loose language for Basel concepts.

    Fix: Learn each term as GARP defines it, and match the option wording to the exact concept being measured.

  • Doing the arithmetic but not interpreting the result.

    Fix: After each answer, state the direction and cause of change, such as what a lower recovery rate does to loss.

Last-day revision: Credit Risk Management

  • Expected loss = PD × LGD × EAD, using consistent time horizons.
  • Recovery rate = 1 − LGD when both are expressed as a share of exposure.
  • Expected loss is a cost of business; unexpected loss is the variability that capital is held against.
  • Transition matrices: each row sums to 100%, and multi-year transitions come from matrix multiplication under the Markov assumption.
  • Structural models treat equity as a call option on firm assets; default occurs when asset value falls below debt at the horizon in the basic Merton model.
  • Reduced-form models treat default as a random event driven by a hazard rate, not tied directly to firm value.
  • Higher default correlation fattens the tail of portfolio losses without changing expected loss.
  • Concentration risk comes from large single names, sectors or regions, and diversification reduces it.
  • Counterparty exposure on derivatives depends on market moves, and netting reduces it only where legally enforceable.
  • Collateral lowers loss given default but brings its own risks, such as value falls and legal issues.
  • Credit derivatives transfer credit risk but can create counterparty risk with the protection seller.
  • Capital rules set minimums, and governance sets limits, approval and monitoring of credit exposure.

Credit Risk Management practice questions

Credit Risk Management in other exams

The same ground in other exams, if you are preparing for more than one or want another angle on it.

Credit Risk Management: frequently asked questions

How many questions in FRM Part II come from credit risk?

GARP lists Credit Risk Measurement and Management as one of six topics in Part II. The exam has 80 equally weighted multiple-choice questions in 4 hours. Check GARP's current exam guide for the official topic details, and prepare every topic well.

Is the credit risk chapter mostly numerical?

It is a mix. You will see calculations such as expected loss, transition probabilities and exposure, but also questions on model assumptions, mitigation and Basel concepts. Practise both calculation and interpretation.

Which credit risk topic should I study first?

Start with credit risk fundamentals and credit analysis. PD, LGD, EAD and expected loss are used in every later topic, so a firm base here makes the models, portfolio and counterparty topics much easier.

Does private credit appear in the credit chapter?

Private credit is part of the 2026 Current Issues readings (BIS, February 2025), not this chapter's title list. It connects closely, though, so review it alongside credit analysis, covenants and concentration.