Learning Objectives:

  • Define credit risk and identify its sources.

  • Understand credit risk assessment techniques.

  • Explain credit risk measurement models: Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD).

  • Understand credit risk mitigation strategies.

2.1 Defining Credit Risk

Credit risk is the risk of loss from a borrower or counterparty failing to meet its obligations. The University of Leeds module covers “Credit Risk Management: Individual Loan Risk” and “Credit Risk Management: Portfolio Risk” as core topics . The University of Bologna module covers “Credit Risk Part I (Probability of Default, Loss Given Default and Exposure at Default, Scoring Models)” and “Credit Risk Part II (Portfolio Models)” .

Sources of Credit Risk:

  • Individual Borrowers: Risk of default by a specific borrower.

  • Portfolio Concentration: Over-exposure to a single borrower, sector, or geographic region.

  • Counterparty Risk: Risk of default by a counterparty in financial transactions.

  • Settlement Risk: Risk of settlement failure.

  • Country Risk: Political and economic risks in a borrower’s country.

2.2 Credit Risk Assessment

Credit risk assessment involves evaluating the creditworthiness of borrowers. The National Banking Institute’s course covers “Credit Risk Management” in detail, including “Risk Rating and Risk Pricing,” “Portfolio Management,” and “Loan Policy – Prudential Exposure & Limits on Exposure for Individuals, Institutions, Groups and Banks.”

Key Elements of Credit Risk Assessment:

  • Credit Scoring: Statistical models to assess creditworthiness.

  • Internal Risk Ratings: Assigning risk grades to individual borrowers.

  • Financial Statement Analysis: Analysing balance sheets, income statements, and cash flows.

  • Industry and Economic Analysis: Assessing the borrower’s industry and broader economic conditions.

  • Collateral Valuation: Evaluating the quality and value of assets pledged as security.

2.3 Credit Risk Measurement Models – The PD-LGD-EAD Framework

Since the 2004 debut of Basel II, all credit risk measurement starts with Probability of Default (PD), Loss Given Default (LGD), and Exposure at Default (EAD) . These three components form the foundation of credit risk measurement and are encoded in the Basel framework’s formula for calculating Risk-Weighted Assets (RWA) .

Probability of Default (PD): The likelihood that a borrower will default over a given time horizon. For each identified pool of exposures, banks are expected to provide an estimate of the PD, subject to minimum requirements . The PD for retail exposures is the greater of the one-year PD associated with the internal borrower grade and a minimum floor (0.1% for qualifying revolving retail exposures and 0.05% for all other exposures) . A model that directly estimates a corporate borrower’s PD should be complemented by qualitative assessment of the borrower’s management, industry and country risk .

Loss Given Default (LGD): The percentage of the exposure that will be lost in the event of default. For each exposure that is used as input into the risk weight formula and the calculation of expected loss, the LGD must not be less than the parameter floors . LGD parameter floors for retail exposures include: mortgages (5%), QRRE (0%), other retail (30%) . The LGD floor for residential mortgages is fixed at 5%, irrespective of the level of collateral provided by the property .

Exposure at Default (EAD): The total value of the exposure outstanding at default. Both on- and off-balance sheet exposures are measured gross of specific provisions or partial write-offs . The EAD on drawn amounts should not be less than: (i) the amount by which a bank’s regulatory capital would be reduced if the exposure were written-off fully; and (ii) any specific provisions and partial write-offs . For undrawn balances associated with securitised revolving facilities, banks must continue to hold required capital against the undrawn balances .

Expected Loss: EL = PD × LGD × EAD, representing the anticipated loss from credit exposures.

Risk-Weighted Assets (RWA): Under the IRB approach, banks calculate RWA using risk weight functions that incorporate PD, LGD, EAD, and Effective Maturity (M) .

2.4 Credit Risk Mitigation

Banks use several strategies to mitigate credit risk:

  • Diversification: Spreading exposure across borrowers and sectors.

  • Collateral: Securing loans with assets that can be liquidated in default. Banks may reflect the risk-reducing effects of collateral through an adjustment of either the PD or LGD estimate .

  • Guarantees: Obtaining third-party guarantees to support repayment. Banks may reflect the risk-reducing effects of guarantees through an adjustment of either the PD or LGD estimate, subject to minimum requirements .

  • Loan Covenants: Imposing conditions on borrowers to manage risk.

  • Credit Derivatives: Using instruments like Credit Default Swaps (CDS) to transfer risk.

2.5 Portfolio Credit Risk Models

Credit Risk Part II focuses on portfolio models . Key models include:

  • CreditMetrics (JP Morgan): Measures credit risk by assessing the distribution of portfolio value changes due to credit rating migrations and defaults .

  • KMV Model: Uses equity prices to estimate the probability of default for publicly traded firms.

  • CreditRisk+: A model that treats default as a Poisson process.

  • McKinsey Model: A macro-economic based model for credit risk.

The Silesian University module covers “Credit risk transfer” as a dedicated topic, including “Secondary market loan sale,” “Credit insurance,” “Securitization,” and “Credit derivatives, motives and risk of their use.”

 

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