Credit Risk

Why credit risk matters

Credit risk affects bonds, loans, derivatives, deposits, trade receivables, and many structured products. Even without default, a downgrade or widening credit spread can reduce market value. For lenders and fixed-income investors, the return premium must compensate for expected loss, uncertainty, illiquidity, and economic sensitivity. Portfolio outcomes often depend on correlated defaults during recessions rather than on an average borrower viewed alone.

How it is applied

Analysts evaluate business resilience, cash flow, leverage, collateral, covenants, seniority, refinancing needs, management, and industry conditions. Expected credit loss is often framed as probability of default multiplied by exposure at default and loss given default. Portfolios add issuer, sector, geography, maturity, and rating limits. Spread duration estimates sensitivity to changing credit spreads, while scenario tests model migrations, defaults, recoveries, and liquidity shocks.

Formula

Portfolio example

A lender has a $10 million exposure, estimates a 2% one-year default probability, and expects to lose 60% of exposure after collateral and recovery. Modeled expected loss is $120,000. This is not a prediction that the loan will lose exactly that amount. Most outcomes may have no default, while an adverse outcome produces a much larger loss. Pricing and reserves must also reflect uncertainty and capital usage.

How to interpret it

Higher yields and wider spreads often signal greater perceived credit or liquidity risk, but they are not direct default probabilities. Ratings rank relative creditworthiness and can lag new information. Senior secured debt may have better recovery than subordinated debt from the same issuer, yet documentation and collateral quality matter. Investors should separate expected loss from unexpected loss and compare the promised spread with both, after fees and liquidity costs.

Limitations and common misconceptions

Default probabilities and recoveries are uncertain and highly cyclical. Historical samples may contain few defaults, while correlations rise in downturns. Accounting values can obscure leverage and off-balance-sheet claims. Collateral may fall alongside borrower quality, and covenants may provide less protection than expected. Credit models can create false precision, so security documentation, scenario analysis, diversification, and liquidity planning remain essential.