Credit risk metrics provide efficient tools for measuring the uncertainty of the portfolio loss.
Over the past decade, commercial banks have devoted many resources to developing internal models to better quantify their financial risks and assign economic capital. These efforts have been recognized and encouraged by bank regulators. However, an important question for both banks and their regulators is evaluating the accuracy of a model's forecasts of credit losses, especially given the small number of available forecasts due to their typically long planning horizons.
Credit risk is defined as the degree of value fluctuations in debt instruments and derivatives due to changes in the underlying credit quality of borrowers and counterparties. The ability to measure credit risk clearly has the potential to greatly improve the banks' risk management capabilities. With the forecasted credit loss distribution in hand, the user can decide how best to manage the credit risk in a portfolio, such as by setting aside the appropriate loan loss reserves or by selling loans to reduce risk.
There are two types of metrics required to quantify Credit Risk. The first metric type is called Expected Loss (EL). Expected Loss in statistical terms is the average amount of credit losses per period that a credit company should expect to lose. The second type of metrics is particularly important for credit risk evaluation. It is usually referred to as Economic Capital (EC). The difference between two types of metrics is crucial. Whereas Expected Loss measures the anticipated average loss from a portfolio over the relevant time horizon, Economic Capital captures the variance or the uncertainty of the losses around the average. With its focus on uncertainty, Economic Capital quantifies the portfolio credit risk.
Expected Loss is measured by multiplying together three factors: Probability of Default (Customer's credit quality measurements, agency debt ratings, etc.), Expected Exposure (Accounts receivables plus current mark-to-market exposure of contracts plus the Expected Potential Future Exposure of contracts), and Loss Given Default (Total losses divided by Exposure at default).
Economic Capital is a measure of the amount of resources a firm must maintain to cover a "worst case" credit loss, and still remain solvent. Naturally, the amount of Economic Capital is driven by how an organization decides to define a "worst case" loss. The three drivers of Economic Capital for a "worst case" loss are similar to Expected Loss measurements.
In each case, Credit Risk can be evaluated from two perspectives: Customer Perspective and Credit Company Perspective. The first perspective includes the following measurements: Debt-Service Coverage Ratio (Net Operating Income divided by Total Debt Service), Loan-to-value (the Value of Loan divided by Appraised Value of Property), Combined Loan To Value (the total Value of Loan divided by the total Appraised Value of Property), and Debt-To-Income Ratio (Customer's debt payments divided by the customer's income). The Credit Company Perspective is based on the following metrics: Capital Adequacy (the actual amount of capital (shareholders equity) divided by the calculated amount of Expected Loss), Gross Debt Service Ratio (Annual Loan Payments plus Property taxes, divided by Gross Customer Income), and Customer Credit Quality (Average customer credit quality, according rating reports).
In conclusion, credit risk modeling approach provides credit managers with a powerful tool for measuring credit risk and facilitates several credit risk management applications.