A COMPREHENSIVE MODEL FOR MANAGING CREDIT RISK ON HOME MORTGAGE PORTFOLIOS

Managing credit risk in financial institutions requires the ability to forecast aggregate losses on existing loans, predict the length of ti me that loans will be on the books before prepayment or default, analy ze the expected performance of particular segments in the existing por tfolio, and project payment patterns of new loans. Described in this p aper are tools created for these functions in a large California finan cial institution. A forecasting model with Markovian structure and non stationary transition probabilities is used to model the life of a mor tgage. Logistic and regression models are used to estimate severity of losses. These models are integrated into a system that allows analyst s and managers to depict the expected performance of individual loans and portfolio segments under different economic scenarios. With this i nformation, analysts and managers can establish appropriate loss reser ves, suggest pricing differentials to compensate for risk, and make st rategic lending decisions.