A credit scoring model is a mathematical model used to estimate the probability of default, which is the probability that customers may trigger a credit event (e.g., bankruptcy, obligation default, failure to pay, and cross-default events). In a credit scoring model, the probability of default is normally presented in the form of a credit score. A higher score refers to a lower probability of default.
Credit scoring models rely on several factors, including some that are common to all loans and some that vary by loan type.. For example, the credit factors for a credit card loan may include payment history, age, number of account, and credit card utilization; the credit factors for a mortgage loan may include down payment, job history, and loan size.
Accurate and predictive credit scoring models help maximize the risk-adjusted return of a financial institution. However, markets and consumer behavior can change rapidly during economic cycles, such as recessions or expansions. For this reason, risk managers or credit analysts need to not only create the models, but also quickly adjust and validate them. Techniques used to create and validate credit scoring models include: