A credit model is a scoring framework banks and lenders use to estimate borrower risk and set pricing, limits, or approval decisions. It usually combines financial data, repayment history, identity signals, and other attributes into a risk score or probability of default.
In cyber security, credit models matter because they depend on sensitive data and automated decisioning. Attackers may try to steal customer records, submit synthetic identities, alter application data, or poison training inputs to influence a model’s output. Defenders protect these systems with strong access control, data validation, audit logging, and model monitoring so unexpected score shifts can be detected. A well-governed credit model also helps reduce fraud and keeps lending decisions consistent when reporting data changes or becomes less complete.