Reject Inference

A technique of deciphering hidden patterns, like a cartographer mapping uncharted territory, used in credit scoring and risk assessment to estimate the creditworthiness of applicants who were not approved for loans, thereby enhancing the accuracy and fairness of the decision-making process.

Example

Suppose a bank has a dataset of loan applicants, including both approved and rejected applicants. When building a credit scoring model, the bank only has information about the performance of approved applicants. Reject Inference allows the bank to make informed estimates about the creditworthiness of rejected applicants, despite the lack of performance data. This helps the bank refine its decision-making process and ensure that future applicants are assessed more fairly and accurately, potentially identifying creditworthy individuals who might have been previously overlooked.