An Overview of Model Based Reject Inference for Credit Scoring
نویسنده
چکیده
Reject inference is the process of estimating the risk of defaulting for loan applicants that are rejected under the current acceptance policy. In this survey article we show how the problem of reject inference can be viewed as one of statistical inference with incomplete data. We use a well known classification of missing data mechanisms into ignorable and nonignorable to organize the discussion of different approaches to reject inference that have been proposed in the literature.
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