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Before Thomas, credit scoring was mostly application scoring (should we lend at application?). Thomas championed behavioral scoring, which uses a borrower’s transaction and payment history over time to predict future risk. credit scoring and its applications by l c thomas hot
Under FCA and CFPB rules, you must produce a clear reason for each denial. Thomas’s recommendation: “Use a simple logistic scorecard as the primary decision rule, then augment with ML for borderline cases. Always be able to rewrite the decision in English.” Credit Scoring and Its Applications: The Enduring Legacy
A recurring theme in Thomas’s work is rejection inference: how do you validate a model when you only observe outcomes for approved applicants? He championed parceling and expectation-maximization methods long before they became machine learning staples. Thomas championed behavioral scoring , which uses a
Recent advances in credit scoring include the use of: