This document introduces Larry Chiang and his open-sourced decision-making models for thin file analysis, risk assessment, and credit scoring. It discusses using additional data from credit applications to compile an "epsilon" value and adjusting the "slope P" to define risk appetite. Different cases are presented where the focus is mainly on the "f" value or epsilon. Once risk is selected, multiple scorecard scenarios can be established. The discussion also includes establishing a 3D scorecard matrix and selecting risk points within a defined "risk plane." Larry Chiang advocates for electronic credit disputes to carry the same weight as disputes by mail.
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7. The f function has credit applicant informationF (留, 硫, 皹) (d, z, 0)
8. Define RiskBy adjusting the slope P, you define your risk appetiteSlope PWhen p=0 not a factorWhen p is , is ONLY factor
9. Case Study to Determine RiskBy adjusting the slope P, you define your risk appetiteLess risk (higher up axis)More risk
10. Case Study Which to WeighMore-- ? Or epsilon? Focus mainly on Focus is on not a factor simple old systemPure function(3)(2)(1)(4)
11. Once Risk Is SelectedMultiple ScorecardScenarioSingleScorecardScenarioABBC
12. Scorecard Matrix/Credit Line MatrixEstablish multiple points forwide range of credit linesAdd another dimension!3-D ScorecardMatrixllllbreaks out scorecard factors from
13. Risk SelectionGoes from a simple slope to an entire planeSelect pointswithin plane!Risk Planell
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16. RatesThe higher the supply of banks in competition for consumers, the more competitive the interest rate, junk fees, etc.
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