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UD — Credit Underwriting Engine — Technical Spec
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# Understanding Document — Credit Underwriting Engine ## 1. Overview This UD captures the technical architecture and functional specification of the automated credit underwriting engine. ## 2. Functional Specification The credit underwriting engine evaluates loan applications using a combination of bureau data, internal scoring models, and policy rules. ### 2.1 Scoring Model - Primary: CIBIL score (weight: 40%) - Secondary: Internal behavioral score (weight: 30%) - Tertiary: Income-to-EMI ratio (weight: 30%) ## 3. Technical Specification ### 3.1 Technology Stack - Rule Engine: Drools 8.x - ML Model: XGBoost (Python, served via FastAPI) - Database: PostgreSQL 15 for decision audit trail ## 4. Data Model ### 4.1 Input Schema ```json { "applicantId": "string", "panNumber": "string", "cibilScore": "number", "monthlyIncome": "number", "existingEMI": "number", "loanAmount": "number", "tenure": "number" } ``` ## 5. Integration Points - CIBIL API: POST /v3/credit-report - Internal Scoring API: POST /scoring/v2/evaluate - Drools Rule Engine: REST API ## 6. Edge Cases - Applicant with no credit history (thin file): Route to manual underwriting - NRI applicants: Use overseas credit report if available
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Understanding Document — Credit Underwriting Engine
1. Overview
2. Functional Specification
2.1 Scoring Model
3. Technical Specification
3.1 Technology Stack
4. Data Model
4.1 Input Schema
5. Integration Points
6. Edge Cases