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expected-loss

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A credit risk modeling project using Logistic Regression to estimate Probability of Default (PD) and compute Expected Loss (EL) using a Basel-style framework. Includes stress testing under macro shocks and analysis of key drivers like interest rate, income, and debt-to-income ratio. Provides interpretable risk insights with ROC-AUC evaluation.

  • Updated Jun 5, 2026
  • Jupyter Notebook

Governed PostgreSQL credit decisioning simulator for synthetic applications, pre-production strategy testing, matched comparison, counteroffer governance, and Expected Loss tradeoffs—without PII.

  • Updated May 30, 2026

Personal-loan credit-risk & unit-economics platform: vintage delinquency curves, expected-loss modeling, and an interactive approval-threshold scenario simulator. Built with dbt, DuckDB, Python, and Streamlit.

  • Updated May 8, 2026
  • Python

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