projects / 2026 / Study

Credit Scorecard & Survival-Causal Study

An interpretable WOE/IV credit scorecard benchmarked against gradient boosting, plus survival and causal analysis of time-to-default on a public lending dataset.

  • Python
  • scikit-learn
  • statsmodels
  • lifelines
  • Credit Risk

What it is

A credit-risk study on a public lending dataset, in three parts.

The scorecard

An interpretable Logistic Regression scorecard with WOE/IV binning, benchmarked against a gradient-boosted model on AUC, KS and Gini. Class imbalance was handled with SMOTE and cost-sensitive thresholding, which meaningfully improved minority-class recall over the baseline.

Time to default

A Cox proportional-hazards model on time-to-default, to see which borrower and loan attributes change when a loan defaults, not only whether it does.

Does changing the loan term help?

A propensity-matched, difference-in-differences analysis estimating the effect of loan-term modifications on default risk.

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