credit-scoring

A curated list of data mining papers about fraud detection.

Scorecard Development in python, 评分卡

Optimal binning: monotonic binning with constraints. Support batch & stream optimal binning. Scorecard modelling and counterfactual explanations.

ESC Team's credit scorecard tools.

Open solution to the Home Credit Default Risk challenge 🏡

Tools for WoE Transformation mostly used in ScoreCard Model for credit rating

A collection of awesome papers, articles and various resources on credit and credit risk modeling

Scorecard Development in R, 评分卡

Amazon SageMaker Solution for explaining credit decisions.

Statistical analysis and visualization of state transition phenomena

国内首个迁移学习赛题 中国平安前海征信“好信杯”迁移学习大数据算法大赛 FInSight团队作品(算法方案排名第三)

Prediction of loan defaulter based on more than 5L records using Python, Numpy, Pandas and XGBoost

Explainable Boosted Scoring with Python: turning XGBoost, LightGBM, and CatBoost into explainable scorecards

⚖️ Fair ML in credit scoring: Assessment, implementation and profit implications

Machine learning research code for causal perception: comparing competing structural causal models (SCMs) via interventional and counterfactual distributions, applied to fair credit decisions. Open source by Santander AI Lab.

Analytics labs notebooks for Statistics and Business School students

openLGD is a Python powered library for the statistical estimation of Credit Risk Loss Given Default models. It can be used both as standalone library and in a federated learning context where data remain in distinct (separate) servers

Implementation of Genetic Algorithm for feature selection of neural networks proposed by Genetic algorithm-based heuristic for feature selection in credit risk assessment paper.