A curated list of data mining papers about fraud detection.

Scorecard Development in python, 评分卡

ESC Team's credit scorecard tools.

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

Open solution to the Home Credit Default Risk challenge :house_with_garden:

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

Scorecard Development in R, 评分卡

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

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

No description provided.

Analytics labs notebooks for Statistics and Business School students

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

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

No description provided.

Predicting the default customers

天池大数据竞赛 千里马大赛 风险识别与预测赛题 Top5

Model explanation provides the ability to interpret the effect of the predictors on the composition of an individual score.

creditmodel, 模型，评分卡，scorecard, vintage, automatic modeling

This work aim to, on one side, the backend code develop on Python Notebook (code_credit_scoring_np.ipynb), for reason of readability, to find the best Hyperparameter in order to achieve the best forecast for the credit scoring with algorithm we analize during the thesis

A short course on survival analysis applied to the financial industry

Innovative solution for credit scoring leveraging machine learning to predict credit risk using The International Bank for Reconstruction and Development (IBRD) Loans dataset.

Project which will predict credit default or credit risk using artificial neural network algorithms. It will help banks and financial institutions to assign a credit score to the customer profile/portfolio and make a decision whether to sanction a loan or not

The objective of this project is to predict credit score of the borrowers using logistic regression and provide threshold cut-off recommendation

Developing a comprehensive and effective credit scoring model for Bati Bank, leveraging data from an eCommerce platform to enable a buy-now-pay-later service for customers. This project involves understanding credit scoring methodologies, exploratory data analysis (EDA), feature engineering, model training and evaluation, and API development for re

Credit scoring modeling toolbox based on R