Classification model to predict the probability that a customer defaults based on their monthly customer statements using the data provided by American Express.
-
Updated
Apr 28, 2023 - Jupyter Notebook
#
default-prediction
Here are 38 public repositories matching this topic...
Machine learning model to identify customers that are more likely to default based on employment, bank balance and annual salary.
data-science machine-learning aprendizado-de-maquina classification-algorithm classification-model ciencia-de-dados pycaret default-prediction
-
Updated
Aug 18, 2022 - Jupyter Notebook
Logistic regression-based credit scoring model using public Kaggle data, designed for transparent PD estimation, performance evaluation, and teaching or regulatory use cases.
kaggle logistic-regression credit-scoring applied-statistics credit-risk default-prediction probability-of-default
-
Updated
May 28, 2025 - Jupyter Notebook
End-to-end Credit Risk Analytics project using Home Credit data featuring default prediction, XGBoost modeling, customer risk segmentation, underwriting framework, and Power BI dashboard.
python machine-learning power-bi xgboost credit-scoring credit-risk risk-analytics default-prediction financial-analytics banking-analytics
-
Updated
Jun 10, 2026 - Jupyter Notebook
Finance and Risk Analytics Project: Predicting credit default risk using machine learning models (Logistic Regression, Random Forest) and assessing stock market risk through historical returns and volatility analysis to guide financial risk management and investment strategies.
-
Updated
Nov 8, 2024 - Jupyter Notebook
A program to take in loan level data and create a model which can predict probability of default
-
Updated
May 21, 2020 - Python
Machine learning project for credit card default prediction using CatBoost, probability calibration, SHAP explainability and cost-sensitive decision thresholds.
python finance data-science machine-learning classification probability-calibration catboost credit-risk shap default-prediction
-
Updated
Jun 9, 2026 - Jupyter Notebook
Working with an industrial scale data set to build a classification model to predict credit card default, and help creating a better customer experience for cardholders.
-
Updated
Sep 1, 2022 - Jupyter Notebook
The goal of this project is to perform default prediction for commercial real estate property loans based on 17 variables.
python machine-learning eda oversampling undersampling commercial-real-estate mortgage-defaults default-prediction macroeconomic-indicators
-
Updated
Feb 19, 2023 - Jupyter Notebook
End-to-end credit risk modeling to predict loan default and support data-driven lending decisions.
machine-learning fintech credit-risk explainable-ai financial-modeling risk-analytics default-prediction
-
Updated
Feb 13, 2026 - Python
Leakage-aware LendingClub default-risk prediction with logit, elastic net, CART, bagging, random forests, gains and lift screening, and cross-fitted DML.
machine-learning r random-forest logistic-regression cart feature-engineering credit-scoring model-evaluation elastic-net bagging lendingclub roc-auc credit-risk data-leakage p2p-lending default-prediction double-machine-learning cross-fitting brier-score gains-chart
-
Updated
Aug 12, 2026 - R
Implementation of "Financial Default Prediction via Motif-Preserving Graph Neural Networks" - Demo application with synthetic financial network generation, structural pattern analysis, and GCN-based risk prediction.
-
Updated
Dec 27, 2025 - Python
A group assignment on Machine Learning.
-
Updated
May 24, 2024 - Jupyter Notebook
Amex Default Prediction
kaggle-competition lightgbm data-compression feature-engineering bayesian-optimization optuna default-prediction
-
Updated
Dec 6, 2022 - Jupyter Notebook
AI-powered Loan Decision & Credit Risk Platform with Explainable AI, Risk Governance, Analytics Dashboard, and PDF Reporting built using Streamlit & Machine Learning.
python machine-learning hackathon fintech banking data-analytics risk-management credit-risk explainable-ai loan-analytics streamlit default-prediction idbi-innovate-2026
-
Updated
Jul 8, 2026 - Python
Builds predictive models to estimate borrower default probability
-
Updated
Mar 19, 2026 - Python
Production-ready credit risk modeling platform built with Streamlit and scikit-learn to predict loan default probability, generate 300–900 credit scores, explain decisions with SHAP, run what-if simulations, batch-score CSV files, and export PDF assessment reports.
python machine-learning scikit-learn fintech logistic-regression credit-scoring credit-risk explainable-ai shap optuna risk-modeling default-prediction batch-inference loan-underwriting
-
Updated
Apr 17, 2026 - Jupyter Notebook
Production-ready ML system for credit default prediction on transactional data (458k clients). Features end-to-end pipeline: 1,158 engineered features, ablation & Top-500 pruning, LightGBM HPO (AMEX 0.791, Gini 0.923), multi-seed stability, CLI batch inference (20.1s/458k), and 267/267 automated tests.
python machine-learning feature-selection fintech xgboost hyperparameter-optimization lightgbm feature-engineering credit-scoring risk-management catboost optuna time-series-aggregation experiment-tracking ablation-study default-prediction batch-inference ml-system-design reproducible-ml amex-default-prediction
-
Updated
Aug 9, 2026 - Python
信用违约概率预测项目的早期实验仓库。
-
Updated
Jul 20, 2017
Improve this page
Add a description, image, and links to the default-prediction topic page so that developers can more easily learn about it.
Add this topic to your repo
To associate your repository with the default-prediction topic, visit your repo's landing page and select "manage topics."