Popular GitHub Repositories for Institucional Lending

Institutional-grade protocol for tokenizing Real-World Assets (RWAs) on Solana. Features: on-chain compliance, KYC/AML verification, and DeFi integrations for global markets.

Building Classification & Prediction model to classify the Loan applicant request as approved or rejected and then predict the Interest rate for Loan Approval.

Leveraging Federated Learning for Unsecured Loan Risk Assessment on Decentralized Finance Lending Platforms

This is our second project at neuefische DS Bootcamp. Silas Mederer (https://github.com/sls-mdr) and me applied different ML models and for credit default prediction of the P2P platform Lending Club.

AI-driven credit underwriting system combining Machine Learning (ML) & Reinforcement Learning (RL) to optimize loan approvals while managing risk: Credit Risk Prediction via Random Forest model; PPO & DQN for dynamic risk control; Custom OpenAI Gym Environment for simulating real-world lending scenarios & FastAPI real-time processing.

Complete credit risk modeling system: Lending Club default prediction with XGBoost, business-optimized thresholds, and SHAP explainability

Loan Default Prediction Model: A machine learning project that leverages historical lending data to create predictive models for assessing loan default risk, aiding financial institutions in making informed lending decisions.

Predict loan defaults using ML. Leverage Logistic Regression, Random Forest, XGBoost. Preprocess data, train models, analyze features. Make informed lending decisions. Jupyter Notebook and code.

Lendefi Markets for Avalanche

? Predict loan default risk using a logistic regression model, empowering financial institutions to make informed lending decisions with data-driven insights.

Stabilization of classification ML-models using synthetic data with outliers on Open Data.

This project builds an early stage credit default detection model using only application data, intended to serve as a fast prescreening filter before any extra document submission, external bureau checks, ore manual review, enhancing customer experience while maintaining low financial risk in online lending.