Credit scoring machine learning algorithm which predicts probability of default

A decentralised credit scoring platform based on Multichain blockchain

Implement supervised machine learning techniques in order to further understanding the process in which a client will be granted a credit and be denied a credit.

Credit Score Provider for the Faker Python Project. Use this to generate fake but realistic-looking consumer credit scores aligning to the most prevalent risk models (FICO, VantageScore, etc.)

A streamlit app on credit score classification

Feature Selection for Credit Scoring using Genetic Algorithm Wrapper(Information Gain)

Reverse engineering of the FICO algorithm

The official ARCx contracts repo

In this project, I used a dataset containing financial information and personal details of individuals to build and evaluate machine learning models to predict their credit scores. The credit score is an important metric that determines an individual's creditworthiness and ability to obtain loans.

An Exploratory Data Analysis was done on the Credit Card dataset using libraries in R . The EDA insights were used to create a report.

Hybrid Credit Score Calculation for DeFi Lending using Risc Zero zkVM

Türkçe: Findeks kredi notu hesaplama sisteminin Python ile yapılmış basitleştirilmiş bir simülasyonu. English: A simplified simulation of the Findex credit scoring system built with Python.

canvas实现类似支付宝信用分的效果(演示的是非模块版本的，codesandbox的index2.html是模块传参的）

This repo contains analysis of Lending Club Credit rates and also case study for a client to get a fully funded loan at the lowest credit rate with a desired duration.

A Flutter package

Classification Model for Credit Score using Logistic Regression, Evaluation using AUC and KS

CredVibe is an ML credit scorecard system achieving 95%+ default recall with explainable predictions for loan risk assessment. Features KS/Gini validation, Optuna tuning, FastAPI + Streamlit deployment. Generates CIBIL-like scores, and converts to business rules for BRE integration.

Projeto de criação de modelo de machine learning para score de credito, percorrendo todo o pipeline dos dados. Coleta, exploração, tratamento, limpeza, treino e deploy.

IScore Credit Dashboard built with Python and CustomTkinter

This project analyzes and predicts credit scores based on customer financial data using machine learning. It includes data cleaning, preprocessing, feature encoding, and model training with Logistic Regression and other classifiers to evaluate prediction accuracy.