AI-Powered Credit Risk Assessment

Advanced machine learning model that predicts loan default probability using borrower financial data. Make informed lending decisions with 95%+ accuracy.

95%+

Accuracy

1,248

Training Data

3

ML Models

Live Prediction
85% Safe
Risk Score
Low Risk
Confidence
92.3%

Credit Score Predictor

Enter borrower information to get instant credit risk assessment

$
Enter the borrower's annual income in USD
$
Enter the requested loan amount
Choose the loan repayment period
Borrower's credit history status

Key Features

Advanced AI capabilities for comprehensive credit risk assessment

Machine Learning Models

Three advanced ML algorithms: Logistic Regression, Decision Tree, and Random Forest for accurate predictions.

Real-time Analytics

Instant risk assessment with detailed probability scores and confidence intervals.

Risk Mitigation

Comprehensive risk profiling to minimize loan defaults and optimize lending decisions.

SHAP Interpretability

Model interpretability using SHAP values to understand prediction reasoning.

Data Processing

Advanced data preprocessing with feature engineering and missing value imputation.

Responsive Design

Mobile-friendly interface accessible from any device, anywhere, anytime.

Model Analytics

Comprehensive insights into model performance and data patterns

Model Performance
Feature Importance
Dataset Overview

1,248

Total Samples

85.2%

Non-Default Rate

14.8%

Default Rate

4

Features

About This Project

This credit scoring model leverages advanced machine learning techniques to assess loan default risk with high accuracy.

Technical Specifications:
  • Random Forest Classifier
  • Feature Engineering & Scaling
  • SHAP Model Interpretability
  • Cross-validation Testing
Developer:
Developer
Rohan Kumar

@rohan911438

Python

Machine Learning

Scikit-learn

ML Framework

SHAP

Interpretability

JavaScript

Web Interface