mlemuel/msmecreditscoring

Loan Default Scoring System

This Hugging Face Space provides a machine learning interface for predicting loan default probabilities using multiple trained models.

Features

• —Multiple Models: Choose from 5 different ML models:
• —Random Forest
• —Gradient Boosting
• —Logistic Regression
• —Naive Bayes
• —Decision Tree

• —Interactive Interface: Input business metrics and get instant predictions
• —Visual Feedback: Bar chart visualization of default probability

How to Use

1. 1.Select your preferred ML model from the dropdown
2. 2.Enter the business/credit metrics:
3. 3.Credit Report Negative Items
4. 4.Accounts Receivable
5. 5.Credit Report Total Indebtedness
6. 6.Capital Expenditure (CAPEX)
7. 7.Credit Report Requests (last 5 years)
8. 8.Business Existence Years
9. 9.Business Failure Score
10. 10.Credit Report Good Standing Items
11. 11.Credit Report Credit Score - A credit score between(0 - 850)
12. 12.Payment Index - a number betweeen

1. 1.Click Submit to see the default probability prediction

Models

All models are pre-trained scikit-learn pipelines that include preprocessing and the classifier.

Requirements

See requirements.txt for dependencies.