Amanyadav-07/mortgage-default-risk-dashboard

🏦 Real-time mortgage default risk scoring dashboard built with Streamlit & Scikit-learn. Enter borrower details → get instant default probability, risk tier, and underwriting recommendation.

14
/ 100
Experimental
No License No Package No Dependents
Maintenance 13 / 25
Adoption 0 / 25
Maturity 1 / 25
Community 0 / 25

How are scores calculated?

Stars

—

Forks

—

Language

Jupyter Notebook

License

—

Category

credit-risk-modeling

Last pushed

Mar 08, 2026

Commits (30d)

0

GitHub
Credit Risk Modeling · 228 frameworks

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/ml-frameworks/Amanyadav-07/mortgage-default-risk-dashboard"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.

Higher-rated alternatives

xRiskLab/xBooster

Explainable Boosted Scoring with Python: turning XGBoost, LightGBM, and CatBoost into...

64

ing-bank/skorecard

scikit-learn compatible tools for building credit risk acceptance models

55

minerva-ml/open-solution-home-credit

Open solution to the Home Credit Default Risk challenge :house_with_garden:

51

semasuka/Credit-card-approval-prediction-classification

Credit risk analysis for credit card applicants

50

ParthS007/Loan-Approval-Prediction

Loan Application Data Analysis

48

Explore ML Frameworks

All categories Trending ML Framework directory Insights