JatinSharma496/AI_Predictive_Models_for_Credit_Underwriting
This repository contains a machine learning-based predictive model for automating loan eligibility assessments. Using features such as demographic details, loan information, and credit history, the model predicts whether a loan should be approved or denied.
This project helps loan officers, credit risk managers, and financial analysts quickly assess the likelihood of a loan applicant defaulting. You input details like the applicant's age, income, employment length, loan amount, and credit history. The system then provides an instant prediction of whether the loan is likely to default, along with insights into which factors influenced that decision.
No commits in the last 6 months.
Use this if you need an automated, data-driven tool to speed up loan eligibility assessments and improve the accuracy of your lending decisions.
Not ideal if you require a comprehensive credit scoring system that integrates with complex financial databases or mandates specific regulatory compliance features beyond default prediction.
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Language
Jupyter Notebook
License
MIT
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Last pushed
Aug 27, 2025
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