Abhi0323/Machine-Learning-Based-Loan-Default-Early-Warning-System
Developed an end-to-end ML system on Azure to predict loan defaults, leveraging advanced data preprocessing, feature engineering, and machine learning models to optimize accuracy. This project includes a comprehensive suite of tools and techniques for robust financial risk assessment, deployed to enhance decision-making for high-risk exposures.
This system helps financial institutions predict which loan applicants are likely to default. It takes a customer's financial data and other relevant details as input, then provides an instant prediction of their default risk. Credit risk managers, loan officers, and financial analysts can use this to make more informed lending decisions.
No commits in the last 6 months.
Use this if you need to quickly assess the default risk of loan applicants to minimize potential financial losses.
Not ideal if you're looking for a general-purpose fraud detection system or require predictive models for other types of financial risk.
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22
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8
Language
Jupyter Notebook
License
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Last pushed
Apr 21, 2024
Commits (30d)
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