Workdiamond2022

Loan Prediction System Using Machine Learning

Yash Patil · Ishan Kotian · Abhinav Shinde · Reshma R. Gulwani

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Financial Distress and Bankruptcy Prediction Microfinance and Financial Inclusion Data Mining and Machine Learning Applications

Abstract

As the needs of people are increasing, the demand for loans in banks is also frequently getting higher every day. Banks typically process an applicant’s loan after screening and verifying the applicant’s eligibility, which is a difficult and time-consuming process. In some cases, some applicants default and banks lose capital. The machine learning approach is ideal for reducing human effort and effective decision making in the loan approval process by implementing machine learning tools that use classification algorithms to predict eligible loan applicants.

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References

2020An Approach for Prediction of Loan Approval using Machine Learning Algorithm 2022LOAN APPROVAL PREDICTION BASED ON MACHINE LEARNING APPROACH 2017Prediction of loan status in commercial bank using machine learning classifier 2015Loan Credibility Prediction System Based on Decision Tree Algorithm

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2024Machine Learning and Deep Learning for Loan Prediction in Banking: Exploring Ensemble Methods and Data Balancing 2022An Approach to Predict Loan Eligibility using Machine Learning

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