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Loan default prediction using Machine Learning Models

Vijay Kumar, Rachna Narula, Akanksha Kochhar

Abstract


Borrowing from financial institutions has become commonplace in today's society. Many people submit loan applications each day for a variety of reasons. But not every one of these candidates is reliable, and not everyone is accepted. A significant part of bank loans are frequently not returned each year, leaving the bank with enormous losses. Making a choice to approve a loan involves significant risks. Therefore, the goal of this project is to gather credit data from a variety of sources and then use various machine learning techniques to extract key information. With the use of this model, businesses can decide whether to approve or reject consumer loan requests. This article examines actual bank credit data, performs numerous


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