EDA: Bank Loan Default Risk Analysis

N. Ramadevi, Vasagiri Sai Kumar, Kondamadugula Dheeraj Reddy, Gandragoli Kasi Viswanath, Natuva Komal Sai, Bachu Venkata Deepak Kumar

2025

Abstract

The increasing number of debt lapse presents a large assignment to economic institutions, affecting their profitability and lengthy-term economic stability. Debt omission occurs whilst the borrower fails to fulfill his compensation obligations, leading to expanded hazard for banks and creditors. Identification of things contributing to those omissions is vital to improve credit score danger evaluation and make sure greater powerful lending practices. This takes a look at focuses on search information analysis (EDA) to research historical mortgage records and highlight the most important pattern affecting the loan reimbursement behavior. By analyzing borrower characteristics including income level, employment repute, credit score, mortgage quantity, hobby rate and reimbursement history, the purpose of this take a look at is to become aware of critical factors that determine the opportunity of mortgage urge. Using data visualization and statistical strategies, the research default examines the relationship between various economic and demographic variables to provide precious insights in chance. Understanding those patterns can assist banks to make loans and manipulate financial dangers knowledgeable. Analysis curses the importance of credit score history, as debtors with negative compensation records are more likely to default. Additionally, elements along with high loan-to-earnings ratio, risky employment and big loan quantity contribute to debt offenses. By identifying these essential chance indicators, economic establishments can boom their credit evaluation shape and apply extra powerful hazard mitigation strategies. One of the major goals of this have a look at is to help banks in developing facts-driven loan approval strategies. By leveraging insights from EDA, monetary establishments can refine their lending standards, reduce non-acting loans, and optimize risk evaluation fashions. This, in turn, facilitates in preserving financial balance whilst making sure that eligible borrowers get hold of get admission to credit score.

Paper Citation

in Harvard Style

Ramadevi N., Kumar V., Reddy K., Viswanath G., Sai N. and Kumar B. (2025). EDA: Bank Loan Default Risk Analysis. In Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25; ISBN 978-989-758-777-1, SciTePress, pages 125-129. DOI: 10.5220/0013909100004919

in Bibtex Style

@conference{icrdicct`2525,
author={N. Ramadevi and Vasagiri Kumar and Kondamadugula Reddy and Gandragoli Viswanath and Natuva Sai and Bachu Kumar},
title={EDA: Bank Loan Default Risk Analysis},
booktitle={Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25},
year={2025},
pages={125-129},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013909100004919},
isbn={978-989-758-777-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Research and Development in Information, Communication, and Computing Technologies - ICRDICCT`25
TI - EDA: Bank Loan Default Risk Analysis
SN - 978-989-758-777-1
AU - Ramadevi N.
AU - Kumar V.
AU - Reddy K.
AU - Viswanath G.
AU - Sai N.
AU - Kumar B.
PY - 2025
SP - 125
EP - 129
DO - 10.5220/0013909100004919
PB - SciTePress