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Machine Learning Techniques-Based Banking Loan Eligibility Prediction

Machine Learning Techniques-Based Banking Loan Eligibility Prediction

Anjali Agarwal, Roshni Rupali Das, Ajanta Das
Copyright: © 2022 |Volume: 14 |Issue: 2 |Pages: 19
ISSN: 2637-7888|EISSN: 2637-7896|EISBN13: 9781683183488|DOI: 10.4018/IJDAI.313935
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MLA

Agarwal, Anjali, et al. "Machine Learning Techniques-Based Banking Loan Eligibility Prediction." IJDAI vol.14, no.2 2022: pp.1-19. http://doi.org/10.4018/IJDAI.313935

APA

Agarwal, A., Das, R. R., & Das, A. (2022). Machine Learning Techniques-Based Banking Loan Eligibility Prediction. International Journal of Distributed Artificial Intelligence (IJDAI), 14(2), 1-19. http://doi.org/10.4018/IJDAI.313935

Chicago

Agarwal, Anjali, Roshni Rupali Das, and Ajanta Das. "Machine Learning Techniques-Based Banking Loan Eligibility Prediction," International Journal of Distributed Artificial Intelligence (IJDAI) 14, no.2: 1-19. http://doi.org/10.4018/IJDAI.313935

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Abstract

In our daily life, it is difficult to meet financial demand while in crisis. This financial crisis may be solved with financial assistance from the banks. The financial assistance is nothing but availing loan from the bank with proper agreement to repay the amount including calculated interest within the loan approved tenure. The customer can only avail loans against the submission of some valid and important supportive documents. However, although the customer is aware of the whole process of repayment and installment along with loan approval tenure, most of the time it is hard to get the approved loan within a shorter period. Therefore, the objective of this paper is to automate this manual and long process by predicting the chance of approval of the loan. The novelty of this research article is to apply machine learning techniques and classification algorithms to predict loan eligibility through an automatic online loan application process

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