Loan Default Prediction Using Machine Learning Techniques and Deep Learning ANN Model
subject: Artificial Neural Network; Kaggle; Lending Club; Loan prediction
description: Loan default prediction is a critical task in the financial sector, aimed at assessing the creditworthiness of borrowers and minimizing potential losses for lending institutions. Online loans continue to reach the public spotlight as Internet technology develops, and this trend is expected to continue in the foreseeable future. In this paper, the authors proposed loan default loan prediction system based on ML and DL models. This work makes use of the information on loan defaults provided by Lending Club. The dataset is preprocessed by applying various data preprocessing techniques and preprocessed dataset is generated. Later, we proposed four ML algorithms decision tree, random forest, logistic regression, K-NN and Feed forward neural network. The experimental results shown that proposed feed forward neural network achieved good accuracy for loan default prediction with an accuracy of 99%. 2023 IEEE.
creator: Lakshmanarao A.; Gupta C.; Koppireddy C.S.; Ramesh U.V.; Dev D.R.
source: 2023 Annual International Conference on Emerging Research Areas: International Conference on Intelligent Systems, AICERA/ICIS 2023
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2023-01-01
rights: Restricted Access
relation: ISBN: 979-835030345-2
format: Online
language: English
type: Conference paper
coverage: Lakshmanarao A., Aditya Engineering College, Department of It, Surampalem, India; Gupta C., School of Commerce, Finance and Accountancy, Christ University, India; Koppireddy C.S., Pragati Engineering College, Cse Department, A.P, Surampalem, India; Ramesh U.V., Aditya Engineering College, Department of Cse, Surampalem, India; Dev D.R., Vignan's Institute of Engineering for Women, India