Prediction of Bank Fixed Deposits Based on Logistic Regression

Fei Xie

2024

Abstract

Fixed deposits, as the main source of bank funds, are also a prerequisite for the safety of bank operations and good market liquidity. Having more deposits is more conducive to the various investments of banks and the stable development of the national economy, and whether customers will participate in the fixed deposit business has become a focus of research by scholars from various countries. Logistic regression, as a typical binary discrimination method, is highly favored by scholars from various countries in terms of accuracy and interpretability. This article uses logistic regression to analyze the factors of customers themselves and the effectiveness of telemarketing and establishes a mathematical model, achieving good results with an accuracy of 89%, which has the significance of guiding customer selection. Meanwhile, this article believes that if more accurate data can be obtained and psychological data on personality, emotions, and other aspects can be added, the model's accuracy will be further improved.

Paper Citation

in Harvard Style

Xie F. (2024). Prediction of Bank Fixed Deposits Based on Logistic Regression. In Proceedings of the 1st International Conference on Data Science and Engineering - Volume 1: ICDSE; ISBN 978-989-758-690-3, SciTePress, pages 189-195. DOI: 10.5220/0012842900004547

in Bibtex Style

@conference{icdse24,
author={Fei Xie},
title={Prediction of Bank Fixed Deposits Based on Logistic Regression},
booktitle={Proceedings of the 1st International Conference on Data Science and Engineering - Volume 1: ICDSE},
year={2024},
pages={189-195},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0012842900004547},
isbn={978-989-758-690-3},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 1st International Conference on Data Science and Engineering - Volume 1: ICDSE
TI - Prediction of Bank Fixed Deposits Based on Logistic Regression
SN - 978-989-758-690-3
AU - Xie F.
PY - 2024
SP - 189
EP - 195
DO - 10.5220/0012842900004547
PB - SciTePress