Title: Risk evaluation method of electronic bank investment based on random forest

Authors: Yi Tang; Jiaojun Yi

Addresses: School of Information Technology and Engineering, Guangzhou College of Commerce, Guangzhou, 511363, China ' School of Economics, Guangzhou College of Commerce, Guangzhou, 511363, China

Abstract: Aiming at the problems of high error rate, low evaluation accuracy and low investment return in traditional methods, a random forest-based e-bank investment risk evaluation method is proposed. First, establish a scientific e-bank investment risk evaluation index system. Then, G1-COWA combined weighting method is used to calculate the weights of each index. Finally, the e-bank investment risk evaluation index data is taken as the input vector, and the e-bank investment risk evaluation result is taken as the output vector. The random forest model is established and the result of e-banking investment risk evaluation is obtained. The experimental results show that the maximum relative error rate of this method is 4.32%, the evaluation accuracy range is 94.5~98.1%, and the maximum return rate of e-banking investment is 8.32%. It shows that this method can accurately evaluate the investment risk of electronic banking.

Keywords: random forest; electronic banking; investment risk evaluation; G1-COWA combination weighting method.

DOI: 10.1504/IJEB.2024.141857

International Journal of Electronic Business, 2024 Vol.19 No.4, pp.420 - 434

Received: 07 Oct 2023
Accepted: 07 Dec 2023
Published online: 02 Oct 2024 *

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