Commercial Bank IT Risk Evaluation Model Based on GA-BP Neural Network

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

1 Citation (Scopus)

Abstract

To assess IT risk in commercial banks and reduce the probability of incidents, we constructed a set of IT risk evaluation indices based on determining the set of IT risk factors. To improve the accuracy of the evaluation model, the Genetic Algorithm (GA) was used to adjust the weights and thresholds of the BP neural network, thereby establishing a GABP-based IT risk evaluation model. By collecting data from a commercial bank for model testing, the IT risk evaluation was successfully implemented, and the weights of risk evaluation indicators were calculated. The correlation coefficient R values of the model's training set, test set, validation set, and full sample set were greater than 0.95, demonstrating excellent predictive performance and effective IT risk evaluation. Based on the evaluation indicators, the weights of the indicators, and risk levels, commercial banks can develop corresponding targeted preventive and control measures. This comprehensive approach provides commercial banks with more reliable IT risk management and decision support.

Original languageEnglish
Title of host publication2023 IEEE 5th Eurasia Conference on IOT, Communication and Engineering, ECICE 2023
EditorsTeen-Hang Meen
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages401-406
Number of pages6
ISBN (Electronic)9798350314694
DOIs
Publication statusPublished - Oct 2023
Event5th IEEE Eurasia Conference on IOT, Communication and Engineering, ECICE 2023 - Yunlin, Taiwan
Duration: 27 Oct 202329 Oct 2023

Publication series

Name2023 IEEE 5th Eurasia Conference on IOT, Communication and Engineering, ECICE 2023

Conference

Conference5th IEEE Eurasia Conference on IOT, Communication and Engineering, ECICE 2023
Country/TerritoryTaiwan
CityYunlin
Period27/10/2329/10/23

Keywords

  • bank IT risk
  • BP neural network
  • genetic algorithm
  • risk evaluation model

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Hardware and Architecture
  • Human-Computer Interaction
  • Media Technology

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