TY - GEN
T1 - Commercial Bank IT Risk Evaluation Model Based on GA-BP Neural Network
AU - Kang, Wenhao
AU - Cheung, Chi Fai
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023/10
Y1 - 2023/10
N2 - 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.
AB - 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.
KW - bank IT risk
KW - BP neural network
KW - genetic algorithm
KW - risk evaluation model
UR - http://www.scopus.com/inward/record.url?scp=85184115102&partnerID=8YFLogxK
U2 - 10.1109/ECICE59523.2023.10383016
DO - 10.1109/ECICE59523.2023.10383016
M3 - Conference article published in proceeding or book
AN - SCOPUS:85184115102
T3 - 2023 IEEE 5th Eurasia Conference on IOT, Communication and Engineering, ECICE 2023
SP - 401
EP - 406
BT - 2023 IEEE 5th Eurasia Conference on IOT, Communication and Engineering, ECICE 2023
A2 - Meen, Teen-Hang
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 5th IEEE Eurasia Conference on IOT, Communication and Engineering, ECICE 2023
Y2 - 27 October 2023 through 29 October 2023
ER -