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Construction of an AI-Driven Risk Management Framework for Financial Service Firms Using the MRDM Approach

Author

Listed:
  • Kuang-Hua Hu

    (School of Accounting, Finance and Accounting Research Center, Nanfang College, Guangzhou, Guangdong 510970, P. R. China)

  • Fu-Hsiang Chen

    (Department of Accounting, College of Business, Chinese Culture University, 55, Hwa-Kang Road, Yang-Ming-Shan, Taipei 11114, Taiwan, R. O. China)

  • Ming-Fu Hsu

    (English Program of Global Business, Chinese Culture University, 55, Hwa-Kang Road, Yang-Ming-Shan, Taipei 11114, Taiwan, R. O. China)

  • Gwo-Hshiung Tzeng

    (Graduate Institute of Urban Planning, College of Public Affairs, National Taipei University, Taipei Campus, 67, Sec. 3, Ming-shen E. Road, Taipei 10478, Taiwan, R. O. China)

Abstract

The complex problem of risk factors has greatly increased globally due to the quick ever-changing digital era. The development of suitable techniques for facilitating the performance of risk management in the financial service domain is thus an urgent task, especially in today’s highly turbulent business environment. The development of such techniques involves many factors like the classical multiple criteria decision-making (MCDM) problem, but too many factors surrounding the users will confuse them and lead to improper judgments. To deal with this critical task, this study proposes a fusion multiple rule-based decision-making (MRDM) approach that integrates a rule-based technique [i.e., the fuzzy rough set theory (FRST) with particle swarm optimization (PSO)] into MCDM (i.e., DEMATEL, DANP, and modified-VIKOR) techniques that can help decision makers choose the optimal model necessary for achieving aspiration-level effects in a risk control strategy. The results indicate that the improvement priority, which runs in the order as (a) AI algorithm model, (c) AI regulatory and compliance, (d) AI conduct, and (b) AI technology based on the magnitude of the impact, can effectively improve the performance of AI-driven risk management for financial service firms.

Suggested Citation

  • Kuang-Hua Hu & Fu-Hsiang Chen & Ming-Fu Hsu & Gwo-Hshiung Tzeng, 2021. "Construction of an AI-Driven Risk Management Framework for Financial Service Firms Using the MRDM Approach," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 20(03), pages 1037-1069, May.
    • Handle: RePEc:wsi:ijitdm:v:20:y:2021:i:03:n:s0219622021500279
    DOI: 10.1142/S0219622021500279
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    Cited by:

    1. Jeng-Bang Wang & Guan-Hua Wang & Chung-Ya Ou, 2023. "The Key Factors for Sustainability Reporting Adoption in the Semiconductor Industry Using the Hybrid FRST-PSO Technique and Fuzzy DEMATEL Approach," Sustainability, MDPI, vol. 15(3), pages 1-19, January.

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