Artificial Intelligence Capability for Enterprise Financial Risk Management and Business Resilience

Nasir  Uddin; Md Yeasir  Arafat; Wali Ahmed

doi:10.51699/cajitmf.v7i1.1365

Authors

Nasir Uddin Master of Science in Analytics and Systems, University of Bridgeport, Bridgeport, CT 06605, USA
Md Yeasir Arafat Master of Science in Analytics and Systems, University of Bridgeport, Bridgeport, CT 06605, USA
Wali Ahmed Department of Computer Science, University of Bridgeport, USA

DOI:

https://doi.org/10.51699/cajitmf.v7i1.1365

Keywords:

Artificial Intelligence, Financial Risk Management, Risk Prediction, Business Resilience, Enterprise Risk Governance

Abstract

Background: Artificial intelligence is now making more and more impact on the enterprise financial risk management process, contributing to better risk assessment, prediction and decision-making processes. At the same time, there is not enough empirical data that would explain how AI can be used to improve the mentioned processes in the context of effective financial risk management and risk response, and in addition to that, how such usage impacts business resilience. Methods: In this study, a quantitative cross-sectional design was used, and online survey was conducted among 175 specialists from the United States. Three factors (AI Risk Assessment Capability, AI Risk Prediction Capability and AI Decision-Making Capability) and three outcomes (Financial Risk Management Effectiveness, Risk Response Agility and Business Resilience) were considered in the proposed framework. Results: Consistently positive correlations were observed for all variables included in the research. Financial Risk Management Effectiveness correlated best with Business Resilience at r = 0.756. For Financial Risk Management Effectiveness, the best predictor variable was AI Risk Prediction Capability at β = 0.314, followed by AI Risk Assessment Capability at β = 0.286 and AI Decision-Making Capability at β = 0.267. In turn, Risk Response Agility was best predicted by Financial Risk Management Effectiveness β = 0.582, and Business Resilience was predicted positively by Risk Response Agility β = 0.438. The results explained 67.2% of the variance in Business Resilience. Conclusion: The obtained results suggest that risk capabilities of organizations based on AI have the potential to increase the efficiency of financial risk management and build business resilience.

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