ARTIFICIAL INTELLIGENCE POTENTIAL AND RISKS IN OPERATIONAL RISK MANAGEMENT IN BANKS
ARTIFICIAL INTELLIGENCE POTENTIAL AND RISKS IN OPERATIONAL RISK MANAGEMENT IN BANKS

Summary/Abstract: Operational risks are the risk of losses resulting from inadequate or failed internal processes, people and systems, or from external events, including legal risks. They represent a significant type of risk for banks. At the same time, digitalization has a major influence on business models, processes and the internal structures of companies with artificial intelligence being one of the driving forces. This article aims to identify potential opportunities and risks of AI in the context of operational risk management. Methodologically, a literature analysis is used for this goal. Applications in the area of process automation or reporting are possible as well as frameworks for the early detection of risks. Various quality controls can be carried out in a more structured and efficient manner with AI. On the other hand, there are systematic challenges with regard to the quantity and quality of data as well as the other framework conditions for an introduction of AI in the company. Furthermore, various legal aspects remain unclear and harbor risks. Finally, AI applications harbor a whole range of IT risks that can only be mitigated to a limited extent. As a result, it is impossible to make a generalized statement as to whether the introduction of AI in operational risk management is sensible and expedient. The question must be decided on a case-by-case basis based on the existing requirements, resources and overall strategy.

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