Модель інтеграції операційного ризик-менеджменту в систему прийняття рішень банку

Abstract

Among banking risks, operational risk is the most difficult to predict, it poses the threat of unexpected and significant losses for banks. The operational risk of a bank is associated with shortcomings or errors in the organization of internal banking processes, intentional or unintentional actions of bank employees (other persons), failures in the work of the bank’s information systems or it may arise due to external factors. In conditions of high turbulence of the external environment, in which banks are increasingly engaged in preventing losses instead of maximizing profits, it is of paramount importance to ensure the effectiveness of operational risk management and, simultaneously, continuous activities of the bank either under the influence or in the materialization of any threats of operational risk. The materialization of operational risk brings along potential or actual losses, which in some cases may call into question the functioning of the bank. In this regard, compliance with the risk capacity, which is ultimately acceptable to the bank, is of great importance for the bank, taking into account the level of its capital, the adequacy and effectiveness of the risk management system, as well as taking into account regulatory restrictions. Operational risk directly affects financial and economic stability and sometimes acts as a significant undermining not only in the local sense (at the bank level, national level, etc.), but also on a general scale (internationally and globally). The assessment of the bank’s operational risk during any decision-making should protect the bank from extreme manifestations of losses from operational risk events. The article examines the possibility of integrating operational risk management into the bank’s decision-making system and proposes an appropriate model. Testing the model in practical banking activity will improve operational risk management and increase the efficiency of operational risk management.