Journal of Accounting and Management Vision

Journal of Accounting and Management Vision

Transition from traditional enterprise risk management to intelligent decision-based enterprise risk management: The role of artificial intelligence in risk aggregation and value creation

Document Type : Original Article

Authors
1 Assistant Professor of Accounting, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran.
2 PhD Student of Accounting, Faculty of Management and Economics, Tarbiat Modares University, Tehran, Iran.
Abstract
The transformation of business environments, increased uncertainties, and risk complexities have challenged the efficiency of traditional Enterprise Risk Management (ERM) approaches. This research aims to explain the evolution of ERM from a control-oriented and reactive approach towards an integrated, intelligent, and decision-driven ERM. The research methodology is based on a structured review and meta-analysis of domestic and international theoretical and empirical literature. Key concepts such as risk aggregation, Monte Carlo simulation, and artificial intelligence have been examined as the main analytical axes. Findings indicate that the lack of effective risk aggregation mechanisms in standards like the COSO ERM framework is a primary obstacle to achieving decision-driven risk management. In this context, Monte Carlo simulation, as an efficient tool for quantifying and aggregating financial and non-financial risks, facilitates the transformation of ERM into a decision support system. Furthermore, the integration of artificial intelligence with risk aggregation and simulation processes enhances ERM into a forward-looking, adaptive, and value-creating system. The research results suggest that an intelligent, decision-driven ERM framework can play an effective role in improving risk governance, information transparency, and strategic decision-making in organizations, particularly within the context of the Iranian economy.
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