In current Banking industry, a wide range of studies are taking place attempting for effective modeling and measurement of operational risk exposure to meet the regulatory requirement set by Capital Accord II by Basel Committee on Banking Supervision. In contrast, this study focuses on proactive risk monitoring for non-financial institutions and applying best modeling practices of banking industry. Critical Success Factor Methodology and Critical Activities Concept are applied in the process of risk identifying and selecting most important operational risks. Bayesian probabilistic network modeling approach is being used to develop causal network of risk factors and are targeted on monitoring key risk points. These networks enable responsive risk monitoring and proactive risk management as well as certain degree of risk estimation functionality. A software tool - Hugin Lite version 6.8 - is used for Bayesian-KRI networks development and implementation of concepts. Basic considerations of future development framework are outlines and a conceptual model is introduced.
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