Operational Risk Quantification : A Risk Flow Approach
Gandolf R. Finke, Mahender Singh, Svetlozar T. Rachev
Abstract
Gandolf R. Finke, Mahender Singh, Svetlozar T. Rachev
Abstract
ABSTRACT Operational risk has been receiving increasing attention, both in academic research and in practice. We discuss ways of quantifying operational risk with a specific focus on manufacturing companies. In line with interpretations that depict the operations of a company using material, financial and information flows, we extend the idea of overlaying the three flows with risk flow to assess operational risk. We demonstrate the application of the risk flow concept by discussing a case study with a consumer goods company.We implemented the model in six phases using discrete-event and Monte Carlo simulation techniques. Results from the simulation are evaluated to show how specific parameter changes affect the level of operational risk exposure for this company. Inventory as a means of risk mitigation in the network is discussed and results are presented.
OpenAlex reports 7 citations for this work. Citation counts describe recorded attention and do not establish research quality.
A contribution statement is not available in the OpenAlex record.
Method details are not available in the OpenAlex metadata.
Findings are not separately available in the OpenAlex metadata.
Limitations are not available in the OpenAlex metadata.
Application details are not available in the OpenAlex metadata.
ABSTRACT Operational risk has been receiving increasing attention, both in academic research and in practice. We discuss ways of quantifying operational risk with a specific focus on manufacturing companies. In line with interpretations that depict the operations of a company using material, financial and information flows, we extend the idea of overlaying the three flows with risk flow to assess operational risk. We demonstrate the application of the risk flow concept by discussing a case study with a consumer goods company.We implemented the model in six phases using discrete-event and Monte Carlo simulation techniques. Results from the simulation are evaluated to show how specific parameter changes affect the level of operational risk exposure for this company. Inventory as a means of risk mitigation in the network is discussed and results are presented.
Key concepts: Operational risk, Risk analysis (engineering), Risk management, Computer science, Risk assessment, Operational risk management, Operations research, Business