Qualitative Analysis of Operational Risks – A Step-by-Step Approach

The consequences of global crisis have prompted preferred attention towards strengthening of qualitative-based analysis approaches such as key risk indicators (KRIs)/risk control and self assessment (RCSA).The paper concentrates on a quantitative analysis approach that can be applied to operational risk qualitative data. A major objective of the paper is to demonstrate how qualitative information gathered during the process can be analysed to provide conclusions that are applicable to the stakeholder, higher management and other targeted segments. Quantitative loss of data fails to capture various operational risk factors and their potential impact. We propose in our study a model framework to assess and measure operational risks through analysis of qualitative factors in a treasury and investment business line of a bank/financial institution (FI) in India.We develop our model on a few main strands. We start with putting RCSA/KRIs-based participators' observations into mathematical footing to identify and specify degree and severity of risk level. We delineate the process for calibrating the data, estimating frequency deviations and specifying instances of deviations for segregation. We define frequency consequences, impact of likelihood range (probability rating), risk level, degree of risk severity, and also suggest risk mitigation steps.This paper shows how operational risk qualitative factors can be addressed quantitatively and risk management information can be presented in a clear and unambiguous fashion