V. Sree Hari Rao and K.V.N.M. Ramesh

Foundation for Scientific Research and Technological Innovation Hyderabad - 500102, India

J. Innovation Sciences and Sustainable Technologies, 1(1)(2021), 3-19.

Received in final form on November 21, 2020

Abstract
Information Technology (IT) plays a very important role in revolutionizing the legacy way of managing various operations that a financial institution performs and one such area is measurement of various risks to which a financial institution is exposed. The Basel committee for banking supervision provides guidelines for measuring operational risk capital using the Basic Indicator Approach (BIA), Standardised Approach (SA), usually referred to as TSA, Advanced Measurement Approach (AMA) and Standardised Measurement Approach (SMA). We notice that the same operational risk event can lead to a variety of different kinds of losses of varying magnitudes that may fall in different severity categories. This behaviour prompts us to associate a fuzzy membership to the loss severity occurring due to an operational risk event. The study presents a generic framework that uses fuzzy logic methodology to quantify the severity of losses arising due to failure of internal controls and the frequency of their failures based on the historical loss data. The presented methodology can also incorporate expert judgement to generate hypothetical loss records wherever the data is sparse. Scenarios are generated for various states of the controls which are used in conjunction with the severity memberships to determine various measures for operational risk losses.

Keywords
Operational Risk Exposure; Quantification; Fuzzy Framework.

Cite This Article
V. Sree Hari Rao and K.V.N.M. Ramesh, Fuzzy Methodology for Quantifying Operational Risk Exposure of Financial Institutions, J. Innovation Sciences and Sustainable Technologies, 1(1) (2021), 3-19. https://doie.org/10.0603/JISST.2022634688

    561    162    Download