Reputational risk management in conditions of credibility gap in the banking system

Abstract

Purpose

This paper aims to provide appropriate and effective methods for diagnosing and managing the reputational risk of a bank.

Design/methodology/approach

Using the data-mining system CONFOR, the authors have defined and arranged in the objective way the factors influencing the reputational risk level of a bank, with specific factor groups assigned. The mathematical tools of the theory of graphs and cognitive mapping are used for building the cognitive map of reputational risk assessment of a bank. To enable choosing which risk management strategies to use, the methods of impulse modeling and scenario analysis are applied for the purpose of prognostication.

Findings

The authors proposed an integrated approach to the objective determination of the reputational risk level and an easy-to-use choice of risk management scenarios considering all components of management decision making and the main managerial functions.

Practical implications

The range of tools proposed can be used as a simple measure of the bank's reputational risk level, as a component of risk management model, and as a strategic risk management tool. Implementing this approach at the level of the central bank will facilitate realization of its strategic program for restoring confidence in the banking system as a whole.

Originality/value

A relatively greater objectivity in the reputational risk assessment of the bank was achieved, with each stage formalized and confirmed by an economic and mathematical basis, risk parameters quantified. The authors have developed a comprehensive approach to the reputational risk level assessment (the integral assessment included) as well as the management algorithm.

Citation

Trostianska, K. and Semencha, I. (2020), "Reputational risk management in conditions of credibility gap in the banking system", Journal of Financial Economic Policy, Vol. 12 No. 3, pp. 327-343. https://doi.org/10.1108/JFEP-03-2019-0063