Assessing Reputational Risk in Commercial Banks: A Bayesian and Fuzzy Approach with Evidence from Indonesia

Adi Pranat

doi:10.36690/2674-5216-2026-1-87-96

Authors

Adi Pranat Muhammadiyah University Purwokerto

DOI:

https://doi.org/10.36690/2674-5216-2026-1-87-96

Keywords:

reputational risk, commercial banks, Bayesian networks, fuzzy data analysis, Monte Carlo simulation, Indonesia, risk management

Abstract

In the context of growing financial uncertainty, effective risk management has become essential for sustaining stability and public confidence in the banking sector. Among different types of risks, reputational risk is particularly important because it can influence customer trust, stakeholder confidence, and the overall financial performance of commercial banks. In emerging economies such as Indonesia, where the banking sector plays a central role in economic development, the assessment and management of reputational risk require more comprehensive and context-specific analytical approaches. The aim of this study is to develop an integrated framework to assess reputational risk in Indonesian commercial banks under the regulatory environment shaped by Basel II and Basel III. The proposed approach combines Bayesian Networks, fuzzy data analysis, and Monte Carlo simulation to estimate the probability and potential impact of reputation-related losses. To improve data treatment and standardization, the study applies the Hamming distance method, while an Ordered Weighted Averaging (OWA) operator is used to aggregate multiple risk indicators within a hierarchical structure. The model incorporates several key financial and operational factors, including return on equity, goodwill value, risk asset ratio, productive assets, funding ratio, and credit risk exposure. The findings suggest that the proposed framework provides a useful tool for identifying, measuring, and managing reputational risk in commercial banks. The study offers practical implications for bank managers and policymakers seeking to strengthen decision-making processes and enhance the effectiveness of risk management systems in Indonesia’s banking industry. The study confirms the usefulness of an integrated Bayesian and fuzzy approach for reputational risk assessment in banking. Further research may extend this framework by applying it to other countries, comparing banking systems, and incorporating additional indicators of reputational vulnerability.

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Author Biography

Adi Pranat, Muhammadiyah University Purwokerto

Universitas Muhammadiyah Purwokerto, Purwokerto, Central Java

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