An Integrated Total Interpretive Structural Modeling and MICMAC Model for Uncovering the Determinants of Non-Performing Assets in the Indian Banking Industry
Authors
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Fariya Akbar Ansari
Research Scholar, Department of Management, School of Management and Business Studies (SMBS), Jamia Hamdard, New Delhi - 110 062
https://orcid.org/0009-0004-3737-2817
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Vardah Saghir
Assistant Professor (Corresponding Author), Department of Management, School of Management and Business Studies (SMBS), Jamia Hamdard, New Delhi - 110 062
https://orcid.org/0000-0002-6318-5052
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Syed Nadimul Haque
Professor, Department of Management, School of Management and Business Studies (SMBS), Jamia Hamdard, New Delhi - 110 062
https://orcid.org/0000-0002-2695-5062
DOI:
https://doi.org/10.17010/ijf/2025/v19i10/174469Keywords:
total interpretive structural modeling (TISM), non-performing assets (NPA), NPA determinants, Indian banking industry.JEL Classification Codes : G2, G21
Publication Chronology: Paper Submission Date : September 25, 2024 ; Paper sent back for Revision : March 31, 2025 ; Paper Acceptance Date : July 10, 2025 ; Paper Published Online : October 15, 2025
Abstract
Purpose : The purpose of rising non-performing assets (NPAs) in the Indian banking sector poses a significant challenge that impacts the sector’s growth and performance. This can be attributed to various factors, including borrowers’ low earnings, priority sector lending, relaxed lending norms for corporate houses, credit default by companies, recessionary tendency in the economy, capitalism and poor credit culture, among others.
Design/Methodology/Approach : The determinants have been comprehensively analyzed using total interpretive structural modeling (TISM). In addition to this, the cross-impact matrix multiplication applied to the classification (MICMAC) model has been developed to ascertain each determinant’s driving-dependence power.
Findings : The present analysis revealed that “Credit default by companies” had the greatest driving power. This factor is considered the most significant determinant of NPAs in the banking industry. This is followed by “Poor credit culture,” which has an unfavorable effect on the bank’s asset quality. Further, “Recessionary tendency in the economy” and “Capitalism” affect all other factors.
Practical Implications : The findings of the present study would definitely provide a better understanding to financial analysts and policymakers in understanding the key factors associated with NPA and thus preventing the healthy assets from being converted into NPAs. The prioritized determinants need to be focused on to develop a sustainable banking industry.
Originality/Value : The study analyzed the interrelation and relative ranks of the determinants behind the growing NPAs in the Indian banking system using the TISM approach and MICMAC analysis.
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