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Predictive modeling for non-performing assets in the indian banking sector

Suresh B Pathare & Mohneet Sandhu

Journal of Statistical Research2025https://doi.org/10.3329/jsr.v58i2.80616article
ABDC C
Weight
0.50

What the paper says

This paper explores the financial and operational factors that contribute to India’s Nonperforming Assets (NPA) problem and discusses practical solutions for mitigating the risk of future NPAs. Descriptive statistics, regression analysis, and time series analysis are used to identify the main drivers of NPAs of Indian banks, revealing that high levels of NPAs have resulted in lower profitability, increased provisioning requirements, and higher borrowing costs. The findings and recommendations of this study provide valuable insights for policymakers, regulators, and banking practitioners seeking to reduce the risk of NPAs in India. Journal of Statistical Research 2024, Vol. 58, No. 2, pp. 335-351

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https://doi.org/https://doi.org/10.3329/jsr.v58i2.80616

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@article{suresh2025,
  title        = {{Predictive modeling for non-performing assets in the indian banking sector}},
  author       = {Suresh B Pathare & Mohneet Sandhu},
  journal      = {Journal of Statistical Research},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.3329/jsr.v58i2.80616},
}

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Predictive modeling for non-performing assets in the indian banking sector

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.