Is The Financial Health Of Urban Co-Operative Banks Sound? A Study Based On Altman Z-Scores

This study was initiated due to the recent bank scams in the co-operative banking sector in Kerala, which raised a need to prove the financial stability of Urban Co-operative Banks (UCBs) which are an integral part of the Indian banking sector. The financial soundness of sixteen UCBs in Kerala is assessed in this study over ten years from 2012-13 to 2021-22 using Altman Z scores, re-estimated Altman Z scores using Binary Logistic Regression (BLR) and Multilayer Perceptron Neural Network (MLPNN). BLR was used to classify banks into grey and distress zones, and MLPNN was used to identify non-linear relationships in the data. The study’s findings show that the re-estimated Altman Z score model using BLR exhibited high predictive accuracy in predicting distressed and non-distressed UCBs, therefore, it may be considered as a reliable tool for predicting financial distress in UCBs. The MLPNN model needs further improvement in the form of the inclusion of new variables which will be within the future scope of the research. The bank management and other stakeholders will be able to monitor the financial stability of UCBs with the help of the findings of the study.

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Publication Details

Journal
South India Journal of Social Sciences
Published
2024-12-31
DOI
https://doi.org/10.62656/sijss.v22i4.1197
Primary Topic
Islamic Finance and Banking Studies
Type
article
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article

Is The Financial Health Of Urban Co-Operative Banks Sound? A Study Based On Altman Z-Scores

Vankayalapati Radhika, R Resmi
South India Journal of Social Sciences
Islamic Finance and Banking Studies
article

Is The Financial Health Of Urban Co-Operative Banks Sound? A Study Based On Altman Z-Scores

Vankayalapati Radhika, R Resmi
article en

Abstract

This study was initiated due to the recent bank scams in the co-operative banking sector in Kerala, which raised a need to prove the financial stability of Urban Co-operative Banks (UCBs) which are an integral part of the Indian banking sector. The financial soundness of sixteen UCBs in Kerala is assessed in this study over ten years from 2012-13 to 2021-22 using Altman Z scores, re-estimated Altman Z scores using Binary Logistic Regression (BLR) and Multilayer Perceptron Neural Network (MLPNN). BLR was used to classify banks into grey and distress zones, and MLPNN was used to identify non-linear relationships in the data. The study’s findings show that the re-estimated Altman Z score model using BLR exhibited high predictive accuracy in predicting distressed and non-distressed UCBs, therefore, it may be considered as a reliable tool for predicting financial distress in UCBs. The MLPNN model needs further improvement in the form of the inclusion of new variables which will be within the future scope of the research. The bank management and other stakeholders will be able to monitor the financial stability of UCBs with the help of the findings of the study.

South India Journal of Social SciencesVol. 22(4)
Maharaja Engineering College (IN)
Sustainable cities and communities
Openalex Percentile: Top 57%
Islamic Finance and Banking Studies
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