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A study on bank branch management evaluation models using statistical methods
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DOI：10.29220/CSAM.2025.32.6.773.png)
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Abstract
En 中文
This study aims to develop an objective performance evaluation model for bank branches, ensuring that branch-level efforts to improve evaluation scores are effectively aligned with profitability enhancement. In contrast to conventional evaluation systems, which often incorporate various internal and external policy factors, the proposed model emphasizes quantitative analysis based on statistical methods. Drawing on the CAMELS framework established by U.S. financial supervisory authorities and the Early Warning System (EWS) employed by the Financial Supervisory Service (FSS) of Korea, this study applies t-tests and Principal Component Analysis (PCA) to select key financial indicators and determine their respective weights. The evaluation model consists of 12 indicators across four key areas: Earnings, Productivity, Asset Quality, and Customer Relationship. The final performance results are classified into 15 rating grades based on the calculated weights. This quantitative approach provides a more accurate and objective assessment of branch management performance. However, the effective implementation of the model requires continuous monitoring and sustained, organization-wide efforts.
Keywords:
Management evaluation
CAMEL
statistical CAEL
principal component analysis (PCA)
Journal
C
IF:
0.6
Papers:
30
Citations:
0