Evaluation of banks’ commercial credit applications using the analytic hierarchy process and Grey relational analysis: A comparison between public and private banks

Ertuğ, Zeliha Kaygısız; Girginer, Nuray

doi:10.4102/sajems.v18i3.744

SAJEMS

2015

DOI: 10.4102/sajems.v18i3.744

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Evaluation of banks’ commercial credit applications using the analytic hierarchy process and Grey relational analysis: A comparison between public and private banks

Zeliha Kaygısız Ertuğ¹,

Nuray Girginer²

Abstract: The purpose of this study is to develop an evaluation model that considers the quantitative and qualitative criteria for the appropriate selection of firms demanding commercial credit for both public and private banks. In this paper, the authors propose an integrated model that combines the Analytic Hierarchy Process (AHP) and Grey Relational Analysis (GRA) into a single evaluation model. The model is illustrated with a case study on bank experts to demonstrate the effectiveness of this integrated method for f… Show more

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Cited by 6 publications

References 6 publications

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Evaluating and ranking the Indian private sector banks—A multi‐criteria decision‐making approach

Sama

Kosuri²,

Kalvakolanu³

2020

Journal of Public Affairs

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The paper examines the performance of Indian private sector banks based on various combinations of multi‐criteria decision‐making techniques. Annual reports of the respective banks were used to capture the data and measure the performance by considering multiple inputs and outputs. The data are analyzed through notable multiple criteria decision‐making (MCDM) techniques, CRITIC, TOPSIS, and grey relational analysis (GRA). The study reveals that HDFC is the best performing bank among other private sector banks and creates a benchmark. Applying the combination of MCDM techniques, namely CRITIC‐TOPSIS and CRITIC‐GRA, HDFC is ranked first followed by Bandhan Bank as the second. Other banks are ranked differently due to methodological differences. After obtaining the ranks by CRITIC‐TOPSIS and CRITIC‐GRA, the ranks are tested using the Wilcoxon signed‐rank test. Only private sector banks are considered for the current study. Future studies on the performance of banks can be taken up by comparing different types of banks, targeting an extension of the time frame studied. The findings suggest that the private sector banks need to increase their performance by investing in income‐generating areas. Improving the performance will help them in surviving in the market as well as competing with the top public sector and foreign banks. The findings can also be useful to various stakeholders and, in particular, to investors to know the value of the banks for future investments. For the first time, researchers have used a combination of MCDM techniques such as CRITIC‐TOPSIS and CRITIC‐GRA. Selected inputs and outputs have been studied for the private sector banks using MCDM techniques to measure the performance.

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Evaluating and ranking the Indian private sector banks—A multi‐criteria decision‐making approach

Sama

Kosuri²,

Kalvakolanu³

2020

Journal of Public Affairs

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A comparative study on performance measurement of Indian public sector banks using AHP-TOPSIS and AHP-grey relational analysis

Guru

Mahalik

2019

OPSEARCH

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Banks are the financial intermediaries and important means for the advancement of economies. In the cutthroat competitions, the increase in market shares is a matter of concern for all. Banks are expected to increase their efficiency to boost competitive capacity, which also helps the Decision-maker to know about grey areas for development. Therefore, performance measurements of efficiency calculation, by using different methods are the concern for research across the world. This paper tries to use the combination of AHP, TOPSIS, and Grey Relational Analysis for efficiency calculation of different public sector banks in India and finally, results were compared. AHP is used to determine the weight criteria and Grey Relational Analysis and TOPSIS are used to rank the bank performances. The proposed method of this study used various inputs and outputs criteria which were taken from various banks annual reports. Descriptive statistics and correlation matrix were used to test the validity of the criteria. The findings reveal that banks which are considered as efficient are close to relative closeness to the ideal solution, expose an alternative ranking of the banks, present research also provides better insight to focus on the area of improvement in comparison to others banks. The Comparative result shows both models have the almost same interpretation. Little deviation in their ranks is due to methodological differences. The proposed research will provide a framework for further applications and both approaches will help decision maker of Indian Public sector banks to find optimal solutions to the complex problems by assessing various alternatives.

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A credit ranking model for a parafinancial company based on the ELECTRE-III method and a multiobjective evolutionary algorithm

Chavira

Leyva-Lopez

Noriega

et al. 2017

Applied Soft Computing

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Evaluation of banks’ commercial credit applications using the analytic hierarchy process and Grey relational analysis: A comparison between public and private banks

Cited by 6 publications

References 6 publications

Evaluating and ranking the Indian private sector banks—A multi‐criteria decision‐making approach

Evaluating and ranking the Indian private sector banks—A multi‐criteria decision‐making approach

A comparative study on performance measurement of Indian public sector banks using AHP-TOPSIS and AHP-grey relational analysis

A credit ranking model for a parafinancial company based on the ELECTRE-III method and a multiobjective evolutionary algorithm

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