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Key determinants of deposits volume using CAMEL rating system: The case of Saudi banks
by
Assous, Hamzeh F.
, AL-Najjar, Dania
in
Bank deposits
/ Banking
/ Banking industry
/ Bankruptcy
/ Banks
/ Banks (Finance)
/ Biology and Life Sciences
/ Capital Financing - economics
/ Capital Financing - standards
/ Central banks
/ Composite materials
/ Dependent variables
/ Deposits
/ Earnings
/ Ecology and Environmental Sciences
/ Economic growth
/ Efficiency
/ Engineering and Technology
/ Financial institutions
/ Financial Management
/ Financial performance
/ Humans
/ Independent variables
/ Innovations
/ Investigations
/ Investments - economics
/ Islamic financing
/ Liquidity
/ Literature reviews
/ Loans
/ Management
/ Nonperforming loans
/ People and Places
/ Product development
/ Profitability
/ Profits
/ Ranking
/ Ratings
/ Regression models
/ Researchers
/ Saudi Arabia
/ Social Sciences
/ Standard error
/ Statistics
/ Supervision
2021
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Key determinants of deposits volume using CAMEL rating system: The case of Saudi banks
by
Assous, Hamzeh F.
, AL-Najjar, Dania
in
Bank deposits
/ Banking
/ Banking industry
/ Bankruptcy
/ Banks
/ Banks (Finance)
/ Biology and Life Sciences
/ Capital Financing - economics
/ Capital Financing - standards
/ Central banks
/ Composite materials
/ Dependent variables
/ Deposits
/ Earnings
/ Ecology and Environmental Sciences
/ Economic growth
/ Efficiency
/ Engineering and Technology
/ Financial institutions
/ Financial Management
/ Financial performance
/ Humans
/ Independent variables
/ Innovations
/ Investigations
/ Investments - economics
/ Islamic financing
/ Liquidity
/ Literature reviews
/ Loans
/ Management
/ Nonperforming loans
/ People and Places
/ Product development
/ Profitability
/ Profits
/ Ranking
/ Ratings
/ Regression models
/ Researchers
/ Saudi Arabia
/ Social Sciences
/ Standard error
/ Statistics
/ Supervision
2021
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Key determinants of deposits volume using CAMEL rating system: The case of Saudi banks
by
Assous, Hamzeh F.
, AL-Najjar, Dania
in
Bank deposits
/ Banking
/ Banking industry
/ Bankruptcy
/ Banks
/ Banks (Finance)
/ Biology and Life Sciences
/ Capital Financing - economics
/ Capital Financing - standards
/ Central banks
/ Composite materials
/ Dependent variables
/ Deposits
/ Earnings
/ Ecology and Environmental Sciences
/ Economic growth
/ Efficiency
/ Engineering and Technology
/ Financial institutions
/ Financial Management
/ Financial performance
/ Humans
/ Independent variables
/ Innovations
/ Investigations
/ Investments - economics
/ Islamic financing
/ Liquidity
/ Literature reviews
/ Loans
/ Management
/ Nonperforming loans
/ People and Places
/ Product development
/ Profitability
/ Profits
/ Ranking
/ Ratings
/ Regression models
/ Researchers
/ Saudi Arabia
/ Social Sciences
/ Standard error
/ Statistics
/ Supervision
2021
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Key determinants of deposits volume using CAMEL rating system: The case of Saudi banks
Journal Article
Key determinants of deposits volume using CAMEL rating system: The case of Saudi banks
2021
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Overview
CAMEL is considered one of the well-known banking rating systems used to build a proper bank ranking. In our paper, we investigate the CAMEL rating for Saudi banks, which is considered the second largest banking sector in GCC. The Saudi banking sector consists of 11 banks and is the leading sector in the Saudi stock index (TASI). In this research, we aim to determine the ranking of Saudi banks according to CAMEL composite and CAMEL overall ratings and explore the effects of these ratings on banks’ total deposits for the period from 2014 to 2018. The methodology involves four phases. In the first phase, we calculate the key financial ratios of CAMEL’s composites for each bank. In the second phase, we rank the banks from 1 to 11 to each one of CAMEL’s composites for each bank per year. In the third phase, we rank Saudi banks according to CAMEL composite and CAMEL overall. Finally, in the fourth phase, we run a regression model using CAMEL financial ratios rank as independent variable and banks’ total deposits as a dependent variable. Using the stepwise regression method, the results indicated that the best regression model has an adjusted R 2 of 73.4% and a standard error of around 0.58. The results further indicated that capital measured by CAR, management as an efficiency ratio, earning with ROE proxy, and liquidity as loans to deposits have positive effects on banks’ total deposits. Meanwhile, earnings as net interest income to net revenue and liquidity calculated by CASA have a negative effect on banks’ total deposits. Finally, asset quality ratios and the rest of the ratios have no significant effect on banks’ total deposits.
Publisher
Public Library of Science,Public Library of Science (PLoS)
Subject
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