Key determinants of deposits volume using CAMEL rating system: The case of Saudi banks

被引:13
作者
Al-Najjar, Dania [1 ]
Assous, Hamzeh F. [1 ]
机构
[1] King Faisal Univ, Sch Business, Finance Dept, Al Hufuf, Saudi Arabia
关键词
ASSET QUALITY;
D O I
10.1371/journal.pone.0261184
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
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.
引用
收藏
页数:15
相关论文
共 71 条
[1]   Asset quality, non-interest income, and bank profitability: Evidence from Indian banks [J].
Ahamed, M. Mostak .
ECONOMIC MODELLING, 2017, 63 :1-14
[2]  
Ajayi Samuel Olatayo., 2019, Research Journal of Finance and Accounting, V10, P84
[3]  
Akber S.M., 2020, INT J ISLAMIC BANKIN, V4, P1, DOI [10.46281/ijibfr.v4i2.640, DOI 10.46281/IJIBFR.V4I2.640]
[4]   Determinates of Islamic banks liquidity [J].
Al-Harbi, Ahmad .
JOURNAL OF ISLAMIC ACCOUNTING AND BUSINESS RESEARCH, 2020, 11 (08) :1619-1632
[5]  
Alyousfi A.Y. H. S., 2017, International Journal of Economics and Financial Issues, V07, P477
[6]  
[Anonymous], 2009, LEBANON DETERMINANTS
[7]  
Anwar J, 2017, ACCOUNTING J BINANIA, V2, P23
[8]  
Aprilia J., 2018, J. Adm. Bisnis, V61, P172
[9]   Do banks change their liquidity ratios based on network characteristics? [J].
Ardekani, Aref Mahdavi ;
Distinguin, Isabelle ;
Tarazi, Amine .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2020, 285 (02) :789-803
[10]   Banks' Financial Reporting Frequency and Asset Quality [J].
Balakrishnan, Karthik ;
Ertan, Aytekin .
ACCOUNTING REVIEW, 2018, 93 (03) :1-24