TheSaudi Arabian Banks

Banksare considered to be the most critical part of the financial system.Therefore, they contribute a lot to the growth of a given economy(Almazari & Alumani, 2012). If there is a problem with thebanking industry, the economy also will experience a huge problem.Moreover, a banking system that has efficient systems have soundreflections of intermediate processes that lead to greatcontributions towards the growth of the economy (Bhuian,2007).Additionally, the efficient functioning of the commercial banksresults into effective monetary policies. The analysis of theefficiency of the profitability is also an essential factor forevaluating the performance of a given bank (Akhevein, 2013). Toestimate the performance and efficiency of different banks, we haveto apply different methods of analysis such as regression analysis.Furthermore, analysis of the financial indicators is the commonlyused method by the banks (Akhavein, 2013). However, at some time, thefinancial indicators might sometimes be big and make theinterpretation of the result to be difficult.

Inspite of the existence of the financial studies of the banks, theliterature study of the financial performances of Saudi Banking doesnot exist (Akhavein, 2013). Therefore, there is the need for greatwork to study the financial performance of the Saudi Arabia banks(Akhavein, 2013). Moreover, the study of the financial performance ofthe Saudi Arabia banks is also important to the various groups ofpeople that have interests in banking. An example of such groupincludes the central bank of Saudi Arabia, the community of the SaudiArabia, Academicians, and the Saudi Arabia government at large(Almazari & Alumani, 2012). Therefore, the important of my studyis to address the important issue regarding the financial performanceof the Saudi Arabia banks. The paper is organized in such that itwill concentrate on the regression analysis the banks performance.The analysis will also involve the measure of the banksâ€™profitability efficiencies. Therefore, the method of the measure willrequire the use of ROA (return on assets). During the analysis, theoperating income-size of the bank will be used as the dependentvariable while the size of the bank assets, utility management, andoperational efficiency will be used as independent variables(Akhavein, 2013). The number of the Saudi Arabia banks that will beasses is five. The assessment will be carried on the banks for thefinancial period of (2006 to 2014). Besides, the selected banks forthe analysis will be carried quantitatively so as to find thedifference based on their level of performance (Akhavein, 2013). Forthe record, the Saudi Arabia banks are ranked according to theirfinancial efficiency (Akhavein, 2013). Furthermore, the study isimportant in that it also concentrate on the importance of the SaudiArabia banking system to the economy.

Also,the study is anticipated to concentrate on two folds, that is, whatare the relevant contribution of the management decisions to theperformance of the banking system and how the performance of theSaudi Arabia banks have contributed to the academic field (Almazari &Alumani, 2012). However, the paper will mainly concentrate on themanagement will it comes to the field of banking. Therefore, it mighthelp decision makers with attentions regarding the major activitiesthat are associated with banking (Akhavein, 2013). Furthermore, themanagement team will learn how to improve the positioning and theranking of a given bank as compared to its competing banks. Besides,the financial information that will be gathered in this study will beuseful to bank managers when it comes to the aspect of setting upfinancial strategies and plans (Ruppert, 2011). __Thenull hypothesis that will to be tested in this paper is checkingwhether there has been any increase in efficiency of financialsystems in Saudi Arabia from 2006 to 2010 using of regressionanalysis method. To achieve such, testing the relationship betweenthe average net income and average assets will be essential part ofthis regression analysis.__

LiteratureReview

TheRecent investigation regarding the performance of banks Saudi Arabiabanks has been done by a number of people. For example, Al-Faraj didsue data envelopment approach (DEA) to evaluate the technicalefficiency of the Saudi Arabia banks in the year 2002 (Almazari &Alumani, 2012). He eventually compares his result with the worldscores of the mean efficiency. Al-Faraj and his fellow scholars(2006), recommend that the banking industry in Saudi Arabia shouldcontinue with their effort of adapting new technologies. As a result,they will be able to provide sustainable services to their customersand at the same time making them have favorable conditions in thecompetitive market (Almazari & Alumani, 2012).

__Furthermore,according to __Almazari&Alumani __(2012),financial system in Islamic are 30 years old and is part of bankingsystem. Some banks in Saudi Arabia such as Islamic banking areprofit-loss sharing or interest-free banking. Due to this, during1980s, banks in Saudi Arabia experienced rapid growth in efficiencyin financial institutions. However, little has been done to prove howthat relate to increasing net income in the country. __

__Accordingto Whitely and Kaynak (1999), customers â€˜attitude to conformistfinancial services and products encourage bankâ€™s efficiency.Convenient of bank was listed as the primary customersâ€™ motivationin selecting a particular bank. However, according to Marlowe and Lee(1996) reputation of back is most important in growth and developmentof any financial institution as it determines customersâ€™ motivation__(Bhuian,2007)__.The assume both research did was that if the customers are motivatedto join a certain bank, its efficiency will automatically rise due toincreased cash flow assets. However, the issue of average net incomeand average assets was ignored totally leading to need of includingsuch in entire calculation of banking efficiency. Regression analysisis essential in this determination. __

__Researchdone by __Ruppert(2011), __provedthat core concept of Saudi Arabia banking to provide services totheir customers is giving and giving interest, and interest- freeloans not allowed in all transactions. This interest prohibitionmakes Saudi Arabia banking system unique. In simple term use of moneyis the difference between Saudi Arabia and conventional banks.Conventional banks are known to use their money as commodity that canbe bought and sold with interest __(Akhavein,2013)__.However, this raises interest mechanism alternatives adopted by SaudiArabia system. Furthermore, a question of how Saudi Arabia banksworks if they are prohibited from trade on interest rate. Use ofregression analysis tries to answer this question using average cashincome and average asset. __

Accordingto the research that was done by Akhevein (2013), it is true thatthere is the significant and positive relationship between theprofitability and the size of the bank. In that case, the large sizeof scale can result in economy of scale which in turn will reduce thecost of gathering information (Akhavein, 2013). Besides, few costsaving can result into the increasing of the size of the bank.However, the size of the bank can have some positive impact to somelimits. Beyond those limits, the resulting impacts are more ofnegative than being positive ((Bhuian,2007).In that case, the relationship between profitability and the size ofthe bank has a lot of uncertainty, which are contributed by differentfactors.

BasicExplanation of Regression Analysis

Regressionanalysis is defined as a statistical tool that is used in theinvestigation of the relationship variables (Almazari & Alumani,2012). The variables might be independent or dependent (Akhavein,2013). In the most occasion, the investigator is mostly concern withthe causal effect that one variable has to another. This may includethe effect of increasing the price of a given product that is ondemand or the effect of changing the chain of money supply in case ofthe inflation rate (Ruppert, 2011). Therefore, such issues can bebest investigated by using regression analysis. The method helps withthe estimation of the measurable effect the given casual variables tothe variables that they may have the influence on. Consequently, thetechnique of the regression analysis has become important when itcomes to the aspect of economic analysis (Akhavein, 2013). In mostoccasions it founds it application in the analysis of the performanceefficiencies of the banking industry.

Overviewof the Banking System in Saudi Arabia

Accordingto the current trend in the banking market, Saudi Arabia is thecurrently worldâ€™s fastest growing market for the banking business(Almazari & Alumani, 2012). The national banks are also facingstiff competition from the current banking market and are expected tomake improvements regarding technological advancement (Akhavein,2013). The government is also expected to employ favorable policiesregarding the banking business. The Saudi Arabian banking industryhas also been registering positive growth in the banking businesseven during the global financial crisis. They have even continued toexpand their lending activities.

Moreover,their lending activities are in the inclusion of small businessenterprises, households, and non-financial organizations (Almazari &Alumani, 2012). The banking system in the Kingdom of Saudi Arabia ismostly dominated by the private sector. The private sector accountsfor the bulk in the extension of their credit and the bulk in thedeposit received by the bank (Akhavein, 2013). According to theCentral Bank of Saudi Arabia, the bank lending had reached SR891.6billion towards the end of November 2011 (Lòˆchel & Li, 2011).It was 15 % more than the lending that was registered in a yearearlier (Lòˆchel & Li, 2011). The positive momentum was greatlygenerated by the rise in giving credit to private sectors. Accordingto Lòˆchel & Li, (2011), in November 2011, the loan extends toprivate sectors had reached SR859.4 bn. The total growth of the SaudiArabia regarding assets had reached 13.6 % between 2007 and2014(Bhuian,2007).

Moreover,the banking systems of Saudi Arabia are considered to be one of thesafest in the world, that is, according to the information on theglobal assessment that was published by the Poorâ€™s and Standards.For example, the Gulf Kingdom bank was given a rating of 2 (Faraj *etal.,*2006). It implies that the bank was upgraded from a rating of 3,therefore, making it the bank that has low risk in the Middle East(Akhavein, 2013).

Methodology

Toachieve the objective of the analysis, many of the data was gatheredfrom the secondary sources such as the financial statements of banks,that is, between the year 2006 and 2010. The data were very importantwhen it come to the aspect of computing the financial ratios of a fewSaudi Arabian Banks (Almazari & Alumani, 2012). The informationwas also useful in investigating the rate of performance. Moreover,some of the data were gathered from papers, articles, books, the web,and specialized international journals. The study appears to bedescriptive as it measures, describes, and compare the financialsituations of different banks.

Thestudy mainly concentrates on major banking activities that arecomprised of net income, total assets, operating income, operationalefficiency, return on assets, asset management, operating expenses(Ruppert, 2011). The study will also explore on the variance that canresult from different variables. Therefore, it was imperative to usedregression analysis as one of the methods.ss

SaudiArabia Banks

Period | The National Commercial Bank | Riyadh Bank | Banque Saudi Fransi | The Arab National Bank | Saudi British Bank | Bank Al-Jazira | Saudi Hollandi Bank | Saudi Invest-ment Bank | Al-Rajhi Bank | Samba Financial Group | Gulf Inter-national Bank | Emirates NBD | Bank Albilad | BNP Paribas | National Bank of Kuwait | Deutsche Bank | Bank Muscat | National Bank of Bahrain | J.P Morgan Chase N.A Bank | Alinma Bank | National Bank of Pakistan | T. C. Ziraat Bankasi .A. S | State Bankof India | |

2000 |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

2001 |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

2002 |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

2003 |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

2004 |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

2005 |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

2006 |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

2007 |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

2008 |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

2009 |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

2010 |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

2011 |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

2012 |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

2013 |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

2014 |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |

Annualstatistics report

S |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | ||

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | OCTOBER 2008 | |

  |   | Money , Banking Statistics And Insurance |   |   |   | Share Market Statistics |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | JANUARY 2008 | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | MARCH 2008 | |

  |   | Investment Fund Statistics |
|   |   | Government Specialized Credit Institutions |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | APRIL 2008 | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | JUNE 2008 | |

  |   | Public Finance Statistics |   |   |   | Prices And Cost Of Living Index |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | JULY 2008 | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | SEPTEMBER 2008 | |

  |   | Foreign Trade Statistics |   |   |   | Balance of Payment Statistics & International Investment Position |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | OCTOBER 2008 | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | DECEMBER 2007 | |

  |   | National Account Statistics |   |   |   | Oil Statistics |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

  |   | Other Miscellaneous Statistics |   |   |   | Annual Balance Sheet Of SAMA |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

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  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

  |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   |   | |

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Analysisof the Results

Fromthe tables and the regression analysis, it is clear that the netincome of all of the banks was negative. Moreover, in the year 2010Riyadh Bank registered a negative growth rate of -2.9% (Ruppert,2011). Similarly, Bank Aljazira registered the lowest growth rate of-96.9 it was the lowest among all of the banks (Ruppert, 2011).According to the table of the total operating income, all of thebanks registered high values apart from the BJ bank. Comparing thebanks concerning the growth of total expenses Saudi Investment Bankdid register the highest value as compared to the other banks. It hada percentage growth rate of 155.3% (Faraj *etal.,*2006). On the other hand, Bank Aljazira still maintained the lowestregistration.

ROA(Return on Assets) is defined as the financial ratio that measuresthe relationship between earnings or profits and the total assets(Ruppert, 2011). Furthermore, it assesses the performance of theprofitable of the total asset of the bank. And according to thisstudy, it was treated as the measure of the financial performances ofbanks. From the table and regression analysis, it is observed thatthe ROA contain two elements which are effectiveness and efficiency(Almazari & Alumani, 2012). Effectiveness can also be referred toas profit margin while efficiency can be referred to as total assetsturnover. The table of ROA reflects on the management ability ofbanks. It implies that their ability to generate more income profitswith the available assets. According to the table analysis, BJ bankwas the best with a percentage of 3.5% (Ruppert, 2011). It impliesthat the management team of the bank had the ability to use theavailable resources to generate profits.

RegressionModel

Theregression model of the study is as follows:

Y=B_0+B (1 ) X_1+B_2 X_2+B_3 X_3+B_4 X_4+B_5 X_5+B_6 X_6+B_7 X_7+u

Where,Y is the dependent variable, ROA is the return on asset while ROE isreturn on Equity (Akhavein, 2013). The independent variables arerepresented by (X).

X1=Capital adequacy.

X2=Inflation

X3= Deposit

X4= Earning Quality

X5=Macroeconomic variable

X6= Size of the bank

X7=Loan

B0to B7 are the coefficient of the independent variables.

Explanationsof the tables in Excel

Accordingto Vinod & Ullah (2011), excel tables need to be representedusing different sheets. Moreover, these tables were explained usingsuch model with sheets from 1-10. The table in sheet 1 representaverage asset of each bank versus the average net income of eachbank. Sheet 2 represent the output of the regression analysis of theaverage asset versus the average net income of each bank. Sheet 3represent the table of average operating income versus averageexpenses. Sheet 4 represent the output of the regression analysis ofthe average operating of each bank versus the average expenses ofeach bank. Sheet 5 represent the table of the average assets, averagenet income, average operating income, average operating expenses,ROA, management efficiency ratio, and assets management ratio of eachbank. Sheet 7 and 8 are the same. The difference is that sheet 8shows the residual output of the analysis in terms of graph. Theyboth represent the regression analysis of the ROA and assetsmanagement ratio. Sheet 10 represent the sum of X, which are theindependent variables according to the model. The sum of thevariables includes average assets, average net income, averageoperating income, and, average operating expenses. However, from thedata there was no ROE so the regression analysis was done using thesum of X versus the ROA (Bhuian,2007).

Explanationof the Excel Results

Accordingto excel, the regression analysis was done on between two variables.The first set of the regression analysis was based on average assetsand average net income. In this case, the average assets of each bankwere used as the independent variables while the average net incomewas being used as the dependent variables.

Regressionanalysis of the model was done in parts depending on the availabledata (Vinod & Ullah, 2011). In that case, the ROA was taken to bepart of the dependent variable. Since there was data relating to ROE,its values were considered to be zero. The independent variables (X)were represented by the sum of the average income, average assets,average net income, and average operating (Bhuian,2007).According to the result of the excel while using average operatingincome as the independent variable and the average expenses for eachbank as the dependent variable, the correlation is significant at the0.05 level (2-tailed). R-square is equal to 0.978187 (Bhuian,2007).The value of F is at 89 is 68966 while the significance of F is at0.010966, t-start at the intercept is 0.157371 and P-value is0.889405 (Bhuian,2007).Other elements such as mean square, regression, sum of square,regression factor F, and significance are summarized in the ANOVAtable (Bhuian,2007).

Conclusion

Inconclusion, the regression analysis and table analysis of thecollected data shows that Saudi Arabia is the fastest growing marketfor banking business. The banks are operating in an environment thatappears to be very competitive. Therefore, the analysis predicts thatSaudi Arabia will be a more efficient place for the future bankingbusiness. Banks have also proven to be the most critical part of afinancial system. They play important roles when it comes to theeconomic growth of a given nation. Therefore, the paper focuses onthe banking business as one of the critical parts of an economy.

Basedon the regression analysis and table analysis, it does not imply thatbank with a lot of assets will always have good profitabilityperformance. The regression analysis also shows that there exist ahuge impact on assets management, operational efficiency, and thetotal size of the bank on the efficiency of profitability. From theregression analysis, it was observed that some of the independent donot affect the efficiency of profitability. Moreover, the informationregarding this analysis is also relevant to bank managers. They canuse the information to improve their management policies. As aresult, effective financial system is available in Saudi Arabia.

References:

Akhavein,J. D. (2013). Finance and economics discussion series: The effects ofmegamergers on efficiency and prices. Place of publication notidentified: Bibliogov.

Almazari,A., & Alumani, M. (2012). Measuring Profitability Efficiency ofSaudi National Banks. Retrieve from:__http://www.ijbssnet.com/jornals/Vpl_3No_14_Special_Issue_July2012/19.pdf__

Faraj,T. N. A., Bshait, K. A. B., & Muhammad, W. A. A. (January 01,2006). Evaluating the efficiency of Saudi commercial banks using datadevelopment analysis. International Journal of Financial ServicesManagement, 1, 4, 466

Lòˆchel,H., & Li, H. X. (2011). Understanding the high profitability ofChinese banks. Frankfurt, M: Frankfurt School of Finance &Management.

Ruppert,D. (2011). Statistics and data analysis for financial engineering.New York: Springer.

Vinod,H. D., & Ullah, A. (2011). Recent advances in regression methods.New York: M. Dekker.

Bhuian,S. N. (2007). Exploring market orientation in banks: an empiricalexamination in Saudi Arabia. *Journalof Services Marketing*, *11*(5),317-328.