¶ … merger outcomes in Malaysian banking sectors include input and output variables. The inputs used in the study of the financial sector include operating and interest expenses. The operating expenses are expenses incurred in the management of a bank's daily operations including personal costs, establishment costs, marketing expenses, and general as well as administrative expenses. Banks' establishment costs are expenses pooled towards payment of premises rents, maintenance as well as repair of expenses as well as depreciation costs. Banks personnel costs are expenses incurred in the regular activities and daily banking duties that include employees' wages and salaries. The operating expenses usually reflect a bank's efficiency in daily management of resources. The variance of the cost of personnel directly affect the operating expenses, which is an indicator of banks efficiency or inefficiency in management and control of operating costs (Bank Negara Malaysia ).
In addition, interest expense variables are the cost these Malaysian banks incur towards the servicing of loans or borrowed money. This variable encompasses deposits from clients and other subsidiary financial establishments as well as loans, bonds and notes sold to the public. The documentation of interest paid out relating to revenue and earnings enable the banks focus on ways to increase revenue and pretax earnings.
Output variables on the other hand include non-interest incomes, net interest income and the sum of loans and advance payments issued out by a bank to creditors and employees. The net interest accrued by the banks is the difference between the interests the banks get from loans issued to customers and the interest the banks pay to account holders. Higher interest rates imposed by the banks push the net interest variable higher and are the main driver for business growth of the banks. The outcomes of the interest rates stabilize the earnings of the banks and increase performance and profitability. The increases or decrease of the net interest income may reflect changes in the volume of the financial institutions interest earning assets.
The non-interest income variables include revenue sourced from sundry services; deposit service charges as well as fiduciary fees charged the banks. The non-interest income is important in calculation of the banks' revenue earnings and risk management strategies. Most of the Malaysian banks' income is majorly from fiduciary fees and non-interest incomes. Increases in the country's inflation levels call for controlling and close monitoring of the non-interest income.
Nonetheless, output variable necessary is the total amount of loans and advances issued by the Malaysian financial institutions. The total loans and advance payments to clients and employees such as bank overdrafts, term loan, and receivable bank bills and customer claims regarding acceptance credits are the constituents of this variable. This variable is necessary in the measurements of revenue levels of the financial institutions.
Theoretical Model Review
Abd-Kadir, Hazlina, Zarehan Selamat and Muzlifah Idros in their publication, Productivity of Malaysian Banks after Mergers and Acquisition appearing in the European Journal of Economics, Finance and Administrative Sciences, 2010: studied the mergers of Malaysian banks. These banks included Hong Leong Bank Berhad, Arab Malaysian Bank Berhad, Maybank, Bumiputra Commerce, RHB Bank, Multi-Purpose Bank, Southern Bank, EON Bank, and Public Bank. The theoretical model for the study was accessed via the banks' published balance sheets in their annual records.
Abd-Kadir, et al., (2010) incorporated a non-parametric method, Data Envelopment Analysis (DEA) in measuring the efficiency of the Malaysian banks in the study. This method allows for the disintegration of the efficiency and productivity differences into a single unit that represents the banks' competence and output levels as opposed to their close rivals in the banking industry.
Abd-Kadir, Habibullah and Radam (2005), agree that this model is the most beneficial for the Malaysian-banking sector in reducing costs in recent times. In addition, the DEA allow the study...
The data envelopment analysis is not demanding works best with small sample size and requires no knowledge of proper inefficiency structures during the study of the Malaysian banks. Though the study involves all the Malaysian banking institutions, the relatively small study group involved makes the adoption of the DEA in the study beneficial.
The method illustrates that the higher the output produced from the pre-mentioned inputs, the more proficient the banks' production levels. The efficiency ratios are determined by a restriction that related ratios for every Decision Making Units (DMUs) must be less or equal. The DEA allows for multiple outputs and inputs without necessarily having pre-approximated weights. From this study the theoretical DEA incorporated DMUs of various outline to estimate the performance of the ten banks in the study within Malaysia. Hence, the Data Envelopment Analysis (DEA) proves to be the best method in the measurement of the banks' productivity levels within the study.
The Banks Revenue and Losses after Merging
The average productivity changes across the top 10 banks in Malaysia has increased by 11.1% annually, realized as from the period of the year 2003 to 2009 .Averagely, methodological effectiveness seems to be waning by 6% over this study epoch. This is gauzed to be as a result of less competent bank management. In spite of this, there is technological improvement made on average with 17.1% growth after the Merger and Acquisition (Kumar, Fong and Charles).
The productivity has only been realized for six out of ten of the banks analyzed. The banks with the productivity after acquisition and merger are as follows: Alliance Bank, Am Bank, CIMB, EON Bank, Public Bank and RHB. Explicitly, the bank with the most increase in total aspect output is Am Bank with the growth of 55.5%. This 55.5% increase is grounded on the technical efficiency change which is approximated to be 0.975% of technological change. The general competence change of Am Bank is built on 13.7% of pure technical efficiency and 40.2% on scale efficiency. The bank that had the most declines in total factor productivity for the period of year 2003 to 2009 is Hong Leong Bank with the depreciation of 21.7%. The decrease of total factor productivity of Hong Leong Bank can be held responsible on the loss of technical efficiency of 42.2% and even an increase of 35.3% in technological change which could not make up for the loss, and along this lines the decrease in total factor output realized.
Conversely, seven banks have witnessed an improvement in the technological transformation, with the exemption of two banks, that encountered a decrease in technological change, which have been pointed out to be Am Bank and Maybank, with a falling off of 2.5% and 8.1%, correspondingly. In general, the technical effectiveness of banks grew up in only three away from ten banks while five banks dropped in percentage and two banks, probably Alliance Bank and Public Bank, remained constant without any progress or depreciation. This may necessitate premeditated decisions for the banks sector to progress effectively. The genuine technical efficiency stayed put for four banks, thus it can be fulfilled that these four banks; CIMB, EON Bank, Maybank and Public Bank, have merely scale efficiency adjustment that influence the improvements of revenue on individual bank.
As Sufian states that the indices are computed by putting into comparison the data generated after every twelfth month, as a result of the first output that was only present against year 2004 as a substitute of year 2003. Over the five-year period, the results show that there was a mean yearly increase of 10.1% as totality factor productivity. Ultimately, 10.1% appreciation is good and rather small figure, entailing the productivity across top 10 banks which is fairly the same and there is no too big difference of productivity. This might be a result of keen competitive tension faced by these banks during this period of analysis. This increase of 10.1% in productivity is solely caused by an increase in technological progress of…
