Identifying Useful Measures For It Investment Finance Essay - Free Essay Example

In this section Im going to identify useful measures for IT investment and it is implication for financial performance of banks. The determination of IT investment is problematic because of lack of consensus in defining and measuring such investment. Researchers have difficulty in agreeing as to what model actually constitutes IT. Some used a narrow definition that includes only an information system while others used a broader definition that also includes data communication. Some used direct measures while others used surrogate measures. Previous researchers have used various ratios as measures of IT investment. Bender and Harris and Katz used IT expense as a percentage of total operating expenses as a measure. The Diebold group used IT budget as a percentage of revenue. A similar measure, It expense to premium income, was also used by Harris and Katz. All of those ratios have advantages and disadvantages. The population is all the LCB banks which are registered in Colombo stock exchange, and the sample will be five banks in that population. It includes two government banks and three non government banks, namely Bank of Ceylon, Peoples bank, commercial bank, Hatton national bank and HSBC. Primary and secondary research will be integrated as a data gathering procedure. The reason for this is to be able to provide adequate discussion for the readers that will help them understand more about the issue and the different variables that involve with it. In the primary research, managers and staff will be surveyed and will be distributed to the respondents through email. Participation of the respondents will be treated with maximum confidentiality. Two questionnaire papers will be surveyed. First one provide for the managers and it will included some questions regarding to requesting information about the IT investments and financial performance of the banks and other one provide to staff members of the IT department asking questions to get information about the computers usability and disadvantages or advantages of IT. But this survey method has more drawbacks, such as information may not be 100% reliable, some managers may reluctant to give some information, understanding weaknesses may be occurred and if it is a questionnaire, some responding banks may not have defined IT investment as same way. To avoid those drawbacks, I have decided to use secondary data for my research. Sources in secondary research will include annual reports, previous research reports, newspaper, magazine and journal content. Therefore it is efficient using current year financial statements and highlights for quarterly and annual and other reports as a secondary data. It is more reliable than survey. As well as it provide two or three year comparison of balance sheet, income statement and operating income, revenue and earnings per share of the banks. My research period will be 2003 to 2009 and to get present condition information current year will be surveyed. . Data will be analyzed using the latest SPSS software. Model 1 Since the norms for IT investment and Banks financial performances data vary from bank to bank , proir to conducting statitical analysis, each ratio will be standardized by subtracting its mean from the ratio itself and and then deviding the result by standard deviation. For avoid varinces of datas it will effective to mesure mean,Standard deviation and range for IT investment and financial performance of the banks. Budgeted IT investment ratio = Budgeted IT investment *100 Total RevenueTo mesure a banks IT invetment, the present research uses five ratios, including IT budget as a percentage of revenue, value of a banks IT as a percentage of revenue, percentage of IT budget spent on staff, percentage of IT budget spent on the training of IT staff and number of PCs and terminals as a percentage of total employee. The first ratio reveals how much a bank is spending on IT relative to its compititors. It can be calculate Value of IT investment ratio = IT value *100 Total RevenueThe IT value ratio reflect to current position of a banks technology, IT value figures are estimates of the current market value for all IT equipments,it can be calculate The staff spending cirterion reflects the banks relative investment in IT staff. It can be calculate Budgeted IT spend for staff = Budgeted IT spend on staff *100 Number of IT staff As well as information system managers must keep their employee well trained. The trining ratio used to mesure the relative amount spent by bank for this purpose. It can be calculate Budgeted IT investment on training staff = Budgeted IT spend on training staff *100 No of training Staff The last ratio mesures the extent to which the bank has made IT availabe to banks users. This ratio can be calculate IT usability ratio = No of PCs and terminals *100 Total employees Using above ratios I will find out mean and standard deviation of those ratios. Standard deviation is a measure of how far apart the data are from the average of the data. If all the observations are close to their average then the standard deviation will be small. Based on review of previous research, five direct measures of financial performance will be selected for this study. Return on investment (ROI), Return on equity (ROE), Return on assets (ROA), Earnings per share (EPS) and Net profit margin (NPM) ROI = Gain from investment-Cost of investment Cost of investment Return on investment can be measured using following ratio, Return on equity (ROE) can be calculate, ROE = Net income Shareholder equity ROA = Net income Total AssetsReturn on assets (ROA) can be calculate, EPS = Net income Dividends on preferred stock Average outstanding sharesEarnings per share (EPS) can be calculate, Net profit margin (NPM) can be calculate NPM = Net profit Total Income After measuring mean and standard deviation it is effective to measure correlation of those two set of variables. Correlation is a statistical measurement of the relationship between two variables. Possible correlations range from +1 to -1. A zero correlation indicates that there is no relationship between the variables. A correlation of -1 indicates a perfect negative correlation, meaning that as one variable goes up, the other goes down. A correlation of +1 indicates a perfect positive correlation, meaning that both variables move in the same direction together. Correlation helps to identify the relationship between Information technology and financial performance of the banks. In the first step will be find out IT investments correlated with themselves and financial performance correlated with themselves. Then the IT investment ratios will be next correlated with the financial performance ratios to investigate for the possible presence of, and the nature of pair wise relationship among the measures. Carl Pearson correlation analysis will be use for this purpose. Model 2 Above model shows that how much IT investments affecting to the financial performances, it shows only percentage figures. But hypothesis testing may be reflecting what factors actually affect to the increase financial performances relating IT investments. So I have selected hypothesis testing as my second model. In this model Key variables will be measured in an attempt to practice identifying dependent and independent variables and to explain how the independent variable affects the dependent variable. Independent Variable Dependent variable Internet banking ATM machines Computer system Return on Equity (ROE) Net profit margin (NPM) Earnings per share (EPS) Return on Investment (ROI) R According to above diagram, financial performances (dependent variable) depend on following financial indicators. Internet Bank: It is how the Internet used frequently by the Bank from a variable It is one of the independent variables, ATM: The number of ATMs owned by the bank in the period, it is one of the independent variables. , Computer system: It is the net investment bank in the computer software, hardware and equipment in the period i. It is one of the independent variables However, this model will also divide into another sub-models concerned with measuring the impact of independent factors of each of the indicators of financial performances, Model Affecting variables Return on Equity(ROE) Internet banking, ATM machines, Computer system (Hardware, software and other equipment) Net profit margin(NPM) Internet banking, ATM machines, Computer system (Hardware, software and other equipment) Earnings per share(EPS) Internet banking, ATM machines, Computer system (Hardware, software and other equipment) Return on Investment (ROI) Internet banking, ATM machines, Computer system (Hardware, software and other equipment) Hypotheses Development The main Hypotheses is There is no statistically significant impact on the use of information technology to improve the financial performance in Sri Lankan banks. H01: There is no statistically significant impact on the use of IT in Sri Lankan banks in the ROE H02: There is no statistically significant impact on the use of IT in Sri Lankan banks in the NPM H03: There is no statistically significant impact on the use of IT in Sri Lankan banks in the EPS H04: There is no statistically significant impact on the use of IT in Sri Lankan banks in the ROI Hypothesis Testing First I am going to examine the reliability of statistical analysis for the data by identifying how this data is close to normal distribution, if the data will not have normal distribution, then it should be a subject to necessary treatment . If it will close to the normal distribution I can use it correctly to test the hypothesis. After that I will be use regression model to identify effect of many independent variables on dependent variable. Regression analysis includes techniques for modeling and analyzing several variables, when the focus is on the relationship between a dependent variable and one or more independent variables. More specifically, regression analysis helps to understand how the typical value of the dependent variable changes when any one of the independent variables is varied, while the other independent variables are held fixed. Finally I will test above sub models using regression model. Data The impact of Internet-Banking on Bank Profitability- The Case of Turkey (by Assist. Prof. Dr. Ceylan Onay et al) under this topic they examined about internet banking on banks profitability. They follow an empirical model based on previous works by Berger(1995), Demirguc-Kunt and Huizinga (1999) and by Quispe-Agnoli and Whisler (2006), where they define bank performance, Yit (measured by ratio of banks pre-tax profits to total assets(ROA) or to its equity(ROE) or ratio of its net interest revenue to its total assets(MARGIN)) for bank i in year t as follows: ÃÆ'Ã… ½Ãƒâ€šÃ‚ ±0 is a bank fixed effect term that captures time-invariant influences specific to bank i, MACROt is a matrix of macroeconomic variables in Turkey in year t that include percentage change in real GDP per capita and average lending rate charged by banks in year t. Xit is a matrix of bank-specific control variables: Total deposits in bank i as a ratio of total assets in year t, total loans of bank i as a ratio of total assets in year t. BANKCRIt is a dummy variable of banking crisis in Turkey that takes on a value of 1 if there is a systemic bank crisis respectively in the country at time t and 0 if none. They employ this variable to control for changes in banks performance as a result of banking crisis in the country for the period. Following the work of Hernando and Nieto(2007) they employ a matrix of dummy variables, INTERNETJ , that are defined based on the time of adoption of a transactional website by the bank. Thus, INTERNET1 is a dummy variable that equals 1 if the bank introduced a transactional web site in year t (during the past 12 months). Similarly, INTERNET2 equals 1 if the bank adopted online banking in year t-1. We go back as late as t-2 to capture changes in bank performance over time. ÃÆ'Ã… ½Ãƒâ€šÃ‚ µit is a mean zero, constant variance disturbance term. To analyze the effects of internet banking on bank performance, we have collected panel data from 14 commercial and savings banks in Turkey that have adopted internet banking sometime between 1996 and 2005. A list of banks included in our analysis along with their respective years of internet banking adoption is available. Their dataset is drawn from income statements and balance sheets found in the BANKSCOPE Database for Turkish banks compiled by Bureau van Dijk Electronic Publishing (BvDEP). It covers a period of ten years (1996-2005) and is unbalanced due to the unavailability of data for some of the banks in our sample. The data on the timing of the adoption of internet banking for each bank is obtained from Polatoglu and Ekin (2001). Dates of episodes of systemic banking crises in Turkey during which some or all of banking capital is exhausted is obtained from Caprio et als Banking Crisis Database(2005). The dummy variable BANKCRI is obtained by using this information[1]. Table 3.2 lists the banking crises and time frames used in the population of this variable. For macroeconomic data, they have consulted IMFs IFS database (in obtaining data on the average lending rate) and Conference Boards Total Economy Database(for the gdp per capita values ) They found that the adoption of online banking does not seem to have a significant impact on the performance of Turkish banks measured in terms of ROA, ROE or MARGIN in the year of adoption(INTERNET1). However, in the following year (INTERNET2), they saw a significant decrease in the profitability. This could be attributed to the increase in IT expenditures following the adoption of the new technology. Only in the second year following the adoption of the technology, they examined a positive coefficient of the variable on the ROE estimation. This indicates that the process was gradual. The sign of the coefficient on the ROA for the same period was also positive but this variable was not significant.