Data Mining in Information Technology and Banking Performance

Data Mining in Information Technology and Banking Performance

Yao Chen (University of Massachusetts at Lowell, USA) and Joe Zhu (Worcester Polytechnic Institute, USA)
Copyright: © 2003 |Pages: 13
DOI: 10.4018/978-1-59140-051-6.ch017
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Abstract

Information technology (IT) has become the key enabler of business process expansion if an organization is to survive and continue to prosper in a rapidly changing business environment while facing competition in a global marketplace. In the banking industry, a large amount of IT budgets are spent with the expectation that the investment will result in higher productivity and improved financial performance. However, bank managers make decisions on how to spend large IT budgets without accurate performance measurement systems on the business value of IT. A survey on managing technology in the banking industry found that 55% of the 188 senior executives surveyed stated that the returns on their investments in IT were either good or excellent. However, 50% of the senior executives also stated that they did not have any formal systems in place to measure the return on investment. This illustrates a need for a proper data-mining technique that can examine the impact of IT investment on banking performance. It has been recognized that the link between IT investment and banking performance is indirect, due to the effect of mediating and moderating variables. This chapter presents a methodology that measures the efficiency of IT utilization and the impact of IT on banking performance when intermediate measures are present. A set of banks is used to illustrate how we (1) characterize the indirect impact of IT on banking performance, (2) identify the best practice of two principal value-added stages related to IT investment and profit generation, and (3) improve the financial performance of banking.

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