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Data Mining and Warehousing and its Impact on Banking Organizations

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  1. Introduction
  2. Data Mining, OLAP and Warehousing in the Banking Industry
  3. OLAP?Online Analytical Processing
  4. Data Warehousing
  5. Conclusion

Over the course of the last several years, the development and proliferation of information technology has impacted most industries. As the result of new technology, organizations are now able to collect and analyze data for the development and implementation of new products and services. Nowhere is this process more evident than in the banking industry. In the last several years, organizations in the banking industry have widely adopted technologies that allow for both data mining and warehousing. For organizations that have undertaken these changes, the results have been quite positive overall.

[...] As such, data mining clearly has implications for the development and financial success of the banking organization. In an effort to elucidate the myriad of ways in which data mining in banking can be used for marketing, Wallace (1997) notes the case of San Diego-based Advanta Mortgage Corp. As noted by this author, Advanta Mortgage has been able to incorporate data mining for the purposes of cross- selling other products and services to its credit card customers. By identifying specific trends in customer behavior, Advanta has been able to better identify specific customers that might be interested in other programs offered by the organization. [...]

[...] For instance Alexander (1997) in his examination of applying both data mining procedures and OLAP to the banking organization notes that, ?Using data mining, you may come up with a model to find who are the most profitable customers. Then you may do more traditional OLAP analysis of that subset of data to see what the impact would be if you lost those customers, how it would affect your bottom line? (p. 61). What this effectively demonstrates is that OLAP provides the necessary tools to further analyze data for the purposes of extracting critical information about operations and customers. [...]

[...] This article provides a general overview of data mining and the ways that is applied in both the banking and retail industries. Huber, N. (2004, March 23). Lloyds TSB saves £20m by using monitoring software to cut fraud. Computer Weekly This article examines the methods used by Lloyds TSB to reduce credit card fraud. Khirallah, K. (1999). Building a data warehouse at Chase Manhattan Bank. Bank Accounting & Finance, 40-46. This article details the development of a data warehouse at Chase Bank. [...]

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