Operational data is the source for all business intelligence applications, but the data is typically not in the correct format to support the decision-making process in a business. Further, nowadays, banks are storing more information than ever before. Decision makers must have the right information at the right time to help them make more informed and intelligent decisions. The data in the operational database represents current transactions, however, the decisions are based on a different time frame. Moreover, data in operational databases are stored with a functional or process orientation and what really decision makers would like to have is subject orientation of data, which facilitates multiple views for data and decision making.
Data Warehousing and Data Mining are the right solution that makes the above possible. One of the main goals of implementing a data warehouse is to turn the wealth of corporate data into information that can be used in the daily decision making process. In this paper, we highlight the need of data warehousing and data mining for banks and provide an approach to build the warehouse suitable to banks. The banking industry is becoming increasingly dependent on Information Technology to
retain its competitiveness and adapt with the ever-evolving business environment. The
industry which is essentially becoming a service industry of a higher order, has to rely
on technology to keep abreast with global economy that technology has thrown open.
As far as Indian Banking scenario is concerned the Government has stipulated that
banks have to computerize their operations at the earliest. The Institute for Development
and Research in Banking Technology (IDRBT) has undertaken the mammoth task of
networking all Indian banks under the Indian Financial Network (INFINET). The prospect
of INFINET encompassing the Indian banking scenario gives mammoth volume of data
to be handled by banks. This data could be of different forms and on different platforms.
Everyday mountains of data is produced directly as a result of banking activities, and
as a by-product of various transactions. A vast amount of information is about their
customers. Yet, most of these data remains locked within archival systems that must becoupled with operational systems to generate information necessary to support strategic
decision-making.
A variety of approaches for computer-aided decision-making systems have appeared
over time under different terms like Management Information Systems (MIS), Executive
Information Systems (EIS), and Decision Support Systems (DSS). The term Management
Information System is not new to the banking sector. Since the early 80s, banks have
been using the Management Information Systems for the process of generation of various
reports which are used for analysis at the Corporate/Head offices for their decisionmaking
for own use as well as for conveyance to authorities in charge of regulation. Often,
these reports are generated through computers and can be generated at any point of
time. However, the terms Data Warehousing and Data Mining have gained significance
with the growing sophistication of the technology and the need for predictive analysis
with What-if simulations. |
