In the current era of competition, the use of computers and allied technologies has become inevitable and it has been well recognized that Information Systems (IS) plays different roles in different industries. This paper makes an attempt to explore empirically the difference in the role of IS in the banking industry, i.e., between public sector, private sector, and foreign sector banks operating. The study indicates that IS plays a supportive role in public sector banks and a strategic role in private and foreign sector banks. The study also indicates that the future impact of IS does not vary significantly with the banking groups.
Traditionally, IS has been viewed by its practitioners as playing only a supportive role. Recently, however, due to a significant decline in the cost of information technology (IT) and greatly improved speed and power of computers, IS -lias moved from its traditional role as an application of back office support to one offering opportunities for gaining significant competitive advantage. It is being increasingly viewed as having the capability to alter core organizational directions, reorient corporate strategy, and redefine industry structure.
A highly dynamic market, changing client demands, fierce competition, the necessity of strict control and risk management are only some of the characteristics of the business environment where modern banks conduct their operations. Better management and better decision-making process make the difference between the successful and the unsuccessful on the market with these characteristics. Business intelligence solutions for banks should provide the decision makers from all business segments of a bank with the ability to manage and exploit information resources, in order to solve the problems and make timely and high-quality decisions. Business intelligence systems in banks must be comprehensive and yet simple for the end user. Business intelligence covers many areas of the bank, and among the most important are: Customer Relationship Management (CRM), Performance Management (PM), Risk Management (RM), Asset and Liability Management (ALM), and Compliance. Data warehouse and online analytical processes (OLAP) form the informational basis for the application of business intelligence. Data mining and knowledge retrieval are also important segments of business intelligence and deal with complex statistical analysis, discovering "hidden" relationships between data and forecasting the behaviour trends of business systems.
Modern banks must respond to challenges such as process automation, increased client expectations, aggressive competition, mergers and acquisitions, new product development and market segmentation. At the same time, banks must also manage risks and harmonise their business operations with the growing national and international regulations, such as IAS, AML, BASEL II etc. Management comes down to decision making, and decisions must be timely, efficient and based on accurate and reliable information derived from data. Banks record large amounts of data daily; data are recorded for all clients on their personal, psycho-social, property and financial features, as well as all their accounts, transactions per account, credit liabilities etc. This data is generated in the bank’s basic information system and stored in transactional databases. Experience has shown that transactional databases are a rich information source that can be used for enhancing the business of any company, especially a bank, due to the above mentioned facts about the availability of large amounts of data. It became clear a long time ago that banks have a lot of data but little information, and very little knowledge on many aspects of their operations. Transactional databases, however, are enormous.
Let us suppose that bank management wants to establish the characteristics of clients that have been insolvent in the past. Such information can usually be requested from IT personnel at the bank, who, in such cases, must spend a considerable amount of time to produce the requested report, on top of their regular workload. By the time the report reaches the manager’s desk,it may be too late for decision making.
The development of information and communication technologies (ICT) provides successful solution to the above mentioned problems. A large subset of business information and knowledge management, and the first step towards a learning organisation is a set of methods, tools and applications denoted by the blanket term “business intelligence“ (BI). Nowadays, BI is regarded as a separate discipline encompassing elements of information technology, strategy, managerial accounting, corporate analysis and marketing. It enables gathering, analysing, disseminating and acting based on the business information, aimed at facilitating the resolution of management problems and making the best business decisions. A business intelligence system does not exist as a final product; its producers offer technological platforms and knowledge for their implementation.
Modern banks are known to be among leaders in the area adopting new technologies and knowledge, which is exactly why they are the fertile soil for implementing such an infrastructure. A special type of databases, referred to as data warehouses (DW), are generated to meet the needs these systems, where data is organised in a manner convenient for conducting analytical processes on large data set. A data warehouse contains a copy of data isolated from the operational databases and structured specially for reports and analyses. Data warehouses and Online Analytical Processing (OLAP) form the informational basis for applying business intelligence. Data mining and knowledge discovery are also important segments of business intelligence, dealing with complex statistical analysis and discovering "hidden" relationships between data forecasting the behaviour trends of business systems.