The concept of banking refers to the multitude of services and products that commercial banks offer to clients and include besides transactional accounts both passive and active products. Due to the increased competitiveness in banking, the relationship between the bank and the client has become an essential factor for the strategy in order to increase customer satisfaction. Currently the banking system is able to store impressive amounts of data that they collect daily, from customer data and transaction details to data on their transactional or risk profile. The process through which large amounts of data are analyzed, extracted, identified and the information obtained using mathematical and statistical models are interpreted is known as data mining. The discovery of knowledge from data involves identifying some models, some patterns with which certain events or possible risks are anticipated. This process helps banks to develop strategies in areas such as customer retention and l.
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International Journal of Engineering Sciences & Research Technology
Data mining is one of the tasks in the process of knowledge discovery from the database. In the corporate world every organization is competing the other organization in terms of their value towards the business and the financial growth. Apart from execution of business processes, the creation of knowledge base and its utilization for the benefit of the organization is becoming a strategy tool to compete. In this paper we discuss about the basic details of data mining and the the use of knowledge discovery process and the new techniques from the business point of view.In our approach we make an efficient system so that the organization will get the right information at the right time and right to access the necessary information for their growth.The growth of the organization depends on the quality of service, competing with the other organizations,provide required information to the customers,satisfaction of the employees working in the organization. In the banking sector all the financial work can be done in the computers and their connectivity through World Wide Web the softwares get automatically updated in time,use of internet banking and ATM makes the big change in the banking sector. The banks have realized that their biggest asset is the knowledge and the planning to implement the right knowledge at the right time,the financial resources and the techniques of datamining for customer segmentation and profitability, marketing, risk management and customer relationship management and the fraud detection.
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Data mining is becoming strategically important area for many business organizations including banking sector. It is a process of analyzing the data from various perspectives and summarizing it into valuable information. Data mining assists the banks to look for hidden pattern in a group and discover unknown relationship in the data. Today, customers have so many opinions with regard to where they can choose to do their business. Early data analysis techniques were oriented toward extracting quantitative and statistical data characteristics. These techniques facilitate useful data interpretations for the banking sector to avoid customer attrition. Customer retention is the most important factor to be analyzed in today's competitive business environment. And also fraud is a significant problem in banking sector. Detecting and preventing fraud is difficult, because fraudsters develop new schemes all the time, and the schemes grow more and more sophisticated to elude easy detection. This paper analyzes the data mining techniques and its applications in banking sector like fraud prevention and detection, customer retention, marketing and risk management.
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American Journal of Applied Sciences
