Data Mining: a Tool for the Enhancement of Banking Sector

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Data Mining: A Tool for the Enhancement of Banking Sector
Shipra Kalra; Rachika Gupta
kalra.shipra87@gmail.com; guptarachika@yahoo.co.in
Lecturer, Chanderprabhu Jain College of Higher Studies and School of Law, Sector A-8, Narela, Delhi-110040

Abstract

Data mining is emerging as a very useful tool for providing valuable information from large databases and enabling managers and business executives to make hard core decisions in a much easier and effective manner. It is a process of analyzing the data from various perspectives and summarizing it into valuable information. This paper defines what data mining is and how does it works. It then focuses on the use of data mining in banking industry on various areas like market segmentation, direct mail marketing, customer churn, fraud detection and risk management. Keywords: data mining, market segmentation, direct mail marketing, customer churn, fraud detection, risk management

1. Introduction

Almost every organization today is recognizing the importance of utilizing data mining in their businesses. Data mining is emerging as a very useful tool for providing valuable information from large databases and enabling managers and business executives to make hard core decisions in a much easier and effective manner. Not only data mining helps to extract useful knowledge from large amount of data but it is also helping in declining various costs like cost of computation power and also reduces time for decision making and knowledge discovery. Data mining is primarily used today by organizations with a strong consumer focus - retail, financial, communication, and marketing organizations. It enables these organizations to determine relationships among "internal" factors such as price, product positioning, or staff skills, and "external" factors such as economic indicators, competition, and customer demographics [13]. Data mining can help these organizations to better serve their customers, and increase the effectiveness of the organization (Chopoorian et al., 2001). [8]

Data mining is becoming strategically important for banking sector as well. It analyzes the data from various perspectives and summarizes it into valuable information. Data mining assists the banks to look for hidden pattern in a group and discover unknown relationships in the data. Today many banks are employing data mining for their proper functioning, the list includes: Bank of America, First USA Bank, Headlands Mortgage Company, FCC National Bank, Federal Home Loan Mortgage Corporation, Wells Fargo Bank, Nations-Banc Services, Mellon Bank N.A., Advanta Mortgage Corporation, Chemical Bank, Chevy Chase Bank, U.S. Bancorp, and USAA Federal Savings Bank. [11]

This article begins with: what is data mining, how data mining works. It then specifically focuses on what data mining can do in banking sector relating to Market segmentation, Customer churn, Fraud detection, Risk management, Direct mail marketing, and Trend analysis.

2. What is Data Mining?

Data Mining is the process of extracting knowledge hidden from large volumes of raw data. According to Cabena et al. (1998) data mining is defined as “the process of extracting previously unknown valid and actionable information from large databases and then using the information to make crucial business decisions” [7]. Data mining software is one of a number of analytical tools for analyzing data. It allows users to analyze data from many different dimensions or angles, categorize it, and summarize the relationships identified. Technically, data mining is the process of finding correlations or patterns among dozens of fields in large relational databases. Data mining tools predict behaviors and future trends, allowing businesses to make proactive, knowledge-driven decisions. Data mining tools can answer business questions that traditionally were too time consuming to resolve. They search databases for hidden patterns, finding predictive...
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