Methods of data mining used by credit card companies

Methods of data mining used by credit card companies

Do you have any suggestions on the methods of data mining used by credit card companies?

    Requires Free Membership to View

    When you register, you'll begin receiving targeted emails from my team of award-winning editorial writers on the latest customer relationship management (CRM)and call center technology issues today. Our goal is to keep you informed on the hottest issues facing this fast-changing industry.

    Hannah Smalltree, Editorial Director

    By submitting your registration information to SearchCRM.com you agree to receive email communications from TechTarget and TechTarget partners. We encourage you to read our Privacy Policy which contains important disclosures about how we collect and use your registration and other information. If you reside outside of the United States, by submitting this registration information you consent to having your personal data transferred to and processed in the United States. Your use of SearchCRM.com is governed by our Terms of Use. You may contact us at webmaster@TechTarget.com.

Credit card companies have actively used data mining techniques to address a variety of problems. On the marketing side of the business, decision trees have been a popular choice for predicting customer acquisition and retention targets. On the fraud prevention side, neural networks are commonly used. There isn't a hard and fast rule about which algorithms to use to solve a particular problem; analysts usually employ a variety of techniques and then select the best model that solves the problem at hand. If you are looking at a problem and are trying to determine which method to use, my suggestion is to try several and then evaluate them to choose a winner. You might want to make your choice of data mining software based on the ability of the software to automatically explore the space of possible techniques and present you with the best one.

For more information, check out SearchCRM's Best Web Links on Data Mining.


This was first published in April 2002

Join the conversationComment

Share
Comments

    Results

    Contribute to the conversation

    All fields are required. Comments will appear at the bottom of the article.