Data Mining - Mehmed Kantardzic [279]
Bank of America (USA)
Bank of America is one of the world’s largest financial institutions. With approximately 59 million consumer and small business relationships, 6,000 retail banking offices and more than 18,000 ATMs, Bank of America is among the world’s leading wealth management companies and is a global leader in corporate and investment banking and trading across a broad range of asset classes. Bank of America identified savings of $4.8 million in2 years (a 400% return on investment) from use of a credit risk management system provided by SAS institute consultants and based on statistical and data-mining analytics [“Predicting Returns from the Use of Data Mining to Support CRM,” http://insight.nau.edu/WhitePapers.asp]. They have also developed profiles of most valuable accounts, with relationship managers being assigned to the top 10% of the bank’s customers in order to identify opportunities to sell them additional services [“Using Data Mining on the Road to Successful BI, Part 3,” Information Management Special Reports, Oct. 2004]. Recently, to retain deposits, the Global Wealth and Investment Management division has used KXEN Analytic Framework in identifying clients likely to move assets and then creating offers conducive to retention [“KXEN Analytic Framework,” Information Management Magazine, July/Aug 2009].
B.2 DATA MINING FOR THE TELECOMUNICATIONS INDUSTRY
The telecommunication industry has quickly evolved from offering local and long-distance telephone services to providing many other comprehensive communication services including voice, fax, pager, cellular phone, images, e-mail, computer, and Web-data transmission, and other data traffic. The integration of telecommunications, computer networks, Internet, and numerous others means of communication and computing is under way. The U.S. Telecommunication Act of 1996 allowed Regional Bell Operating Companies to enter the long-distance market as well as offer “cable-like” services. The European Liberalization of Telecommunications Services has been effective from the beginning of 1998. Besides deregulation, there has been a sale by the FCC of airwaves to companies pioneering new ways to communicate. The cellular industry is rapidly taking on a life of its own. With all this deregulation of the telecommunication industry, the market is expanding rapidly and becoming highly competitive.
The hypercompetitive nature of the industry has created a need to understand customers, to keep them, and to model effective ways to market new products. This creates a great demand for data mining to help understand the new business involved, identify telecommunication patterns, catch fraudulent activities, make better use of resources, and improve the quality of services. In general, the telecommunications industry is interested in answering some strategic questions through data-mining applications such as:
How does one retain customers and keep them loyal as competitors offer special offers and reduced rates?
Which customers are most likely to churn?
What characteristics indicate high-risk investments, such as investing in new fiber-optic lines?
How does one predict whether customers will buy additional products like cellular services, call waiting, or basic services?
What characteristics differentiate our products from those of our competitors?
Companies like AT&T, AirTouch Communications, and AMS Mobile Communication Industry Group have announced the use of data mining to improve their marketing activities. There are several companies including Lightbridge and Verizon that use data-mining technology to