Western Independent Banker - May/June 2013 - (Page 9)

By Mike Middleton Data Mining for Profits in 2013 significant loss of revenue. At institutions without a disciplined approach to fee waivers, it’s not surprising to find that over 70 percent of all waived fees are given to unprofitable customers. In fact, it’s not uncommon to find that a $500 million bank waives over $300,000 in fees per year to unprofitable customers. To remedy this, the first step is to utilize data mining within your customer base to identify the customers with waived fees and stratify them according to profitability. For customers with overall profitable relationships, fee waivers are certainly appropriate. However, for unprofitable relationships bankers should implement strategies to eliminate (or at least reduce) the number of waived fees, such as offering unprofitable customers the chance to increase account balances to avoid fees. THE PAST FEW years have been no picnic for bankers with stringent compliance regulations, a challenging rate environment and soft loan demand, and without new sources of profitability, community banks are facing another grueling year. The good news is that this adversity has created many opportunities – if bankers know where to look. For many banks, there is a huge untapped opportunity to increase revenue by data mining customer information already in the bank’s system. Even for banks that have implemented data mining strategies, many have been slow to effectively utilize this data, such as determining the profitability of customers or prospects. The following strategies identify revenue enhancement opportunities that can be used to improve your data mining tactics and increase your bank’s bottom line. Reduce Waivers on Deposit Service Charges Too often community banks waive fees for unprofitable customers, resulting in a Improve Cross-sell Opportunities Somewhat astonishingly, more than half of banks have customers with only one account and 20-25 percent do not even have a checking account. Studies consistently show that the more products a customer uses, the lower the likelihood they are to leave – and the higher the profitability of the customer. To take advantage of this, banks can use data mining to gather information about customer accounts and, in turn, use that data to sell additional products. Cross-sell ratios for community banks under $2 billion generally range between 2.1 and 2.7 products per customer. To deepen relationships, banks should target the lowest hanging fruit – customers who have only one account with the bank. Realizing the opportunities in crossselling, a $1 billion bank in the Northwest declared the practice a strategic priority. The analysis indicated that through sales training and better tracking and measurement, the bank could boost its cross-sell continued on page 10 As renewals come up, banks can use data mining to determine the profitability of customers and loans, and then use that information to offer attractive terms to the most profitable. Western Independent Banker May/June 2013 9 http://www.wib.org

Table of Contents for the Digital Edition of Western Independent Banker - May/June 2013

A Message from the Chair
Data Mining for Profits in 2013
Banks Must Face Their Own Fiscal Cliff
Boost Your Bottom Line with Lending Process Enhancements
Managing Interest Rate Risk to Achieve Strategic Profitability
Moving Mobile Banking Toward Acceptance – and Profitability
Alternative Revenue Strategies to Improve Bank Profitability
Analyzing Customer Performance to Increase Bank Profitability
WIB Service Corporation Report: Secrets to Success in 2013
Professional Development Resources
Welcome New Members
Index of Advertisers/ Advertiser.com

Western Independent Banker - May/June 2013

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