For many credit unions that have moved to a community charter, the next question becomes where to site branches.
Often decisions are made for all the wrong reasons: where have other institutions placed their branches, what routes do some members of senior management drive to work, or where there is a corner absent any other financial branch.
But data is available both within the credit union's own database that can be combined with vendors that have assembled detailed demographic, census and financial institution data that can greatly refine opportunities for branch placement and, in turn, a return on that investment.
MapInfo, which offers business intelligence tools for developing site locations strategies, has introduced a new database called Demand Insight Financial that can be used with its AnySite solution to better place branches. The company says it can provide a credit union with Demand Estimates on 16 different core products, both the total market and the portion available to retail financial institutions.
"It's not just where the consumer lives," stressed MapInfo's David Bunten. "It's also where people work and where small businesses are located."
During BAI's show, MapInfo had its software on display, overlaying over maps of the Dallas/Ft. Worth metroplex, for instance, graphical markers displaying different types of deposit and loan data, income data, and more by area. For instance, the software can create a drive-time paradigm showing various data within five driving minutes of a particular site. It can even provide estimates of cannibalization projections.
The company has a vast storehouse of demographic, purchasing pattern, socio-economic, financial and other data as the result of numerous acquisitions it has completed. Outside of financial institutions, it also does site location work for giant retailers such as Home Depot and the GAP. Bunten said its long-time financial clients also share their data with the company (as a block of data, not by individual name or account number) which is used to predict what he said are highly accurate models. He noted the company has spent 17 years compiling and refining its data. "It's a total model," he said. "It's tuned and very accurate."
But would not financial institutions all using the same data end up bunching their branches together? Not necessarily, said Hal Hopson, director of Predictive Analytic Solutions with Raleigh, N.C.-based MapInfo.
"Branches will not congregate because financial institutions have different product strategies," he replied. "They may specialize in home equities or MMAs. And some banks and credit unions also try to stay away from certain competitors, and you also have to factor in the location of existing facilities."
He said the data can also be used to move locations or to change the size of a facility's footprint. "A common misunderstanding is to congregate around affluent areas," he said. "Then you have too many trying to get a piece of the same pie."
What many credit unions also misunderstand, he said, is the value of siting branches near where people work, as that is a common driver for how many define convenience. "It's a mistake to just look at residential locations," he said of credit unions that will pull home address data from their own databases and make a decision based on that criterion.
"A lot of times what we hear from credit unions is that they spent a lot of money on the community side in an effort to attract new members and service existing members," he said. "The question is how do we have a rational expectation of how well that branch is servicing members and attracting new members. Credit unions say, 'How do I know if I spend $2 million on a new branch and $500,000 each year to operate it that I will see a return?'"
What Must Be Bought
Hopson said a credit union purchasing the MapInfo solution will not need any additional systems people. The software can reside on a desktop, and is also available in a less-expensive form online.
He said there is not much data that needs to be imported on the front end, as most credit unions have already captured the data they need.
Craig Capp, who was with Raddon Financial Group prior to joining MapInfo, said the credit unions that have the most difficult time in making site decisions are those that are strongly aligned with an employee group or sponsor.
"One area where those credit unions are weak is in having data that goes beyond the employer-membership," he said.
