Data Mining to Identify New Markets (1,176 words)
December 2000
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What's a financial institution to do when it has reached a plateau in its current market?
That was the situation Dallas Teachers Credit Union (DTCU) found itself in last year when it realized it had little room for growth. But its status was even more critical. It knew it might never expand much beyond its current 147,000 members, or at most its projected top level of 250,000 members, without a change to its charter. You see, the credit union was chartered as an occupational group in 1931 and could not offer its services outside the education market.
"We had hit the ceiling of that market," says Jerry Thompson, DTCU's senior vice president and chief information officer. "So we needed to go back to the State of Texas in January or February to request a change to our charter from occupational-based to community-based."
Opening the Door to a New Market
The DTCU needed to present a strong case before the Texas Credit Union Department to convince it of the need for an upgrade in its membership charter. Today, regardless of a bank or credit union's size, data mining technologies can help to identify new markets—both in terms of geographic area and demographics. Thompson says the credit union used information housed in its IBM EZMart data warehouse to make its case. "We went into the warehouse and looked at transactions using ArcView Business Analyst" software from ESRI, a developer of geographic information system software.
"Looking at our existing base showed excess capacity and the fact that we had a lot of potential in underserved areas," Thompson notes.
Usually one would look at geographic area in five-mile circles around the branches, but this would lead to gaps where no branches exist. Some innovative thinking led to the idea to use school districts as the basis of the geographic database build so there'd be no gaps. "With very few restrictions, every area has to be served by a school," Thompson explains.
"We did a three-year build on the file to reveal a potential field of 2.7 million in the geographic area. This included a combined 40 school districts in the 10-county Dallas area," he says.
The DTCU was granted its new charter on June 1 of this year.
Mapping Its Members
Geographic analysis of its data warehouse has been instrumental in helping DTCU in other ways, for instance to visually represent its member base within the surrounding communities. "The most exciting thing about all this is we can take the top 10 percent most profitable members and spatially map them across the field of the membership area," Thompson explains, adding "this is where the money comes from. These are the branches, the ATMs, they use."
That was the situation Dallas Teachers Credit Union (DTCU) found itself in last year when it realized it had little room for growth. But its status was even more critical. It knew it might never expand much beyond its current 147,000 members, or at most its projected top level of 250,000 members, without a change to its charter. You see, the credit union was chartered as an occupational group in 1931 and could not offer its services outside the education market.
"We had hit the ceiling of that market," says Jerry Thompson, DTCU's senior vice president and chief information officer. "So we needed to go back to the State of Texas in January or February to request a change to our charter from occupational-based to community-based."
Opening the Door to a New Market
The DTCU needed to present a strong case before the Texas Credit Union Department to convince it of the need for an upgrade in its membership charter. Today, regardless of a bank or credit union's size, data mining technologies can help to identify new markets—both in terms of geographic area and demographics. Thompson says the credit union used information housed in its IBM EZMart data warehouse to make its case. "We went into the warehouse and looked at transactions using ArcView Business Analyst" software from ESRI, a developer of geographic information system software.
"Looking at our existing base showed excess capacity and the fact that we had a lot of potential in underserved areas," Thompson notes.
Usually one would look at geographic area in five-mile circles around the branches, but this would lead to gaps where no branches exist. Some innovative thinking led to the idea to use school districts as the basis of the geographic database build so there'd be no gaps. "With very few restrictions, every area has to be served by a school," Thompson explains.
"We did a three-year build on the file to reveal a potential field of 2.7 million in the geographic area. This included a combined 40 school districts in the 10-county Dallas area," he says.
The DTCU was granted its new charter on June 1 of this year.
Mapping Its Members
Geographic analysis of its data warehouse has been instrumental in helping DTCU in other ways, for instance to visually represent its member base within the surrounding communities. "The most exciting thing about all this is we can take the top 10 percent most profitable members and spatially map them across the field of the membership area," Thompson explains, adding "this is where the money comes from. These are the branches, the ATMs, they use."
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