Tatra banka reduces client attrition, boosts sales with SAS®
With 40 percent market share, credit cards are a key product at Tatra banka. Founded in 1990 as Slovakia's first private lending institution, Tatra banka experienced slow growth and double-digit attrition when the global economic crisis hit. Hard times forced consumers in the saturated market to put away or cancel their credit cards – many of them falling behind in their payments. So the bank set a goal of reducing attrition by 30 percent. And it turned to SAS for the predictive analytics to achieve it.
"We couldn't afford losing clients of such a profitable and image-making product that defined us so much," says Marián Babic, Head of the Campaign Management Department.
"If you want to select the right clients from such a large pool, you need mathematical and statistical technology," says Babic.
"What is interesting about the private segment is that there is always a limiting factor," says Babic. "We could not approach all the clients; basically, we had to pick the right ones."
Improving data quality to support processes
"We did not want to be dependent on external suppliers; we preferred to have our own team of experienced people who could promptly respond to our needs in the future," says Babic.
Since credit cards weren't the bank's only products, it also planned to use business analysis for bank accounts and mortgages. The bank later purchased a SAS solution that enabled it to cross-sell products to existing clients.
Before conducting any major analysis, however, the bank needed high-quality data to support its processes. Marek Bičár, Segment Manager, recognized early that analyses and business decisions couldn't be based on incomplete or incorrect data – and the data needed to be consolidated. Working with SAS Consulting, the bank mastered the processes of data collection, modeling and business interpretation. And now it can create a new model within one or two weeks.
With the help of SAS, the bank can create detailed segments and more effectively select customer groups for targeted sales or retention campaigns. It has also nearly reached its goal of reducing customer attrition by 30 percent.
Tatra banka has also seen measurable cross-selling results. "Today, figuratively speaking, our shots are more accurate. To achieve the same result we need fewer shots," says Babic.
The bank discovered that clients who are designated by the predictive model as having the highest potential to buy a certain product often accept the offer at a rate two or three times higher than randomly selected clients. In addition, analytics help the bank optimize communication. Babic says it's not important to swamp clients with advertising – it's more effective to keep them informed of new products and offers.
Planning for the future
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Reduce attrition among credit card clients during a tough economy
SAS for predictive analytics
Ability to predict which offers customers will accept helps Tatra banka meet goal of reducing attrition by 30 percent; targeted customers accept offers at a rate two or three times higher than randomly selected customers; solidifies bank’s reputation as a business leader in Slovakia
“We couldn't afford losing clients of such a profitable and image-making product that defined us so much.”
Head of the Campaign Management Department