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Austria's Largest Bank Accelerates Data Mining With KXEN.

SAN FRANCISCO & PARIS -- With increasing competition in the financial services industry it is now more important than ever for banks to deploy the latest customer technologies to optimize the speed, accuracy and frequency of their marketing. Leading the sector in Austria is the country's largest -- Bank Austria Creditanstalt -- where innovative data mining tools are now helping turn targeted marketing into a fine art.

The bank now routinely mounts a new customer campaign once every two weeks, seeing take-up rates of between three and five per cent -- up from one per cent before -- and has achieved new business worth an estimated 50 million Euros in one season alone.

Behind the gains is Extreme Data Mining technology from vendor KXEN. It has brought improvements in the accuracy and speed (and hence frequency) of the data analysis used to identify potential customers. Just as important it has made complex data mining much easier, allowing it to be used by many more bank employees than before.

Bank-Wide Program

The implementation of KXEN's technology followed a bank-wide 'fit for sales' program begun in 2004 and aimed at bringing all sales and marketing activity under central control, together with a reform of direct marketing. As part of these changes a higher frequency of marketing promotions was vital, but that was something the bank's then data mining platform could simply not support.

Werner Widhalm is head of the customer knowledge management unit at BA-CA. "It was critical for us to be able to conduct 14-day marketing campaigns based on relevant customer data, but traditional data mining had been far too time-consuming and complex to allow a fortnightly program to be established," he explains. "The self imposed mission became one to find a tool for data mining which accommodated a heightened demand for speed and precision."

Working alongside Widhalm on the project team was a management consultancy firm. It very quickly identified Extreme Data Mining as a perfect fit for the bank's needs, ran a test and within a few weeks KXEN's technology was chosen.

Speed and accuracy aside, it was the KXEN solution's ease of use even by non-specialists that was the most compelling factor in the bank's decision. Most other data mining tools require specialization in mathematics or statistics before they can deliver meaningful results.

"Anyone who has a reasonable amount of experience in data analysis can quickly acquaint themselves with the software," says the bank's Erich Hrusa, responsible for technical architecture in customer knowledge management. "We also wanted a fast-working system to meet the demands."

During implementation, work focused on the bank's data warehouse which stores operational information daily, weekly or monthly, and which feeds an analytical data mart also serving as a hub. The data mart -- running on six SQL Server 2000 servers -- holds some four million customer records, including information on previous and prospective customers, and it is here that analytic data sets are generated ready for modeling by the KXEN software. Some 4.5 terabytes of data are held in the bank's operational systems, with a further 2 terabytes archived.

Analytical models created in KXEN are automatically fed through the bank's scoring engine in batches weekly or monthly depending on the schema. "In a month we can now run a minimum of 20 analyses, something which before would have taken at least four months to process, thus improving our time to market," explains Erich Hrusa.

Specific applications of KXEN's Extreme Data Mining technology include prediction of propensity-to-buy, customer segmentation (cluster analysis) and retention analysis. Results from KXEN analyses are fed back to the data mart from where they go into the bank's Epiphany system where they inform marketing campaigns.

Practical Approach

Such has been the success of the new KXEN system at BA-CA that staff no longer consider the old way of data mining -- users developing regression models over long periods of time -- to be viable. They believe the KXEN software itself holds the mathematical expertise required, with the expert adding the all important business knowledge that completes the process. "This practical approach works very well," says Hrusa.

As well as producing models at high speed the KXEN software also rapidly evaluates their quality. The end result is vastly increased speed and productivity, making modeling effectively a production line activity. "Our data mining models are far more industrialized in comparison to previous ones: this is the only way to manage the plethora of marketing activities now," he says.

But what about the success rate of predictions? Werner Widhalm again: "It is difficult to make an exact evaluation as there are generally about five to eight parallel marketing campaigns, which may be competing with each other. But we are looking at a success rate of target customer deals in the area of three to five per cent with KXEN. Before that, it was one per cent or less."

Also indicative is that data mining now supports around 20 per cent of new business at the bank, which added up to some 50 million Euro last spring. "Thanks to good data quality and more qualified information we achieve better results even though we approach fewer customers," says Widhalm.

There have been other benefits too. One example is in analyzing customer churn. "We have over 1,500 attributes and patterns on old customers who have left, therefore the factors that might indicate a current customer about to churn would simply not be discernible to the naked eye," says Widhalm. Now if a customer displays certain behavioral patterns -- such as termination of products or a decrease in volume -- staff can spot it in time and take appropriate action.

Impressive though the results to date have been, BA-CA is already thinking of ways to improve them even further. One example is evaluation of methods where the results of relevant success measurements flow back into the model, together with incorporation and further analysis of sales from operations. Following best practice the bank also intends to extend and develop in the direction of centralized data processing, with a view to creating what it calls a 'single point of truth'.

In the analytical area Werner Widhalm feels the goal should be to provide an increasing level of detail about customers and so gain still more information for data mining. "The more we know about our customers the better we can serve them," he says.

About Bank Austria Creditanstalt

A member of the UniCredit Group, Bank Austria Creditanstalt (BA-CA) operates the leading international banking network in the Central and Eastern European growth region. It has more than 7 billion Euros in equity and its market shares range from 20 to over 50 percent, making it Austria's largest bank.

Headquartered in Vienna, Bank Austria Creditanstalt's history goes back more than 150 years. Today it is a dynamic full service bank offering its customers -- including 85% of the largest Austrian businesses and more than 60% small/medium companies -- access to international financial markets. It has 400 branches and around 9,800 employees in Austria, was the first Western bank to gain a foothold in the former COMECON countries, and is continuing to expand into Central and Eastern Europe.

About KXEN

KXEN provides next generation business analytics software to drive better corporate decisions. KXEN's unmatched speed, ease of use and scalability enable leading companies around the world to expand the use of predictive analytics and enhance corporate performance. Based on breakthrough mathematical theory, KXEN's products offer reliable predictions and deep insight for achieving critical business goals. The company partners with leading systems integrators and software vendors to integrate advanced analytics into enterprise applications and business processes. Founded in 1998, KXEN is headquartered in San Francisco, California, with offices in the USA, UK, and France, and distributors throughout the world. Visit the KXEN Web site at www.kxen.com.
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Publication:Business Wire
Date:Feb 27, 2007
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