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Progressive Financial Services Firms Demonstrate the Value of Predictive Analytics; Decision Services Offer a Path for Others to Follow

(Posted by guest Blogger, Gib Bassett)

Yesterday an article I wrote about Decision Services appeared in the online edition of DM Review’s December 2007 issue ("Decision Services: Pragmatic Real-Time Analytics"). In it, I describe how Decision Services, by providing a framework for managing both business rules and analytics, can pave the way toward adopting predictive analytics.

One of the points I make is that many firms rushed to adopt predictive analytics for a single business function or customer channel, and this focus bit many an organization by overlooking the broader application of predictive analytics to the entire enterprise. Decision Services offer a solution to this problem by serving as the basis for rules automation today while providing a growth path to including predictive models in a deployment. This point is driven home in a Nov. 12, 2007 article brought to my attention today in Insurance & Technology Magazine, titled “Predictive Analytics and Complex Event Processing Technology Move to Cutting Edge of Financial Services Industry.” The article raises several examples of how leading financial services firms have successfully deployed predictive analytics by taking an enterprise view. Consider:

“A key part of the success of Selective's predictive analytics effort, according to Bravo, was the complete integration of predictive analytics with personal and commercial lines operations, rather than launching predictive analytics as an isolated, bolt-on solution. "One of the advantages that Selective has is our ability to bring [predictive analytics] into the regular insurance operations of the company and not disrupt those operations while still taking full advantage of the guidance and granularity the models provide," he (Bravo) says.”

Another example:

"Immersing the company in predictive analytics, rather than stapling the concept to the side of the enterprise, also was a key to success at Wachovia ($720 billion in assets). In part to facilitate the use of predictive analytics in building new customer relationships, the Charlotte, N.C.-based bank realigned its marketing group to include several other divisions, such as insight and innovation, e-commerce, and customer loyalty and satisfaction."

While any financial services firm would like to implement predictive analytics and reap similar benefits, the first steps are not always clear, a problem raised by the Data Warehousing Institute's Wayne Eckerson mentioned in this recent blog posting. Also in that posting, I refer to Decision Yield as one way many organizations are determining their initial foray into predictive analytics as part of an Enterprise Decision Management (EDM) strategy.  Financial Services firms of any sophistication owe it to themselves to explore how predictive analytics could positively affect their business and a Decision Yield assessment can point the way.

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Dan Dolberger

Hello Gib,

As someone who has for along time championed the enterprise-wide application of demand driven price optimization in the financial services, your post hit me right on the inspiration spot. To me, Price Optimization is a prime way to start the journey from "clip-on analytics" to full immersion.
So, thanks for the inspiration, and you can see the result on:

Dan Dolberger

Gloria J Miller

Hello Gib,
You make an excellent point about approaching an enterprise-wide deployment of predictive analytics. While working at SAS, I have seen so many financial services companies with all the software capabilities they need that fail to use those capabilities throughout the entire enterprise. Troy University is currently running a survey on “Decision-Making Using Systems and Technology”.

It will be interesting what the results and outcomes later this year. Best regards, Gloria

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