For all the dollars sunk into compliance efforts over the past five years, companies have been hoping they'd eventually gain some business value from having data in line with regulatory requirements. In fact, the original vendor pitch for a variety of compliance products and services seemed more about incremental business value than hitting the compliance mark. It was a "me too" come-on that fizzled in the market when it was discovered that the bulk of the compliance burden was manual and about correcting and documenting processes more than it was about technology.We have written about this topic before, but as time has passed, maybe we're getting closer to the light. Last week I co-chaired a presentation from BearingPoint's financial services group, (co-sponsored by Oracle) on the topic of "customer performance management." That's an interesting mix of terms that implies measuring and managing customer data, which we all know is scattered about in product, divisional and departmental silos. But in heavily regulated industries, particularly financial services, a variety of legislative requirements call for an enterprise level data set of customer information, the "have it or go to jail" missions that attract the attention of chief executives. Because of Basel II, AML (anti-money laundering), KYC (know your customer) and other hurdles, financial service firms have spent tens or hundreds of millions of dollars building sophisticated (and still siloed) data sets for regulatory reporting. The idea here is to exploit an enterprise-wide (that's the key term) customer data in concert with other risk, finance and customer relationship information to establish the broader view of the customer.

It's not necessarily another data warehouse project; Bill Lehman, managing director of the global financial services practice at BearingPoint, has been working with clients to federate and/or service enable the enterprise customer view. In practice, this would be the customer identification hub, anything from a directory to an active reference system linked to data sets scattered among various product groups. "We have some people who are pretty strong on service-oriented architecture [SOA], and in several cases now we've built hub-based systems rather than another data store. You do have to build a hub for reference purposes and to establish and maintain the enterprise customer ID, but using SOA it's much more economical than a complete enterprise data warehouse."

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