By Katherine Burger

One of the themes that has emerged from discussions and presentations at this year's IASA Annual Educational Conference & Business Show in Minneapolis is the importance of insurers taking a different, more-savvy approach to information management, in order to leverage the opportunities enabled by the new generation of data management and analytical technologies, as well as to avoid the costs, inefficiencies and operational risk of poorly managed data.

"There's more data awareness in the industry than ever before," commented Peter A. Marotta, AIDM, Enterprise Data Administrator, Enterprise Data Management, ISO (Jersey City, N.J.), who is charged with both documenting ISO's data assets and taking an enterprise view or the organization's data. That's partly because there is more external and internal data than ever before available to insurance professionals, and also because technologies such as data warehouses and analytics tools potentially make that information more accessible, he noted. But more is not necessary better, according to Marotta. The challenge, he said, is "how to make optimal use of the data itself," and to view "data as a corporate asset," similar to financial assets or staff assets.

The problem, especially where less-informed users are concerned, has to do with the quality of data that's coming from a wide range of sources, including census and postal data, Marotta said. "Do you really know what that data is, where that data is, and how it's defined?" he asked. "To make the best use of data you need to know what you have."

The good news is that a growing number of insurance companies "are migrating to some kind of enterprise data strategy," he said. Marotta also is starting to see a few companies appoint someone to a "chief data officer" kind of role. Still, he stresses, this should not be viewed as strictly an IT responsibility. "A data steward has to be on the business side," he said. "A lot of companies cede [this] to the CIO or CTO." But IT can only focus on the tools and systems that help organize and store the data. "Typically it's the business people who head; if you're chief underwriter you oversee risk information; you're the guy who owns the asset."

Improved data quality is one of the potential benefits insurers can gain by adopting a straight-through processing strategy, agreed the panelists for the conference session "STP Does Not Mean Someday's Terrific Promise." Like Marotta, Celent managing director, global insurance group, Matt Josefowicz urged insurers to view "data as a strategic asset. There's an increasing awareness of importance of enterprise data – customer data, risk data and operational data," he said, adding, "The key issues about data are transparency, accessibility and quality." That said, "Data quality is a major issue – making sure data is clean and not corrupted," Josefowicz noted. "STP is key to supporting data quality."

He outlined several improvements that can be gained when data can flow through the enterprise electronically are automated decisioning and workflow; as well as integrated production systems, external data sources (e.g., automating requirements gathering) and internal data (e.g., claims and policy data).

STP actually helps an organization "leverage institutionalized business knowledge," noted Bill Dochterman, VP, product management, Insurity. "It automates the flow of business and exception processing [by] applying the right resource to the right transaction at the right time."
At Swiss Re, an organization that has been traveling the path to STP through initiatives such as development of a single electronic workflow for data and a each business has single integrated systems path for each line of business, the benefits have included reduced expenses, improved compliance and transparency, and more organizational flexibility, reported Mike Rubin, SVP, technology.

Looking ahead, Rubin said, Swiss Re is looking at opportunities to expand the current platform "to include more of a value chain, and add external data to internal data," as well as consolidating processes in a services-oriented architecture (SOA) environment, and "aggregating all data for better management and analytics."

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