Project cost overruns. Implementation delays. Processing problems, such as missing billing statements, late commission payments, wrong policy information. These are just some of the risks insurers run when undertaking a data conversion project, and unfortunately, there are many ways data conversion can go awry.

“There's a lot of dirty work that needs to be involved in going into the data, cleaning it up, and doing the mapping between the current and target format,” says Todd Eyler, vice president in the insurance sector at Gartner. “Most of the [data conversion] problems and costs come in those areas.”

While most data conversion projects are driven by system conversion projects–such as legacy system replacement or post-acquisition system consolidation–there is a host of other reasons insurers undertake data conversion. “As companies look toward business intelligence tools and need to feed a data warehouse more efficiently, they need cleaner data in standard formats,” Eyler adds. Complying with privacy requirements (such as converting Social Security numbers to other identifiers), meeting format requirements (such as for HIPAA EDI transactions), delivering data in different formats to different customer service channels, or even undertaking stand-alone architectural projects all are initiatives involving data conversion that carry business risks.