Customer Success - Gen Re

December 19, 2014

Gen Re, as a direct reinsurer, is one of the leading Property/Casualty and Life/Health reinsurers in the world. They are represented in all major reinsurance markets through a network of more than 40 offices, supported by over 1,900 employees worldwide.

Maryanne Mancini, RAS Product and Data Lead at Gen Re, shares the challenges they faced during their data migration and the important role BackOffice Associates played in improving their overall data quality.

Video Transcription

My name is Maryanne Mancini and I work for the Gen Re Corporation.

Our team just completed phase one of a system implementation that migrated data from our legacy reinsurance administration systems to package software. My role was to manage a team that was responsible for functional requirements in data migration.

Our business is based on our data. The opportunity to make sure our data was correct, consistent and complete was a high priority for us. This project brought data into the new system from 27 different legacy data sources.

In some cases we found that our data was redundant, and we had to determine what the system of record was for that data. In other cases, data was missing from the legacy system that was required by the new system. In those cases we needed to look them up in our document management systems and get them from our files. In other cases we had found out that we had collected data in the past that wasn't relevant, we had our work cut out for us.

We're a reinsurance company, not a software company. We needed a partner to come in with a set of best practices, that can help us through the challenges we would face in any migration.

BackOffice has helped us improve our data quality in numerous ways. The load early part of the load early, load often methodology gave us an early view of the data in the system and indicated potential challenges we would have. BackOffice was able to quickly produce reports that detailed data that needed to be cleansed or data that couldn't load for one reason or another.

All this and more helped us improve our data quality. 

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