End to End Data Quality Across the Enterprise
This top 10 property and casualty insurer has millions of customers and a special focus for bringing leading-edge technologies to compete in the automobile insurance market.
The insurer’s long history, operational scale and growth have been supported by legacy systems that grew in size to tens of millions of lines of source code. Newer open systems are displacing older ones, but they needed to integrate with a wide variety of other systems spanning both older and newer platforms. Numerous information risk points included data translation, synchronization, communication, complex business rules, data warehouses, regulatory reporting and calculations.
The insurer needed a solution that could scale to perform in its highly information-intensive enterprise. In addition, a wide variety of analysis options were needed to enable validation of content in various formats, from different platforms and databases. The insurer needed the ability to track transactions from beginning to end through the enterprise – from policy quotation through various internal systems, to the general ledger, and to printed documents to be mailed to customers.
With a wide variety of systems, the insurer needed a non intrusive implementation for policy issuance, billing, cash management, claims processing, financial reporting and many other financial and operational processes. In order to support a segregation of duties policy, they needed business rules designed, implemented and executed independent of their application development teams.
Since thousands of business rules needed to be authored and maintained, the selected data analysis solution needed to be easily sustainable, flexible and easy-to-learn and use. The insurer needed to be able to quickly codify information integrity rules to match a complex array of regulatory and business rules. They also needed the flexibility to integrate with existing data formats, platforms, systems and applications.
Read more about this top 10 property and casualty insurer and how they tackled legacy systems that grew in size to tens of millions of source code lines and newer open systems that needed integration with old and new platforms.