You Need to Validate Your Data: WTW Are On It

Willis Towers Watson has launched an updated version of its DataValidator technology, which helps P&C and Life insurers to use their data more efficiently by validating, cleansing and transforming data for use in financial modelling and reporting processes. 

Timely access to good quality data continues to be one of the most difficult challenges facing the insurance sector due to struggles with legacy systems and the demands of IFRS 17 and other fast-evolving regulatory timetables. For insurers under pressure to achieve improvements in processes and efficiency across the whole enterprise, the enhanced features of DataValidator 2.2 offer material benefits, which include:

• Performance leap: With processing speed now between three and 20 times faster, DataValidator 2.2 enables clients to deal with much greater volumes of data in a more efficient way.
• Deeper integration with Unify: The process of combining both Willis Towers Watson’s DataValidator and Unify – its business process management, governance, and automation technology – has become more streamlined, allowing users to more easily build end-to-end business processes, deeply embedding data validation and transformation into insurers’ workflows.

Tom Beasley, Director and Product Lead for DataValidator, Willis Towers Watson, said: “DataValidator allows insurers to streamline the production of their data for actuarial and risk analytics calculations. The software solution is user-friendly, fitting neatly into any existing data process, and helps ensure high-quality data. This generates significant efficiency gains by capturing issues early in the process, thus avoiding unnecessary rework and manual adjustments.”

According to Willis Towers Watson, these updates represent another step towards intelligent automation and will enable Unify to quickly and automatically extract key data quality information from DataValidator. This latest release also ensures a consistent and easy-to-use approach for data validation, removing reliance on manual legacy approaches, while at the same time providing comprehensive data quality assessments and thorough audit trails necessary for mandatory governance and audit readiness.