As we approach the announcement of the Novarica Impact Awards in the fall, we will be highlighting one Impact Award nominee each week on our blog. The Novarica Impact Awards are voted on by over 300 members of the Novarica Insurance Technology Research Council, making them the only purely peer-reviewed awards program in insurance technology.

Many of the 2016 Impact Awards nominees cited cross-functional teams, with resources familiar with multiple business areas, and the use of Agile methodology as keys to a quick and successful delivery. Many projects focused on consolidation and speed, combining disparate data silos and core systems to enable centralized access and real-time querying.

This week, we look at a MetLife project that enabled real-time interactive views of data across multiple platforms.

MetLife needed real-time access to derivatives and associated risk data from multiple systems and data sources. Metlife’s goal was to use advanced analytics to manage liquidity and optimize the use of highly liquid assets. The project employed Agile methodology and a framework for program governance, both of which the team cites as critical to success. Resources with knowledge spanning technology, business domain, and industry standards were also crucial. The 17-month initiative and its resulting system freed up over $575 million of highly liquid assets and cut the liquidity retention period from 30 days to 5. The time required to aggregate data from multiple sources was reduced by 65%, and the project ultimately saved MetLife more than $5 million.

Mitch Wein will be moderating a panel on Metlife’s case study at Insurance Analytics 2016 on October 20 in New Orleans. For more detail on this project and more than 30 others, including cases from GuideOne, Trustmark, Unum, and Amerisure, see Novarica’s Best Practices Case Study Compendium 2016.

This blog has been reprinted with permission from Novarica.

The opinions expressed in this blog do not necessarily reflect those of Insurance Networking News or SourceMedia.

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