Moving Beyond Data Lakes

With all the industry buzz around generative AI, P&C and Specialty insurance carriers are scrambling to evaluate how and where to best apply this emerging technology. But is the insurance industry ready for this next wave of innovation, or are the same limitations that have limited real progress in the past still a cause for concern? 

“Without investing an appropriate amount of time into getting data into the format the business can actually use to measure its effectiveness and progress toward organizational goals, a data lake is simply a lake/sink. This often renders future application builders helpless – the data lake contains hundreds of thousands of data points, but the relevant data they need remains inaccessible.” 

– William Steenbergen, CTO and Co-Founder, Federato

Recent innovations in data querying, caching, pipelining and transformation should give insurers reason for optimism. In fact, Steenbergen believes that these innovations in underlying data architecture are as exciting for the insurance industry as the changes we’re seeing in AI – if not more so. This article looks at how federated data graph technology is helping insurers move beyond data lakes to better harness their data for innovative applications including AI-powered underwriting and portfolio management solutions.

In an interview with Carrier Management, Greg Puleo, vice president, digital transformation at QBE North America, explained the power of a modern underwriting application that leverages an underlying federated data graph: “We now have the chassis that we can start to bolt other things to, and all those other data providers now just become an API [application programming interface] integration seamlessly in the workflow. The underwriters can make better decisions using that data without having to do extra steps.” 

“The carriers that will gain a real advantage from AI will be those that can harness their underused data investments to drive meaningful advances to core insurance processes. Federated microservice-based architectures and data graph technology provide insurers with a viable alternative to data lakes as a means of tackling legacy tech debt and bringing much-needed agility and data-driven innovation to insurance.”

– William Steenbergen, CTO and Co-Founder, Federato

Key Takeaways:

• One of the core problems that makes it difficult for large carriers to innovate with their data and IT strategy is the scattered architecture that is the logical result of growth and acquisitions over a long time. To address the challenge, many insurance IT leaders and consultants propose a central data lake or enterprise data warehouse that gathers all the data into one place. But it’s extremely difficult to execute a data lake or data warehouse project, and it usually takes years and hundreds of millions of dollars to implement.
• There is an often-overlooked alternative that stems from the microservices architecture that many startups have adopted: a federated data architecture. Instead of moving all the data from the different sources into one central location, a query layer is built on top of existing data sources and only gathers data upon request. What makes this approach much easier to set up and maintain is that there is no need to configure the architecture for storing and maintaining a large amount of data.
• A real-world insurance use case of how forward-looking carriers like QBE North America are leveraging federated data graph technology to build out a modern data architecture in lockstep with efforts to build new underwriting applications and workflows.

Read the Full Article

For more insights on the link between underwriting technology and talent, read the full Insurance Thought Leadership article here.