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Enter Centric: No Hurdle Can Stop Growth
The carrier knew they faced a unique problem: Get data out of the mainframe while trying to lower the load on the system — not increase it.
We spent 14 months building a proof of concept (POC) that showed that we could successfully consume data from the mainframe without increasing load and transform that data without the missing copy books. Once we successfully built the POC, we proceeded to implementation.
Our experts applied a progressive approach of implementing collections of use cases associated with a core subject area such as claims or policy over two to four months. This resulted in regular value demonstration for end users.
For example, the client received four new dashboards covering seven use cases in the first three months. See the sample screenshots below.
Additionally, we created a semantic layer as an in-memory columnar data store, which provides a single source of truth that feeds all needs into Microsoft Excel, Power BI and many other tools. We created an enterprise data warehouse that included policy, claims, additional expenses, and reinsurance – reserving information that allowed for a holistic view of profitability.
We designed this new solution in Azure, which marked the client’s first foray into cloud computing, and our team provided hundreds of hours of data analysis to help map thousands of data elements into various destination tables.
The Result: A Data Warehouse Fit for The Test of Time
During our 14-month deployment and four major releases, we built a platform that relies on several accelerators, including code automation to generate SQL server integration services (SSIS) packages, data models, data definition language, and data acquisition frameworks. These modernizations now allow us to generate code patterns in a hundredth of the time it would have taken previously.
With this new platform, our client can now:
- Release game-changing analytics based on monthly milestones at the 3, 6, 10 and 14-month marks.
- Provide monthly analyses for profitability at a level of detail not previously available.
- Tighten management of the claims processes.
- Provide better oversight of underwriting outcomes.
Overall, we implemented a platform that provided monthly profitability updates, which was previously limited or unavailable. With tighter management of claims, the new platform allows for a better understanding of different markets for better profitability for years to come.
Our client is now more data-driven regarding decision-making, marketing, business and renewal processing. Also, the company’s data is now more readily available and has become a visual resource instead of the spreadsheets they used in the past.
Final Thoughts
In the end, our client has prepared themselves for the AI revolution that has come. With the advent of large language models and rapidly advancing AI, having a modern, cloud-based data platform has become table stakes.
As a carrier, you are not alone if you see yourself in our client. Don’t suffer in silence. You can take strategic steps to make incremental progress toward modernizing your data platform.