Consider the challenges faced by many global Tier 1 life insurance companies that experience significant growth by pursuing an acquisition strategy. Typically, when they purchase another insurance company or a book of business, those policies come across to the acquiring organization in the original company’s Policy Administration System (PAS).
The acquirer may not put new business into those legacy PAS systems, but will run a closed book of business, in which they administer the lifecycle of the in-force policies.
Years of acquisitions can result in the insurer’s IT landscape evolving into a complex environment with a multitude of policy admin systems and a wide variety of technologies of varying ages. Across the entire technology stack, the organization is forced to contend with a high degree of technical debt.
This complexity would seem to lead to a logical case for PAS consolidation. However, the cost and complexity of migrating legacy data from multiple outdated systems is often a barrier.
The case against consolidation #
Since many vendors structure their PAS licensing fees according to the in-force policy count, the business case to migrate those closed books of business to a new system may not be obvious since they will incur new licensing costs for the migrated policies.
The high cost of licensing when all policies are consolidated onto one system can be a restriction to the business case for PAS consolidation, even though from a business and technology perspective, consolidation would make a lot of sense.
The Status Quo solution #
The insurer may choose to run the policy admin systems as they are. However, over time, this strategy is not scalable as the insurer must contend with ever increasing complexity, which leads to poor customer experience as they become more difficult to support.
To address the resulting inconsistency, many insurers attempt to adopt an internal data strategy in which they would pull data from all their policy admin systems into a data platform. Rather than attempting a one-time migration, many insurers decide to copy data from every PAS into a massive data platform where ETL (Extract, Transform and Load) transforms are performed daily to present the data as a single system to their admin team for the purposes of reporting compliance payments.
In many cases, insurers build a lot of functionality off the data platform to minimize usage of the PAS by promoting use of the data platform. The system works well but the challenge is that the data platform itself becomes monolithic and expensive to maintain. The daily extract approach limits accuracy of real-time data and is even more expensive to run than the PAS.
The resulting cloud costs can be enormous, and the bespoke data platform requires a lot of data professionals and highly skilled staff and vendors to keep it running efficiently.
A new PAS solution to legacy data challenges #
Equisoft/manage is a PAS solution which uses Oracle’s OIPA as its core and provides UCT insurance data migration and modernization capabilities, along with the OIPA Data Staging (ODS) platform as an out-of-the-box data solution.
The Equisoft/manage solution is a Platform as a Service (PaaS) product to help minimize end-to-end platform maintenance costs. Beyond the OIPA core, Equisoft/manage delivers a wide variety of extensions, integrations, and enhancements like the ODS data platform, which can greatly reduce the cost of addressing complexity via an in-house data platform.
OIPA data structure and /manage enhancements. #
OIPA is a revolutionary policy admin system that is built on a highly normalized data structure. Equisoft has implemented OIPA for over 200 customers across North America and around the world, including Australia, Asia and Africa. Across all those hundreds of implementations Equisoft has never required an OIPA data schema change to be made. Every customer has the same schema because OIPA has this powerful data structure that can support any requirement with no database change necessary, resulting in end-to-end simplification and reduced cost.
The importance of a flexible data schema #
The reason why a flexible data schema is needed is because of an increasing demand for analytical data structures in which the data can be consumed for compliance, reporting, analytics, customer insights and Artificial Intelligence (AI) applications.
In practice, the flexible schema underpinning OIPA has been able to accept anything from hundreds of insurers without any changes. The positive implications for cost and business capability cannot be overestimated as the flexible design simplifies downstream connectivity and end-to-end integration, which promotes good end-to-end architecture.
ODS and optimised data structures #
Typically, during the life of a PAS, a company would need to make multiple business rule changes, each one requiring the addition of another field of data. When a new field is entered or a field changes, then data complexity in the platform is created. In any given column, data may exist after the date of the field change but not before, or the data structure might have changed at some point in time. These types of inconsistencies make it harder to work with data and connected systems, increasing the cost of maintenance.
The evolution of data over time creates the need for things like data lakes, data marts, warehouses, or vaults. However, with the OIPA data schema from those second-order solutions are not needed because the underlying schema never changes.
Highly normalized data can create further challenges—for instance, if a report needs dozens of dynamic fields of data, but those fields are not fixed columns, then that means the structured query language (SQL) may now need to involve dozens of joins back to the same data set, making the SQL ungainly, non-performant and incredibly hard to maintain.
Both approaches to changing data definitions have drawbacks that make complex reporting and other data extracts a challenge. However, the Equisoft/manage platform has an ODS extension with complementary technologies that work together to fill that gap.
In effect, the ODS allows OIPA to retain an unchanging schema, but provides a rich staging platform for reporting and other downstream systems. This purpose specific and optimised data structure means an insurer receives all the benefits of a constant schema without the drawbacks of overly complex or resource intensive SQL.
The out-of-the-box product does all the data transformation and deals with changing business rules in a seamless and low-maintenance way, so that teams of data engineers don't have to manage this complexity in a data lake, warehouse, or any other complex data platform.
In the end, this requires fewer resources and is a far less costly solution to data management and integration. The solution is not intended to eliminate the business case for data platforms, but instead provides a much more simplified basis for any downstream systems since a lot of the complexity created by changing logic is removed.
Conclusion: simplifying data platforms #
For carriers looking to solve the challenges created by data hosted on multiple legacy systems, the integration capabilities created by ODS with automatic data shaping functionality provides a simplified basis for data management.
This data staging solution can fit anywhere in a company’s technology stack and can be used stand-alone or integrated into the enterprise’s own data platforms. It is a scalable, automated, and strategic solution which reduces an insurer’s costs and IT complexity.
