Are the industry’s data systems ready for change?
by Dheeraj Pandey and Upendra BelheMr. Pandey is an Engagement Manager at EXL Service, a provider of data analytics solutions to financial organizations, including L&A Insurance firms. Mr. Belhe is the president of Belhe Analytics Advisory, helping businesses achieve business outcomes through data-driven insights. He serves as a strategic adviser to EXL Service.
The Life Insurance and Annuities (L&A) industry is expected to experience steady growth in the US market. Yet the question remains whether they are ready to capitalize on this opportunity. With aging data architectures and the proliferation of smart devices and the emergence of network economics, insurers need to take a long hard look at how current solutions are meeting the needs of the organization.
Scalable, digital product systems allow insurers to revisit their product innovation process regularly, often resulting in a faster time to market for rate changes and new products. Those with up-to-date IT architectures are also more efficient than their peers with traditional IT architectures. For instance, the total number of policies per full-time equivalent they achieve is more than 40 percent higher. Additionally, those with data-based solutions are better at advancing and supporting analytics while improving customer experiences.
As a result, some of the progressive insurers are either adopting a new data architecture or making changes in their existing systems. Therefore, future-looking solutions must focus on accuracy and easy linking between the various data systems to achieve a market-leading stance.
Legacy systems are crumbling under the sudden surge in demand for digital services. They have become too complex and cumbersome. Often the focus of modernization is confined to cost reduction and improving efficiencies while ignoring business goals and new tech. They must overcome:
- Fragmented and siloed data, data accuracy issues, and data quality issues causing bottlenecks and inefficiencies.
- Internal processes creating challenges around efficient data migration, ingestion, scalability.
- Evolving regulatory changes.
- The pandemic shifting consumer expectations towards carriers with strong digital capabilities.
To deal with these issues, some carriers are making internal changes by backing insurtech startups or establishing innovative labs, while the rest are hesitating.
A New Age Architecture
From competing priorities to regulatory concerns to concerns about disrupting the customer experience, companies can easily identify reasons to simply service existing data systems, which creates a barrier to driving innovation. To position for the future, it is essential to overhaul the archaic systems of traditional L&A carriers. This does not have to be implementing a completely new system. Instead, through careful planning, legacy systems can be modernizing by building on existing data and IT resources. This allows for easier introduction of new capabilities while simplifying existing approaches. Just implementing a single strategy creates the opportunity for further expansion. Consider:
- Transitioning from on-premise to cloud-based platforms. Cloud-based platforms provide faster turn-around times for data-intensive operations. This shift enables L&A carriers of all sizes to deploy and run data infrastructure, platforms, and applications at scale. Plus, it allows an array of smart data migration tools to be used for transitioning legacy core systems to a cloud-based setup, which helps ensure the accuracy of the data being migrated and avoids data quality problems later on.
- Moving to real-time data processing. This move can help improve business efficiencies and customer experience. With real-time data messaging services, insurers can offer more personalized services and alerts as well as improve quote turn-around times. This ensures faster claims processing and triaging, which goes a long way in establishing customer satisfaction.
- Evolving from pre-integrated commercial solutions to modular, best-of-breed platforms. In today’s marketplace, carriers plan to migrate towards a highly scalable IT infrastructure that uses open-source components. The idea is to be able to integrate new technology without disrupting other parts of the data architecture. This modern and more versatile approach is being made possible by data pipelines, API-based interfaces and analytical workbenches. These technologies will help to phase out the primary core systems steadily without disrupting the carrier’s day-to-day activities. This solution is well suited for individual L&A carriers who don’t have the financial leverage to migrate to an all-new IT and data architecture.
- Using decoupled data access. In this environment, L&A carriers allow stakeholders such as agents, underwriters, actuaries, contact-center executives, etc., to access current data via APIs, while also ensuring greater control and security. Incorporating such an operational and technical change improve the overall customer experience by creating a culture of informed and efficient stakeholders unlike a traditional setup where even common datasets were restricted to a select few. Technologies, such as an API management platform and a data platform to buffer transactions outside of core systems can be leveraged to make this shift.
- Adapting domain-based architecture. Moving away from a conventional data-warehouses/data-marts architecture to a function-specific, data-factory architecture that can be tailored and adapted to the context of the incoming data-requests is what carriers can strive to. Data Factories can help create an end-to-end data management capability, from intake to reporting, which would enable quick data-driven decision making at every stage and can reduce data management costs by up to 25% for some of the top carriers.
- Implementing flexible, extensible data schemas. Unlike traditional RDBMS-driven database-schemas, L&A carriers should aim for a flexible schema that facilitates orchestration of data from a variety of different sources. This can include different types of NoSQL databases such as key-pair, document and graph databases, or plain unstructured data. This is specifically useful for carriers in conducting actuarial analyses where a significant amount of time is spent in data-engineering efforts. A flexible, extensible schema can lead to ease of data wrangling, speeding up the modeling effort.
Transformation Challenges/Problem Areas
We are cognizant of the fact that the above recommendations come with some challenges.
- Siloed Customer-Data In Legacy Systems: Ensuring data consistency in such a scenario while updating/migrating the core systems is a major bottleneck in transformation program which require a meticulous effort.
- Customer service risks with “always on” customer-facing systems: These types of systems need to be handled with great care and detailed customer service considerations when they are replaced.
- Ensuring Regulatory Compliances: Before aging core systems are replaced, all existing regulatory controls must be present in the new systems.
- Program fatigue: Like other large-scale, multiyear corporate initiatives, we have seen core modernization efforts resulting in program fatigue, which could be a result of lengthy change process.
- Competing priorities: Many a times’ modernization efforts can disrupt progress on other business priorities for months — or even years. That impact can make core modernization efforts unpopular with business sponsors who would rather invest time and money in their own innovation projects.
A structured methodical approach that leverages relevant industry experience and partnerships is required to overcome the above challenges.
L&A carriers aspiring to stay ahead in a highly competitive marketplace, and ride the insurtech boom should consider the merits of transitioning/upgrading to modern data architectures. While there are many ways to begin a process of upgrading a carrier’s data architecture, it is important to ensure it is done with a structured methodical approach that leverages relevant industry experience and partnerships. This type of Impactful data system modernization initiatives follow an approach that encourages the incorporation of new operating models in the L&A space with drastic improvements addressed from a customer and IT point of view.