How to overcome barriers to adoption of advanced technology

Insurers must adapt to remain competitive and relevant in today’s rapidly evolving digital landscape. However, a recent report on digital modernization in the insurance industry shows that legacy systems and infrastructure are hindering technology adoption.

The the report was produced by EPAM Systems in partnership with London Research. The survey included 200 insurance executives from various providers, including commercial and consumer lines.

The report provides insight into the priorities of industry executives, providing practical strategies for insurers to overcome the challenges of legacy systems and infrastructure. By addressing these obstacles, insurers can stay ahead of the competition by unfettered implementation of emerging and relevant technologies – namely Gen AI.

Potential applications of Gen AI in different lines of insurance

In recent years, the pace of technological progress has accelerated, from the birth of the Internet and fast mobile data to the public cloud and the modern application stack. Gen AI now has the ability to unlock the value of an insurance company’s data heritage to address common insurance challenges and open new opportunities.

In the consumer insurance industry, the potential of Gen AI includes supporting customer self-service, allowing customers to receive new quotes, approvals and renewals without interacting with a call center agent. Advanced chatbots can advise the customer and automatically process the identity and contact details from their driver’s license. With voice interaction expected to arrive soon, the concept of a keyless quote is becoming a reality on the horizon.

Other important use cases in consumer insurance include First Notification of Loss (FNOL) guided registration. In this scenario, technology could automate tasks from customer and policy identification to coverage checks to initial claims assessment and even best actions and full automation of claims processing.

In commercial lines of insurance, Gen AI could streamline referral processing and enhance underwriting support, including assimilation, risk aggregation, deep risk analysis, renewal comparisons, suggested wording, and so on. This technology could also complement broker risk research, writing quote sheets, managing the common query loop and validating premium invoices. However, in reality, nearly half (45%) of insurance companies surveyed said legacy technology systems and infrastructure are the most important barriers to adopting digital tools and new ways of working. Also, 34% admitted that legacy technology prevented them from quickly bringing new products and services to market.

Until insurance companies, whether consumer or commercial, can move beyond legacy systems and infrastructure, the potential business benefits that Gen AI can generate will remain out of reach.

Considerations for Retiring Legacy Technology

While legacy technology has undoubtedly served markets well over the years, it is undeniably holding the industry back now. Depending on the business and area of ​​expertise, there are different approaches to dealing with inheritance.

Re-platforming is part of a larger digital transformation that will require many key decisions. Insurance companies should consider transformation more broadly to set themselves on the right path for future adaptability. They should ask themselves various questions: How are our customers’ needs evolving and how can we build customer trust while improving processing time? What are the relevant industry trends? How will our product and channel strategy evolve? How can we provide valuable services at a lower cost? How can greater automation be achieved where it is most needed? And can experts across the organization be given the right tools to improve their efficiency and effectiveness?

Also, when decommissioning legacy systems, it’s helpful to identify bottlenecks that need to be addressed. Of course, different departments will have different views, whether in product marketing and distribution, channel services, underwriting strategy and risk selection across lines and jurisdictions, or in premium booking and claims management. Modern leaders take more of a product management approach to navigating these complex transformations.

Another important aspect is that insurers have built their organizations around the previous generation of policy administration systems and claims platforms. When the system is changed, it is necessary to review not only the organizational impact, but also the broader opportunities that become available with the latest generation of technology enablement.

Data also plays a critical role in replacing legacy technology and systems with new data-driven technologies such as Gen AI. One of the most significant effects of legacy systems and environments is the challenge of data flow integration and efficiency. Given their value, there is a slow but growing recognition that data-first thinking and data products are becoming prime considerations. However, progress remains slower than many had hoped.

While companies understand the value of good databases, proper data management, and developing an ecosystem of data services, there is still not enough progress on the basics in the insurance industry, which is a naturally data-rich sector. By implementing the right data capabilities, insurers are better positioned to take advantage of these evolving digital technologies.

Finally, when thinking about how to modernize, converge and simplify your property, it can be tempting to oversimplify the challenges. For example, many have asked, “Why do I need more than one policy management system?” Multinational insurers and those in different markets with different types of business will strongly need specialized capabilities that are not available on a single platform. The journey of transformation often requires hard and detailed thinking. Achieving simplification and compliance in business is a good thing, as long as it doesn’t hinder market essentials by misunderstanding future needs and opportunities.

Moving beyond legacy technology

As a relatively emerging technology, the potential of this wave of Gen AI has a journey ahead, with major capabilities released every six months or so. Realizing its value, an insurance company will be more complex in changing its business process, educating users, organizing data, applying domain-specific knowledge graphs, and so on, but the potential here is significant.

Insurance companies should start experimenting and familiarizing themselves with these technologies to capitalize on future opportunities. Crucially, they must prepare the foundations of their data heritage for future technology-driven business opportunities.