(Image source: Celent.)
Technological progress in the insurance industry has brought significant improvements for the front and back office, but it brings with it the pressure to keep up: the more that business processes improve, the more expectations and competitive pressures rise. Insurers often reach a crossroads where they feel the need to undertake a major transformation in order to bridge important gaps in capabilities. However, that may not be necessary according to a new Celent (Boston) report, Building New Insurance Capabilities or Bridging Functionality Gaps, authored by Principal Analyst Nanda Rajgopal.
In writing the report, Rajgopal drew from his experience participating in major transformation efforts at carriers run by business or operations executives. The companies found themselves unable to expand or having to turn down business or having other operational issues because of the limits of legacy systems. To be able to meet their objectives, carriers would undertake a complete selection process and legacy replacement.
Insurers today have systems portfolios that can include legacy applications and modern systems—many of which are now available as software-as-a-service, Rajgopal writes. Many also rely on business process services. The resulting combination of modern systems, legacy applications, outsourcing and SaaS models, creates a complex systems environment.
“Regulatory and compliance requirements, which can vary depending on the state or country in which insurers operate, can add considerable complexity to their operations,” Rajgopal’s report continues. “As a result, when insurers need to add new functionality or bridge a process gap, it can become a complex undertaking that often requires major transformation initiatives. However, with the emergence of new technologies and innovations from InsurTechs, there may be more efficient ways for insurers to quickly add functionality.”
That opportunity comes mainly from three technology areas, according to Rajgopal:
- Low-code/no-code (LCNC) development platforms
- Artificial intelligence, including machine learning (AI/MI)
- Serverless technology
LCNC are designed to enable non-technical users to develop applications by using a visual interface that works through a drag-and-drop approach, enabling the assembly of functions. “These platforms empower users to create applications without the need for extensive coding expertise, enabling them to drive innovation and meet business requirements more efficiently,” the Celent report says.
“Using low-code/no-code platforms, a business user can create a system of engagement—a front-end system—without IT intervention,” Rajgopal adds. “The technology is readily available, with many vendors who have done a great deal of innovation.”
Artificial intelligence—probably the hottest technology area in terms of industry buzz and experimentation on the part of insurers—has a large and growing menu of use cases for insurance functionality, according to Rajgopal, including accessing legacy systems for decision making or to extract data or rules.
“From the perspective of adding new functionalities or bridging process gaps, AI models can augment LCNC platforms by automating business processes, retrieving data for analysis, and providing decision support during process execution,” Rajgopal writes. “They can also run analytics to generate insights from new initiatives, process unstructured data using natural language and OCR [optical character recognition] technologies, integrate with and auto-process within legacy systems, and perform other valuable tasks that go beyond traditional or non-AI technologies.”
The Celent report describes the third of the three enabling technologies, serverless computing, aka Function-as-a-Services (FaaS), as a modern cloud computing ecosystem offered by major cloud providers that provides a rapid development environment to build applications in an agile manner without the need for a server. “Serverless computing is scalable and cost-effective, simplifying the application development process,” the report continues. “It is ideal for situations that require code development to add complex new functionalities or fill process gaps. AI models can also be deployed on serverless technology.”
This technology aids in somewhat more complex tasks, Rajgopal told Insurance Innovation Reporter. “In the old world, you needed servers and infrastructure to build apps. But now, if you’re in the cloud, you can create apps on demand without IT support.”
Foundation for Innovation: Data First, and Cloud Technology
Being able to innovate and close functionality gaps without core system transformation presents a significant opportunity to insurers, but the ability to use the three technologies cited comes with prerequisites, according to Rajgopal. “You need the foundation of a sound data strategy because everything will depend on it,” he cautions. “For example, if you want to train your AI models, you’ll need absolute mastery of your data or you’ll be faced with a garbage-in/garbage-out problem.”
Rajgopal has stressed the importance of building on a foundation of data mastery in earlier reports, including Focusing on Data-First to Transform (Sept. 2023) and Data-First Transformation for Value Realization in Insurance (April 2023).
“Having a unified dataset in the cloud is an essential component that lays the foundation for seamlessly connecting other tools and technologies, which will help bridge gaps and add new functionalities,” he writes in the most recent report. “Many tools and emerging technologies that are essential for filling functionality gaps or building new capabilities are cloud-based. Additionally, since many core system providers, LCNC platforms and AI technologies run in the cloud, we suggest that insurers formulate and execute their data strategy in the cloud.”