Insurers’ Progress on Emerging Technology: Novarica Study
Insurers’ Progress on Emerging Technology: Novarica Study
Beyond digital transformation based on largely proven technology, insurers must patiently explore the capacity of emerging technologies, such as AI and Big Data, for reshaping business processes over the longer term.

During 2020, the pandemic showed insurers the strength of their existing infrastructure as they almost instantaneously transitioned to remote work. It also encouraged them to make progress in their digital journeys, particularly with regard to customer- and agent-facing capabilities. 

What those two things have in common is that they depend on proven technology. In a new report, Novarica looks at insurer’s progress in emerging technologies. The study, “Emerging Technology in Insurance: AI, Big Data, Chatbots, IoT, RPA, and More,” finds that while some may be narrowing their innovation focus in anticipation of a more economically constrained 2021, the industry generally will be gaining ground in their profitable use of new technology.

Conducted during the last quarter of 2020, the study was based on a survey and conversations with 110 insurer CIO members of the Novarica Research Council representing a broad cross-section of property/casualty and life/annuity insurers of all sizes and across most lines of business. Novarica gauged the status of emerging technologies within its “Three Levers of Value” framework, which asserts that technology creates value in one of three ways: helping insurers to sell more, manage risk better, or achieving greater operational efficiency.

Though emerging technology may play a role in digital strategy, it doesn’t necessarily depend on it, notes Matt Josefowicz, President and CEO of Novarica, and co-author of the study along with Harry Huberty, Research Director and Chief of Staff at the Boston-based research and advisory company.

“Digital Strategy uses well-established tools and capabilities that have been part of insurers’ tool kits for last five to ten years,” says Josefowicz. “There are some emerging technologies that may play a part in the digital strategy ramp-up—certainly, chatbots, and to lesser extent, RPA, are more about internal customer experience. We also see a great deal of enthusiasm for no code/low code development tools, and that is being driven by the need to create digital experiences.”

The use case and path to value for these capabilities is clear, Josefowicz acknowledges. However, he says, more technically sophisticated and powerful technologies such as artificial intelligence (AI) systems and Big Data analytics are a step removed from delivering value, he stresses.

“If you’re experimenting with AI or Big Data analytics, it’s a multiple step process to get to business value,” Josefowicz elaborates. “The long-term value may be much greater if you’re affecting your ability to analyze risk or target customers more effectively or detect fraud. But the complexity of realizing that value is also greater.”

Being some number of steps from delivering business value may serve as a definition of emerging rather than proven technology. Novarica identifies three factors that determine the growth rate of emerging technologies:

  • How easily the technology is understood,
  • How readily it can be deployed and integrated with existing processes, and
  • How clearly the value it creates can be measured and communicated.

Technologies like chatbots and RPA, which hit all three metrics, have had rapid growth,” the study states. “Technologies like big data and artificial intelligence have grown more slowly, as they take longer to understand and may not be as easy to drop into existing business workflows.”

“If you license a chatbot tech or RPA you’re probably creating value within several months because the application is use case-specific, simplifying customer experience or internal process,” comments Josefowicz. “Even if you don’t quantify the value directly, the value is visible.”

RPA has an interesting status as an emerging technology that essentially a stop-gap measure to bridge the lingering discontinuities of obsolescent systems. “RPA is a wonderful Bandaid solution if you have a bunch of disjointed systems and process currently causing a lot of user pain,” Josefowicz says. “It doesn’t fix the underlying problem, but it certainly masks the symptoms.”

To the extent that RPA corrects the deficiencies of legacy systems, it could be regarded as a temporary solution category—but in the insurance industry that could still mean decades, Josefowicz says. As insurers’ systems environments continue to evolve, RPA faces emerging challenges of governance and documentation, he cautions.

“As many RPA bots are built, as those underlying systems change, the bots don’t work anymore,” Josefowicz says. “So RPA needs to be governed and documented almost the same way as custom development, even though it’s more rapid to deploy.”

The Novarica study also identified AI and big data as areas or intense activity for carriers, noting that “Deployment has increased for most capabilities; these remain the most-piloted technologies for 2021.”

 

AI: Buy vs. Build

More often than not, this means the adoption of AI-based tools offered by vendors, according to Josefowicz. “We’re seeing the incorporation of AI powered capabilities into a wide variety of tools insurers are taking advantage of, but very few insurers are doing their own artificial insurance development,” he elaborates.

 

“There are some in high-volume personal lines where you do have self-learning algorithms incorporating feedback and either modifying themselves or suggesting modifications,” Josefowicz adds. “But when people think about AI in insurance—image recognition, natural language processing, voice recognition—those are capabilities that are incorporated into applications that insurers are buying rather than building.”

 

Life Insurers Investing in Digital Differentiation

A third key finding of the Novarica study was life insurers have a narrower pilot focus than property/casualty companies. In the life and annuity segment, the study notes, “Less proven technologies are seeing less experimentation as life insurers balance analytics investments against new priorities for digital experience.”

What the finding amounts to, as Josefowicz paraphrases, is that life insurers are very busy investing in foundational digital capabilities using proven technologies. “They’re less experimental with some of the newer technologies because they’re trying to solve a very urgent problem,” he expands. “Many life insurers have under-invested in digital during the last five to 10 years, and now in the pandemic environment they find that’s an important differentiator.”

“We’re certainly not faulting life insurers for not doing more wearables pilots when they still need a fully robust customer portal,” Josefowicz stresses. “We think their priorities are exactly in the right place.”

 

Patient Rethinking of Business Processes

For both the life and property/casualty industry segments, the Novarica study stresses that insurers should understand that gaining maximum value from emerging technology is a matter not merely of “repaving the cow path,” but rather of patiently reimagining business processes. The study also stresses that vendors need to balance technological process with practical application. “Solution providers who develop these technologies should likewise be aware that the ultimate success of their products may depend not on how powerful they are but on how useful they can be,” the study concludes. “Rather than focus on their product’s capabilities, they should focus on helping insurers understand how the product can transform current business practices.”

Source: Insurance Innovation Reporter

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