AI projects in Insurance are Moving from Pilots to Business Programs | Sherpas in Blue Shirts

Posted On May 4, 2018

Insurers are rethinking their business ethos to become protectors instead of payers. The insurer of the future is aiming to develop a customer-centric value proposition. Carriers are looking at developing innovative products that are contextualized to meet evolving customer needs. And the insurance distribution strategy is shifting to adapt to new product offerings, client needs, and digital technology-led disruption in the ecosystem.

Not surprisingly, insurers are adopting AI and related technologies to drive these capabilities. According to our just released Insurance IT Services – Annual Report, the top three business objectives insurers are trying to achieve with AI projects are customer experience, process optimization, and product innovation.

AI Ins BlogAI Trends in the Insurance Industry

Our annual report studied 80 unique AI initiatives by global insurers to unearth AI trends in the insurance industry. Here are the top ones we identified.

Capabilities

Approximately 53 percent of insurers are developing in-house capabilities for their AI initiatives. But many have large skills gaps that will inhibit their ability to scale pilot projects and realize the expected value from AI initiatives.

Embedded intelligence

Insurers have accelerated their focus on embedding intelligence across the value chain, with higher adoption of AI for sales & distribution and underwriting processes.

Self-service

Insurers are adopting intelligent self-service AI tools to enhance the customer experience.

Mid- and back-office process value

The value delivered through front-office AI initiatives such as chatbots is limited. But real value can be unlocked when AI is applied to optimize mid- and back-office processes such as agent support and claims management.

Data

While structured enterprise data remains the major source of data for insurers (52 percent, per our research), the connected ecosystem – i.e., data from IoT-based devices – is gradually gaining traction, at approximately 35 percent. As insurers evolve in their AI journey, deploying AI and machine learning (ML) to leverage unstructured data from third-party sources and connected ecosystems is likely to increase. But as of today, enterprise data silos, legacy systems, and lack of interoperability standards to tap into the connected ecosystem and third-party data are slowing down insurers’ AI initiatives.

Some Standout Examples

Many insurers have made progress in deploying AI and ML to their data and are starting to see quantifiable results. For example:

  • Zurich Insurance deployed AI in its personal injury claims process. The company claims that AI has helped it save 40,000 work hours, and reduced claim processing time from 58 minutes to five seconds per medical report
  • ICICI Lombard launched a chatbot called MyRA to underwrite two-wheeler, fire, and burglary insurance for SMEs. Since its launch, MyRA has been engaged in 65,000 customer interactions, and has sold more than 750 policies without any human intervention.

AI has the potential to deliver significant value to insurers and their customers. To learn more about how it can impact your business, our recent Insurance IT Services – Annual Report is packed with data and our take-away insights from 80 unique insurance firm AI projects. In it, we outline how AI implementation is impacting the insurance industry, and present various AI use cases across the insurance value chain.

Please write to Ronak and Priyanka to discuss how you’re adopting AI in your insurance business processes.

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