High-value AI Tactics in Insurance

It’s important to understand the technologies that fall under the umbrella of Artificial Intelligence including Natural Language Processing, Facial Recognition, Predictive and Generative.  As with all emerging technologies, different portions are at different levels of maturity and their relative efficacy is marketed as improving existing interactions. When we research ways AI can improve business capabilities or value chain, we unlock transformational value. Ultimately AI allows us to ask new questions and gain new insights into areas of business that weren’t feasibly visible before. 

When we review AI’s transformational value potential in Insurance one area to consider is:

  • Cross and Upsell at Renewal
    • Based on claims activity, cohort underwriting profit/loss, coverage adjacency and digital touchpoints, what additional coverages or coverage levels may be well received.
    • Coverage recommendations can be provided to an underwriter for pricing review and then to your distribution model.  
    • Direct distribution models may provide these recommendations to the policyholder via email campaigns to first drive awareness of new coverages and then suggest the new coverage mix during the renewal purchase experience.
    • Leveraging this capability improvement in Captive and non-Captive Agency models can have an even larger impact.  The Agent/Broker will view the proactive recommendations as a mechanism to build their business.  The Agent/Broker may still be able to opt the Policyholder into educational marketing campaigns and bring the new coverage mix into their renewal meetings with the Policyholder.  Most importantly, few carriers actively attempt to build their distribution networks’ businesses.  The resulting impact may be distribution expansion by organic Policy growth, increased penetration at current Agencies/Brokerages, and Agency/Brokerage referrals resulting in new appointments.  
  • AI Tactics
    • AI’s predictive capabilities can provide advanced statistical predictions to determine risk levels based on claims activity and cohort underwriting profit.  
    • Tracking of marketing campaigns and website activity can be used by AI’s predictive capabilities to inform product recommendation.  A policyholder with a personal lines auto policy that is researching commercial cyber coverages on your website may be more apt to buy cyber rather than personal home insurance.  
    • Generative AI can be used for initial drafts of email or call scripting for product education.  

A quick aside on the Regulatory and Compliance impact. The Regulatory & Compliance environment will continue to lag technology development. Thus far, the EU is ahead of the US in this space. The bulk of AI regulations center on fully automating financial product pricing or access.  The use case offered here isn’t  currently regulated and is not likely to be in the future.

Getting started on an AI journey is different from a traditional technology project.  Xede can assist with aligning AI tactics to business value, data assessment, ethical and regulatory concerns in addition to implementation and ongoing management.

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