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Majority of young people trust accuracy of ‘faster’ AI solutions in their home & auto insurance

As insurers turn to AI to improve efficiency and customer satisfaction, 54% of consumers age 18 to 34 said they would trust AI to accurately process applications, answer questions, or handle claims without human involvement if it meant a faster process.

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Pat HowardManaging Editor & Licensed Home Insurance ExpertPat Howard is a managing editor and licensed home insurance expert at Policygenius, where he specializes in homeowners insurance. His work and expertise has been featured in MarketWatch, Real Simple, Fox Business, VentureBeat, This Old House, Investopedia, Fatherly, Lifehacker, Better Homes & Garden, Property Casualty 360, and elsewhere.&Rachael BrennanSenior Editor & Licensed Auto Insurance ExpertRachael Brennan is a senior editor and a licensed auto insurance expert at Policygenius. Her work has also been featured in MoneyGeek, Clearsurance, Adweek, Boston Globe, The Ladders, and AutoInsurance.com.

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The use of artificial intelligence has increased rapidly in 2023, with a third of recently surveyed companies claiming they now use generative AI (gen AI) regularly for at least one business function. [1] Though many consumers are concerned about the ethics and accuracy of AI, [2] insurance customers appear to be less resistant to it compared to when we first reported on AI and home & auto insurance.

Roughly 32% of home, auto, or renters insurance customers would trust the accuracy of AI at one or more points in their customer experience journey (application, customer service, and claims) without human oversight, and around one in seven (15%) would trust AI to handle the complete end-to-end experience, according to the 2023 Policygenius Home and Auto Insurance Technology Survey.

Key findings

  • Younger insurance customers (age 18 to 34) were roughly three times as likely to trust the accuracy of AI as customers age 55 or older.

  • 15% of customers would trust the accuracy of AI at all three customer experience touchpoints (application, customer service, and claims), while 25% would not trust AI at any point during the process and would only want to work with a human while purchasing or using their insurance coverage.

  • When compared to the 41% of customers who said that they have never purchased or used insurance online, tech-savvy customers (59%) were significantly more likely to trust AI during the insurance application, customer service, or claims process (with 45% of tech savvy consumers trusting AI during at least one of these stages vs. 14% of their counterparts).

  • At all three consumer touchpoint scenarios in our survey, the most common response customers gave was that they would want a hybrid human-AI solution as opposed to one with only AI or only humans.

How we defined ‘tech-savvy’

To gain a more thorough understanding of which consumers are more likely to be open to the use of AI, we asked survey respondents if they had any experience using digital tech to either purchase or use their insurance. We then defined “tech-savvy” customers as those who answered that they had experience taking at least one of the listed digital actions.

Which, if any, of the following actions have you taken with regard to purchasing or using your home, auto, or renters insurance? Please select all that apply.

  • I've gotten quotes online (33%)

  • I've bought an insurance policy online (27%)

  • I've used a chatbot to get answers to questions about my policy (10%)

  • I've used tools on a carrier's website to figure out how much coverage I need (18%)

  • I've used a carrier's website or mobile app to file a claim (20%)

  • None of the above (41%)

54% of younger insurance customers trust AI with at least some of their home or auto insurance needs 

When asked if they would trust AI to process their application for insurance, answer policy questions, or assess their claim without human oversight, a majority (54%) of younger customers (age 18 to 34) said they would trust AI to execute at least one of these things accurately, compared to just 16% of customers age 55 or older.  

Younger insurance customers were also the most likely to trust AI throughout the entire customer experience journey, with 26% saying they would trust an AI-driven application process, customer service, and claims assessment without a human verifying its outputs, and an additional 13% would trust AI to handle at least two of these processes without human involvement (for a total of 39%). 

Meanwhile, just 6% of insurance customers age 55 or older said they would trust AI at every customer experience touchpoint, and 35% said they would not trust the accuracy of AI at all throughout the process and would want a human to handle everything, even if it led to slower application approval and delayed claim settlements. 

‘Tech-savvy’ customers are more likely to trust an AI-powered insurance process

Insurers have largely moved away from paper recordkeeping and brick-and-mortar offices, allowing insurance customers to get quotes, file claims, or adjust their policy coverages without having to speak to a human. According to our survey, customers with experience doing these things online were roughly three times as likely to trust AI compared to those who had no experience with digital insurance tech. 

Overview of AI use cases in home & auto insurance

Artificial intelligence has been used in the insurance industry for some time now for basic tasks, such as inputting names, addresses, and property details from an application into a spreadsheet or database. But thanks to recent advances in limited memory AI — the technology behind everything from basic chatbots to self-driving cars — AI is now capable of executing more complex tasks that we’ve normally left up to humans, such as analyzing a policy document or photographs related to a claim and making a decision about that claim based on its analysis.

Underwriting and pricing

Insurers are likely seeing the biggest benefits of AI when it comes to underwriting and issuing policies. More specifically, AI can now be used for everything from automating basic administrative tasks — like entering application data, sending reminders to customers to renew their policy, communicating with customers and loan servicers when changes have been made to a policy, and more — to quantifying and pricing the risk of an applicant by analyzing hundreds of thousands of data points. This allows underwriters to spend more of their time on applications that, for example, have already been approved by AI but require additional human verification before the company will agree to issue a policy, among other potential advantages.

On the consumer side, the increased use of AI in the application process would likely mean faster approval and more accurate and personalized rates. While one in four (25%) customers said they would trust AI to accurately process their application and receive faster approval, consumers were most likely to want a hybrid human-AI approach, with 45% saying they don’t fully trust AI to process their application accurately and would want it verified by a human, and 30% said they would not trust the accuracy of AI at all and would want a human to handle the entire process — even if it meant a slower process.

Customer service 

The recent boom in generative AI technology (a type of limited-memory AI) has helped insurers leverage AI in more consumer- and employee-facing ways, such as communicating with customers via chatbot, creating transcripts or course materials for insurance agents, or by conducting a sentiment analysis to ensure account specialists are prioritizing the most distressed customers and responding to them with the right level of concern.

Roughly 24% of consumers said they would trust AI to accurately answer questions about their insurance policy, 43% said they don’t fully trust AI to do this and would want the information verified by a human, and 33% said they would not trust the accuracy of AI at all and would only want a human to answer their questions.

Claims

On the claims front, limited-memory AI can be used to parse the text of a policy to see if a particular cause of loss cited in a claim is covered, or to scan photos submitted with a car insurance claim to quickly assess the wreckage and check for potential inconsistencies or fraud.

When asked about a fully AI-driven claims experience that could lead to a faster damage analysis and payout, 21% of respondents say they would trust AI to assess and process the claim accurately, 44% say they don’t fully trust the accuracy of AI and would want a human to verify the settlement, and 35% said they would not trust the accuracy of AI at all and would want a human to handle the entire claims process.

Conclusion

Insurance companies’ use of AI in underwriting and policy pricing, customer service, and claims could potentially improve productivity and reduce operational expenses by up to 40%, according to McKinsey. [3] These solutions could also lead to an overall improved user experience for home and auto insurance customers, providing them with everything from instant and hyper-personalized policy options when they submit a quote to expedited settlements when they file a claim. [4]   

But there is also a fair amount of risk that comes with the increased use of AI in the insurance sector, namely if it will act ethically and avoid bias and discrimination when left to make decisions around applications or claims. [5] Furthermore, gen AI as we currently know it has a tendency to “hallucinate” from time to time and spew out inaccurate or nonsensical information, adding to concerns that it may not provide customers with correct information. [6]

By the end of 2023, half of insurance companies will have tested this technology, while a quarter of them are expected to have gen AI products and services already in place. [7]  

Methodology

Policygenius commissioned YouGov Surveys to poll a nationally representative sample of 2,489 adults aged 18 and older, with 2,065 having home, auto, or renters insurance. The average margin of error for responses is +/- 2%. For more details, see YouGov’s methodology. Percentages were rounded to the nearest whole number, so some totals may not add up to 100.

About Policygenius

Policygenius transforms the insurance journey for consumers by providing a one-stop platform where consumers can compare options from top insurance carriers, get unbiased expert advice, buy policies, and manage their insurance portfolio, in one seamless, integrated experience. Our proprietary technology platform integrates with the leading life, disability, and home & auto insurance carriers and delivers an exceptional digital experience for both consumers and insurance carriers. Since 2014, our content, digital tools, and experts have served as a resource for millions of people on their insurance journey, and we have sold more than $200 billion in coverage. In 2023, Policygenius was acquired by Zinnia, an insurance technology and digital services company.

For reporters

To request more information about the data, or to speak with one of our experts, contact press@policygenius.com.

References

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Policygenius uses external sources, including government data, industry studies, and reputable news organizations to supplement proprietary marketplace data and internal expertise. Learn more about how we use and vet external sources as part of oureditorial standards.

  1. McKinsey

    . "

    The state of AI in 2023: Generative AI’s breakout year

    ." Accessed November 28, 2023.

  2. Salesforce

    . "

    Businesses Adopting AI Risk a ‘Trust Gap’ with Customers – Salesforce Report

    ." Accessed November 28, 2023.

  3. McKinsey

    . "

    Insurance productivity 2030: Reimagining the insurer for the future

    ." Accessed November 28, 2023.

  4. National Association of Insurance Commissioners

    . "

    Artificial Intelligence

    ." Accessed November 28, 2023.

  5. EY

    . "

    How insurers can leverage the power of generative AI

    ." Accessed November 28, 2023.

  6. ZDNET

    . "

    Generative AI can't find its own errors. Do we need better prompts?

    ." Accessed November 28, 2023.

  7. Oliver Wyman

    . "

    Keeping Up With Generative AI

    ." Accessed November 28, 2023.

Corrections

No corrections since publication.

Authors

Pat Howard is a managing editor and licensed home insurance expert at Policygenius, where he specializes in homeowners insurance. His work and expertise has been featured in MarketWatch, Real Simple, Fox Business, VentureBeat, This Old House, Investopedia, Fatherly, Lifehacker, Better Homes & Garden, Property Casualty 360, and elsewhere.

Rachael Brennan is a senior editor and a licensed auto insurance expert at Policygenius. Her work has also been featured in MoneyGeek, Clearsurance, Adweek, Boston Globe, The Ladders, and AutoInsurance.com.

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