Making an Effective Business Case for Adopting AI for Insurance in 2024

Business leaders are practically unanimous about their desire to budget for AI to make their organizations more innovative, productive and competitive.

• The global generative AI in Insurance market is expected to grow 34.4%/annum and is projected to reach a market value of $14.4 billion by 2032 (1).
• Eighty-nine percent of business executives responding to a January 2024 BCG survey ranked AI/GenerativeAI (GenAI) as a “top-three tech priority for 2024.”(2)
• McKinsey researchers underscore one major reason for this urgency, estimating that ”generative AI could add the equivalent of $2.6 trillion to $4.4 trillion annually”(3) in value to the global economy.

Here’s why the insurance business case for AI should already be settled

In insurance, AI already plays a significant role in transforming complex document processing, a function essential to successful underwriting and claims processing/settlement.

Nevertheless, practice leaders at insurance carriers, TPAs, and other operators — where the rubber meets the road — are watching other factors outside their control. Their success depends partly on understanding how and when to merge AI into their operation amid such challenges as concerns about lengthy PoC-to-working-products development cycles, and regulation following the Biden administration’s recent AI Executive Order (4); and similar measures enacted in the UK (5) and EU (6).

On a parallel path, they’re often the people also tasked with building and implementing organization-wide best practices and risk management frameworks, as well as emplacing and empowering governance teams.

The potential of AI to deliver breakthroughs to enhance customer service, reduce costs and increase operational efficiencies are well-established. As are the potential risks facing any business bringing AI into their processes.

Insurers, given their immense responsibilities ranging from regulatory compliance to creating investor returns to serving policyholders, have the unenviable task of threading the needle to balance potential gains and the risks inherent with any large-scale change.

Making the case easier still is that AI tools expertly chosen can be deployed and scaled-up rapidly, allowing quick wins, including fast ROI from an investment in AI.

AI opportunities—the power to solve big insurance challenges today

2024 may be an inflection point. In the not-too-distant future we’re likely to look back on this year as the moment insurance fulfilled the promise of its long-gestating tech revolution.

Accenture postulates AI can automate up to 50% of tasks across insurance AND has the potential to augment adjusters, agents and underwriters a further 14% - enabling better, faster decision-making. As you read this, insurance companies using AI are seeing tremendous gains in accuracy and productivity.

Bringing AI and automation into underwriting processes “could result in savings of up to $160 billion over five years as non-core and administrative duties are removed from underwriters’ plates.” (Accenture (7)) As an example of how AI significantly reduces costs, consider overhead related to loss run processing. With accuracy rates exceeding 95% for claim-level and policy-level data, AI applied to these functions yields a 40% increase in underwriting team capacity to deliver faster quoting.

The landmark McKinsey study, “Insurance in 2030,” (8) presents AI/automation as a business imperative, asserting that manual underwriting methods will be “rendered obsolete ... for the majority of personal and small-business insurance products, encompassing life, property, and casual insurance.”

As with underwriting, the benefits of automating claims and empowering operations with AI are ushering in new standards of productivity elevating customer expectations:

Using AI to automate First Notice of Loss (FNOL), one major property insurance carrier reported 90% reduction in manual intervention, automating 70% of claims straight through.

Improved claims success can support customer service and other business operations. An EY survey revealed 87% of customers cited claims processing effectiveness as an influence on their decision to renew with the same insurer. (9)

AI Risks—why some businesses are taking a wait-and-see approach

A consensus is clearly forming on the benefits of Insurance for AI. So why are some businesses still on the sidelines?

Despite executives’ resolve (3) to integrate AI into their businesses, only 8-14% of US insurers have GenAI in production (10), as projects often face headwinds due to data management, cloud migration, and automation of a broader range of operational processes.

Lastly, while decades in the making, AI – especially generative AI – is new to most people. The speed of technology evolution and adoption requires that companies pay close attention to potential legal, ethical and reputational risks. These businesses will have to answer key questions on topics ranging from intellectual property misuse, data privacy and security, to liability (11) and inherent bias/discrimination.

But is the wait-and-see approach the right one?

What is the alternative?

Live discussion: AI in claims and underwriting

A number of insurance businesses today are seeing impressive results from implementing AI in their underwriting, claims and operations.

To gain a better understanding of how these companies are navigating a rapidly shifting landscape of opportunities and challenges, we invite you to register for AI in Insurance Claims and Underwriting, a live webinar on March 6 at 11:AM (Eastern).

In this session, a panel of seasoned AI consultants and practitioners, Chris Raimondo, EY’s Americas Insurance Technology Consulting Leader and Sabine VanderLinden, Co-Founder, CEO & Managing Partner, Alchemy Crew join Roots Automation’s CTO and Co-founder, John Cottongim, to:

• Discuss major trends in claims and underwriting AI
• Breakdown major success factors for your AI program, including use cases
• Share insights from real-world case studies and success stories
• Offer key considerations when building your business case for AI in 2024 .

Please join us for expert insight and guidance to help your business optimize its 2024 AI spend for maximum ROI.

Click to learn more. https://www.rootsautomation.com/webinars-and-events/webinar-unleashing-ai-in-claims-underwriting

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Sources

(1) https://www.alliedmarketresearch.com/generative-ai-in-insurance-market-A283347  

(2) https://www.bcg.com/publications/2024/from-potential-to-profit-with-genai  

(3) https://www.mckinsey.com/capabilities/mckinsey-digital/our-insights/the-economic-potential-of-generative-ai-the-next-productivity-frontier#key-insights

(4) https://www.whitehouse.gov/briefing-room/presidential-actions/2022/03/09/executive-order-on-ensuring-responsible-development-of-digital-assets/

(5) https://www.gov.uk/government/publications/ai-regulation-a-pro-innovation-approach/white-paper

(6) https://www.europarl.europa.eu/topics/en/article/20230601STO93804/eu-ai-act-first-regulation-on-artificial-intelligence

(7) https://www.accenture.com/us-en/insightsnew/insurance/ai-transforming-claims-underwriting

(8) https://www.mckinsey.com/industries/financial-services/our-insights/insurance-2030-the-impact-of-ai-on-the-future-of-insurance

(9) https://assets.ey.com/content/dam/ey-sites/ey-com/en_gl/topics/insurance/insurance-pdfs/EY-claims-in-a-digital-era.pdf

(10) https://www.oliverwyman.com/our-expertise/insights/2023/aug/how-insurers-can-successfully-use-generative-artificial-intelligence.html  

(11) https://globalnews.ca/news/10273910/chatgpt-bc-legal-precendent/#:~:text=Crime-,B.C.%20ruling%20on%20AI%20

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