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Industry Insights with Luke Wolmer: Discovering AI's role in the future of insurance
The role of AI in business, and specifically in actuarial departments, will continue to evolve. As we refine and adapt our use cases to enhance DUAL’s capabilities, we anticipate continued benefits throughout the market.
Luke Wolmer is DUAL’s Chief Actuary, overseeing actuarial management, financial risk, and product strategies to continue to position DUAL as a profitable and knowledgeable industry leader. As AI becomes a larger part of the insurance industry, we sat down with Luke to understand how AI can add value while being used responsibly today and in the future.
How AI is changing the insurance landscape
AI is finding its footholds in every industry, and insurance is no different. As a relatively new concept, most industries are still exploring ways to utilize AI tools to enhance the value and efficiency of their work, while also understanding the risks associated with using these tools. Businesses in the insurance industry are evolving rapidly to compete in a crowded environment that gets riskier each day. While structural and logistical challenges will always be in tandem with growth, participating in new technology is how companies stay ahead.
Some insurance companies are utilizing AI to accelerate digitization, aiding in tasks such as risk assessment, fraud detection, portfolio management, and error reduction throughout applications (Forbes). While there are many ways to begin experimenting with AI throughout organizations, insurers must be diligent with how they anticipate and address pitfalls of AI. Ultimately, insurers can reshape value chains and scale efficiencies with unlimited potential (BCG), so they must build risk management frameworks that allow for the responsible use of AI.
AI as a valuable actuarial tool
Actuarial departments, like many other data-intensive analytical professions, are being revolutionized by this technology. AI can significantly enhance operational efficiencies, allowing for more labor-intensive processes or sophisticated model building to be completed in a fraction of the time. This allows analytical teams to cover more ground, handle higher volumes of work, and execute more complex analyses as a standard part of their operations.
While few insurers are integrating AI technologies at scale or truly seeing the value of AI among their programs at this time, evidence is clear that when used properly, AI can have a measurable impact on various business functions (McKinsey). When applied in an actuarial context, other insurers are using AI to increase the accuracy of predictive modeling, incorporate new data sources, and automate routine or tedious tasks (International Actuarial Association). At DUAL, the value of AI has been tested and demonstrated across two main buckets: portfolio steering and pricing models. On the portfolio steering side, AI can support analyzing large volumes of structured and unstructured data and summarizing key performance indicators such as growth, market trends, and additional insights. DUAL’s actuarial team also uses AI as a supplemental analytic tool to help identify potential rating variables.
AI enhances our strengths, augments human judgment, and unlocks new capabilities that make our existing processes faster, smarter, and more consistent.
Enhanced efficiencies through AI
At DUAL, we focus on collaboration, as we know that efficiency is maximized when knowledge is shared across teams. DUAL’s claims entities work closely with our actuarial department as well as our underwriting teams to build a continuous feedback loop that allows for a clear, holistic view of what’s happening in our markets. Additionally, DUAL’s actuarial department works closely with leadership to ensure the key learnings and insights are spread throughout the business. On a more granular level, these insights can be compared to what underwriters are seeing in the market on a real-time basis to understand where there is overlap in data. Even further, DUAL’s finance department can also use insights from the actuarial department to understand the overarching strategic implications of performance across programs. As DUAL’s actuarial team becomes more empowered with AI, we’re able to tell a strong, comprehensive story to our internal stakeholders and carrier partners about what’s really happening in the market.
The primary benefits of AI are the ability to enhance our productivity at scale, increase our output, and operate across all of our programs with efficiency.
The future of AI in Insurance
Through extensive experimentation, we’re finding ways that AI can support growing profitability and enhanced book building. We anticipate the role of AI in actuarial departments will continue to develop, and as the functionality of these tools continues to develop, we can refine, adapt, and repeat. It’s hard to truly understand the limits of AI without testing them, and on average, companies often capture less than a third of the value they expect from digital transformations such as incorporating AI; however, the increasing distance between laggards and leaders in AI has shown sizable growth advantages for insurers when it comes to total shareholder returns (McKinsey), which is why we’re continuing to build our understanding of these tools every day.
Finding value from AI is its own challenge, but insurers also need to be keenly aware of ongoing emerging risks. While many of the risks of AI are widely known, for the insurance industry in particular, there needs to be an awareness of learned bias in AI tools, protective measures to ensure sensitive or proprietary information is not shared to public sources, and increased cybersecurity across the organization (Michigan Bar Journal). And most importantly, our expert teams need to be able to analyze and critique AI outputs to ensure accuracy.
Other than solving the age-old question of “how can I get more hours in the day?,” AI helps to identify patterns and interactions in massive amounts of data, including those that humans may miss. Overall, this will help DUAL be more competitive in the market and be a better partner to our carriers, as we uncover insights not commonly known in the market and create new avenues for them to grow. Participating in new technologies also opens up new opportunities to the younger workforce, different than standard insurance opportunities, and allows us to shape the future of the industry by incorporating more quantitative backgrounds.
Ultimately, it’s interesting to think about just how far AI will go. Would there ever be a world where no humans are in the loop for actuarial processes? Even though the industry has started to adopt AI in a variety of ways, at this stage we see it as a powerful supplement rather than a replacement. We’ve already seen it create real value for our business and look forward to the ongoing evolution and introduction of use cases for AI in insurance.
For more information about how DUAL helps partners do more or to learn more about DUAL North America, visit our home page.
AI presents significant opportunities for users, including in the insurance industry, but the key to success is that teams still need to have the expertise that will allow for insightful review and critique of AI outputs to ensure consistency and accuracy.
The statements in this article reflect current views and intentions regarding the use of AI within the insurance industry. They are not guarantees of future performance and may change as technology and regulations evolve. DUAL is committed to implementing AI responsibly and strives to align its initiatives with applicable laws, data privacy requirements, and ethical standards.
Nothing in this article is intended to act as legal or other advice, or as an endorsement or recommendation. This article is provided for informational and educational purposes only. DUAL disclaims any warranty, legal liability or responsibility for the accuracy, completeness or usefulness of the information in this article or for any reliance on AI. DUAL does not use AI to make coverage decisions and all uses of AI are subject to human decision-making oversight and judgement.
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