The first half of 2024 has been an incredible journey for Unstructured Unlocked, with over 50 top-ranking episodes featuring thought leaders from across the insurance and AI sectors. We’ve had the privilege of speaking with experts like Henry Gale, Research and Insights Manager at InsTech; and Mandy Hunt, former Chief Underwriting Officer at RSA, who shared their perspectives on how AI is revolutionizing underwriting and enhancing decision-making processes. Alongside them, industry figures such as Arthur Borden, VP, Digital Business Systems & Architecture, Everest; Robin Merttens, executive chairman of InsTech; Joe Curry, Head of Data Science at Apollo 1971; and Charles Morris, Chief Data Scientist at Microsoft, discussed how AI is being leveraged for automation and risk assessment, underscoring the evolving landscape of insurance technology
Listen to the full podcast here: Unstructured Unlocked season 2 episode 8, the best of 2024 so far
In this special Best of 2024 episode, we celebrated the halfway mark of 2024 by highlighting some of our favorite podcast moments from the year so far. From expert analyses of AI’s evolving impact on insurance to practical insights on how automation is enhancing decision-making and profitability, we’re recapping the key conversations that are shaping the future of the insurance industry. Here’s a look at some of the top quotes from our guests across the AI and insurance sectors this year.
AI adoption is accelerating across the insurance industry
2024 has proven to be a year of rapid technological evolution within insurance, particularly in the adoption of artificial intelligence (AI). Historically, the insurance industry has been slower to adopt new technologies compared to other sectors like finance, but as Henry Gale, Research and Insights Manager at InsTech, explained in Episode 37, that’s changing fast:
“In the past, insurance has been a slow adopter compared to the rest of financial services, but it has picked up on generative AI… I think some people get more easily exhausted with this type of hype than others, but I think there’s also more use cases to come,” Gale shared, underscoring how AI is starting to gain real traction among insurers.
This shift is significant. AI is no longer confined to pilots or proof-of-concept projects—it is being implemented in production environments where it is already delivering results. Many insurers are recognizing the potential of AI to handle the growing complexity of risk management, data processing, and customer expectations. At Indico, our enterprise AI solutions are helping insurers process unstructured data more effectively, providing real-time insights that lead to smarter decision-making and reduced operational overhead.
Related content: Turn data into actionable insights for smarter business decisions
Underwriting accuracy improves with AI
One of the most talked-about areas of AI innovation this year on Unstructured Unlocked has been underwriting. Historically, underwriting has been a labor-intensive, manual process, but enterprise AI is now making it easier to process large amounts of data quickly and accurately. In Episode 39, Mandy Hunt, former Chief Underwriting Officer at RSA, offered some great insights into how AI is transforming underwriting:
“The more you automate, the more the system’s going to start drawing those [mistakes] out earlier…we might get to some people that maybe are not interpreting things in the right way or have missed a guideline or something because the system will help us see those things quicker than waiting to do the audit every 3, 6, 7 weeks or years for some businesses,” Hunt explained.
AI isn’t just improving the speed of underwriting—it’s making underwriting more accurate and reliable. By automating much of the data processing, AI allows underwriters to identify potential risks or errors much earlier in the process, reducing the chance of costly mistakes. For Indico, this is a key area of focus. Our enterprise AI platform allows insurers to leverage automation to streamline the underwriting process, reduce errors, and make more informed decisions.
Joe Curry, Head of Apollo 1971 Data Science, echoed this sentiment in Episode 40, where he highlighted the time efficiency that AI brings to underwriting teams: “Being able to extract certain information from slips… is a massive advantage and massive time saver that would’ve taken a UA a couple of days to do.”
Improving underwriting accuracy through AI means helping insurers enhance decision-making capabilities. By eliminating the need for manual data entry and review, we can allow underwriters to focus on more complex, high-value tasks.
Predictive analytics and automation in risk management
Another key takeaway from the first half of 2024 has been the impact of predictive analytics and automation in managing risk. Insurers are constantly faced with the challenge of assessing and mitigating risks, and enterprise AI offers an unprecedented level of predictive accuracy. As AI continues to advance, its ability to analyze vast datasets and generate actionable insights is transforming how insurers approach risk management.
Tom Wilde, CEO of Indico, spoke to this during Episode 1 of Season 2: “Customers generally are… hoping that the vendor solutions can help them to simply get to the decision at the end, right? Should I prove this claim? Should I underwrite this risk? So that’s the answer they’re looking for.” AI provides that very solution, offering decisioning and guidance through data insights.
This highlights a critical benefit of enterprise AI—it doesn’t just automate tasks, it provides the insights needed to make strategic decisions quickly. In an industry where risks can evolve rapidly, particularly in areas like cyber risk and climate change, having the ability to make data-driven decisions in real time is invaluable. AI helps insurers evaluate potential risks more effectively and act swiftly, reducing their exposure to costly claims or financial losses.
Alex Taylor, Global Head of Emerging Technologies at QBE Ventures, added to this in Episode 42, discussing the need for insurers to be more “adventurous” when managing risks like climate change. He noted, “We are in a landscape of dramatically increasing risk… The way that we’re playing into that, of course, is by being a little bit more adventurous in some of the things that we do with our technology solutions. And overall, that’s a good news story.”
Indico’s enterprise AI solutions are designed to empower insurers with real-time data and predictive analytics that help them manage risk proactively. Whether it’s assessing the impact of climate change, evaluating cybersecurity threats, or identifying potential claims fraud, AI helps insurers stay ahead of emerging risks and protect their bottom line.
Related content: Enhancing carrier decisioning through collaborative ecosystems: an Indico webinar recap
Large language models and the future of insurance
One of the most exciting technological advancements that has been making waves in the insurance industry this year is the continued rise of large language models (LLMs). These AI-driven tools, which can process and interpret massive amounts of unstructured data, are proving invaluable for tasks like claims processing, document review, and underwriting. In Episode 41, Charles Morris, Chief Data Scientist at Microsoft, discussed the potential of LLMs to not just automate processes but to reinvent them:
“Gen AI is so transformational a technology, that really, we can reinvent a lot of processes… If I think about, ‘What is the outcome I need to accomplish, and what are the assets and resources available to me to accomplish that?’ I actually—with Gen AI—have new lines I can draw that weren’t possible before. And so, focusing on automating existing processes is not always the right solution. It may be that a full assistive approach from end-to-end in a different way is actually faster, more effective, safer, lower risk.”
LLMs allow insurers to review claims, underwriting submissions, and other documents far faster than manual processes allow, and with fewer errors. By using AI to extract key insights from complex data, insurers can make more informed decisions, whether it’s pricing a policy, assessing a claim, or evaluating a potential risk.
Real-time claims processing and AI’s role in customer experience
Enterprise AI has been making a noticeable impact in claims processing, too. Insurers are under constant pressure to resolve claims quickly and accurately while maintaining high levels of customer satisfaction. The ability to process claims in real time, thanks to AI, is drastically improving the customer experience. In Episode 43, Sunil Rao, Chief Executive Officer at Tribble, highlighted the impact of generative AI on these operations:
“…This is probably a high-leverage generative AI use case you can tackle with relatively low risk… You probably have salespeople, they’re probably spending a disproportionate amount of time juggling Word documents or Google Docs… Can we drive some efficiency there so they can spend more time selling?”
This insight points to a broader trend—using AI not just for high-risk backend processes, but also to optimize client-facing operations. AI enables insurers to automate document-heavy tasks, reducing the time it takes to resolve claims, which in turn leads to higher customer satisfaction. This mirrors Indico’s approach to AI—our enterprise AI platform is designed to automate the processing of unstructured data, such as claims documents and customer interactions, enabling insurers to handle claims more efficiently and with fewer errors.
AI and risk prevention: A proactive approach to insurance
While much of the focus on AI in insurance revolves around automating existing processes, enterprise AI is also enabling insurers to take a more proactive approach to risk prevention. Rather than simply reacting to claims, AI allows insurers to predict and prevent potential risks before they result in a claim. In Episode 3 of Season 2, Kelly Cusick, Managing Director at Deloitte, explained how this shift is taking place:
“The one thing that I think is really potentially exciting and a huge opportunity around a lot of the advancements in data and technology and all that is the ability to not just be there when something bad happens, but the preventative part of the insurance industry. So, working with customers to help them manage their personal risk or their business risk such that you can prevent claims from happening in the first place…”
This shift from reactive to proactive insurance is a game-changer. By using AI to monitor real-time data, such as environmental conditions, market trends, or customer behavior, insurers can identify potential risks early and take action to prevent losses. This benefits both insurers and their customers—insurers can reduce the frequency and severity of claims, while customers can avoid disruptive or costly incidents altogether.
Unlock the power of AI in insurance
As we look ahead to the rest of 2024, it’s clear that enterprise AI is not just a tool for improving efficiency—it’s a strategic asset that can drive long-term success in the insurance industry. From underwriting and claims processing to risk management and compliance, AI is transforming how insurers operate, allowing them to make smarter, faster decisions.
At Indico, we’re committed to helping insurers unlock the full potential of enterprise AI. Our AI solutions are designed to help insurers process unstructured data, automate routine tasks, and enhance decision-making capabilities, all while improving accuracy and reducing operational costs.
We’re grateful to all of our guests for joining us so far this year, and we’re especially thankful for you, our listeners! Stay tuned to hear more deep-dive discussions and insights from insurance industry and AI leaders in the second half of 2024. You can subscribe to Unstructured Unlocked on your favorite podcast platforms:
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Frequently asked questions
- How is AI impacting customer experience in the insurance industry? While the blog touches on AI’s role in underwriting, risk management, and claims processing, it doesn’t dive deeply into its impact on customer experience. AI is transforming the customer journey in several ways, from speeding up claims resolutions to offering personalized policy recommendations. For example, AI-powered chatbots and virtual assistants are helping insurers offer 24/7 support, resolve customer queries faster, and streamline the claims process, ultimately enhancing customer satisfaction and retention. Moreover, AI enables real-time data processing, which allows insurers to offer more personalized products and experiences tailored to customer needs.
- How are large language models (LLMs) specifically being applied in the insurance industry? The blog mentions large language models (LLMs) but doesn’t provide specific examples of their applications. LLMs are primarily being used to process and interpret vast amounts of unstructured data, such as claims documents, contracts, and underwriting forms. These models can quickly extract key insights, assess claims for fraud, and automate document review. This not only reduces human error but also speeds up traditionally time-consuming tasks, helping insurers make quicker and more accurate decisions. Additionally, LLMs can be integrated into customer service systems to handle complex queries and deliver personalized responses.
- What are some specific challenges insurers face when adopting AI? The blog discusses the benefits of AI but doesn’t mention the challenges. One of the main challenges insurers face is integrating AI with existing legacy systems. Many insurance companies have outdated infrastructure that doesn’t easily support modern AI technologies. Another challenge is data quality—insurers must have clean, organized data to get the most out of AI solutions. Additionally, there’s the concern of regulatory compliance, especially with AI-driven decision-making processes. Insurers need to ensure that AI algorithms are transparent, ethical, and comply with the relevant regulations governing privacy, data protection, and fairness in decisioning.
