Until recently, traditional methods of assessing and financing natural perils have worked well, but conditions have changed. Extreme weather and climate events are increasing in frequency and severity, while value at risk is growing exponentially. Historical underwriting and portfolio management approaches are no longer sustainable for insurers. To keep insurance available tomorrow, innovation is required today.

Insurance plays a critical role in resilience. The billions of dollars insurers pay out in claims annually enable policyholders to rebuild their lives and livelihoods. But what happens when insurers can no longer offer protection due to accumulated losses, restrictive state regulations, or a lack of reinsurance capital to transfer risk?

See also: Insurers Must Evolve to Survive Climate Crisis

Individuals, businesses and communities struggle. Some organizations suffer uninsured losses and are forced to close their doors. Local and regional economies slow. The financial fallout affects many.

Southern California has suffered from two of the most destructive wildfires in state history. The Palisades and Eaton fires, which started in early January, have claimed at least two dozen lives and consumed 40,000 acres of homes, businesses and landmarks, with estimated economic losses of $250 billion, according to the Los Angeles Times. As property owners and government officials survey the devastation, insurance companies are facing angry questions about why many are not renewing policies and withdrawing from underwriting risks in the state.

California's insurance regulatory system has had an impact, but it's not the whole story. To continue offering protection in a state with a long history of wildfires, insurers need ways to accurately and sustainably underwrite a risk that is evolving rapidly.

Severe convective storms (SCS) — while not the most attention-grabbing — are actually the most destructive peril, with Aon reporting insured SCS losses totaled $61 billion last year, making it the costliest peril for insurers. Not only are they becoming more frequent but they also pose an existential threat to insurance companies. In 2023, SCS losses were responsible for the insolvencies of four insurers and rating downgrades for dozens of others.

In 2024, the National Oceanic and Atmospheric Administration (NOAA) reported 27 weather and climate disasters that each caused more than $1 billion in damage. 17 involved tornadoes, hail or severe thunderstorms. Less than one-fifth of the billion-dollar disasters NOAA tracked in 2024 were tropical cyclones. Between 1980 and 2024, the annual average of billion-dollar events is nine. In 2020-2024, however, that number rose to 23. More of the U.S. is experiencing severe storms, and insurers are paying more for the losses those events cause.

The problem with SCS loss frequency and severity is insurers are unable to spread this risk through traditional catastrophe reinsurance programs. Reinsurers have been reluctant to provide aggregate loss coverage, and even though limited protection was briefly available years ago, it was cost-prohibitive for insurers. As a result, insurers today can reinsure hurricane risks but must retain SCS losses on their balance sheets. With limited options for spreading risk, insurance companies eventually must decide when the aggregation of claims forces them to curtail their underwriting where SCS perils are present. That is simply not sustainable.

Keys to financial stability

Insurance as a business relies on several conditions to exist. The first of those is a clear understanding of the risks that insurance companies assume on their balance sheets. Next is the ability to accurately price those risks. Third is the ability to spread risks — within a portfolio of policies and with access to reinsurance capital. When these three conditions exist, the result is financial stability, with adequate surplus and capital to pay claims.

Claims ebb and flow from year to year, but unless insurance companies can absorb those losses and underwrite risks profitably, they cannot remain in business — or continue to offer policies for those risks. That ultimately means additional financial burdens for taxpayers.

Sustainability is a major challenge for all businesses, and it's especially acute in insurance. The benefits of a stable, sustainable insurance industry are many — financial protection remains accessible, funds are available when losses strike, and local economies can continue growing.

See also: Insurers Face Complex Risk Environment in 2025

Innovation to mitigate risks

Amid current trends, secondary perils such as wildfires and severe convective storms are driving financial volatility for insurers and policyholders. To mitigate these risks and keep insurance available in geographies where such perils threaten life and property, the insurance industry needs to embrace innovation.

Innovation is already occurring in modeling risks and losses, producing significant improvements in evaluating and pricing risks. Novel risk transfer solutions also exist, including parametric modeled-loss policies that provide cost-effective reinsurance of secondary perils. With these enhanced tools, perils that some insurers have opted to avoid can be insured.

History offers some lessons for insurance policyholders and policymakers. In the past, when risks became too frequent and severe for the insurance industry to handle, the industry called for a federal solution. This has occurred multiple times in the past century — flooding and homeowners insurance led to the National Flood Insurance Program in 1968, the Sept. 11, 2001, terrorist attacks and terrorism risk resulted in the Terrorism Risk Insurance Act in 2002, a federal backstop for systemic cyber risk is still being debated.

Are wildfires and severe convective storms next on the list of risks that require government funding? The private insurance industry appears to have adequate capital to underwrite these risks, with better tools for risk assessment and risk transfer. These innovations can keep insurance available where individuals and businesses most need the protection it offers.

Oliver Wyman shares 10 actions CEOs should take to Reinvent Insurance and fuel growth in 2025. This year’s theme is ‘Growth, Relevance and Resilience,’ with a strong undercurrent of bolder organic moves and more M&A. 

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Sponsored by ITL Partner: Oliver Wyman

My first book, "Big Blues: The Unmaking of IBM," published in 1993, was an archetype. Despite the years of reporting and the blood, sweat and tears that went into it, the book boiled down to a familiar story: A self-satisfied giant failed to see that its world was changing and lost to a nimbler upstart. 

That upstart, Bill Gates, recently published the first volume of his autobiography, "Source Code: My Beginnings," which reminded me of a moment in my book where everything hung in the balance for Microsoft. Gates, just 24 years old at the time, made a shrewd contract demand whose significance the IBMers missed — and without which the world at large might never have heard of Gates or Microsoft. 

How could someone that young be so sophisticated? Because he had already negotiated dozens of contracts with big corporations (he started doing professional programming work in eighth grade) and had been living in the nascent PC world for years. His IBM counterparts, raised on mainframes, had had only a few months to get acquainted with the PC business — and, as they would soon learn, its economics bore little resemblance to mainframes.

There is a lesson there, I think, for the insurance industry. The PC revolution, along with more recent seismic technology shifts, shows that an advance as fundamental as gen AI can change the source of revenue and profits. Yet insurance companies are largely focused on gen AI's low-hanging fruit, such as efficiencies. 

That work is important, but companies should be thinking much, much bigger if they want to be the winner in the latest tale and not a self-satisfied giant left by the wayside. Insurance companies should already be envisioning where the new revenue and profit pools might be, should be testing to see if those visions might be right and should be experimenting with how to get to those pools first. 

I'll offer some thoughts on where at least one major pool could be for insurers, as well as on how to test and experiment. But let's start with the meeting that a young Bill Gates had with a roomful of IBMers in a makeshift office in Boca Raton, Florida, in late September 1980.

Gates and his chief lieutenant, Steve Ballmer, had flown overnight from Seattle to Miami. They changed into their suits in a men's room... and Gates, who hadn't slept in 36 hours, realized he had forgotten to bring a tie. They rented a car and drove to Boca, where they sat outside a department store until it opened at 10am so Gates could buy one. They arrived late for their meeting with the buttoned-down IBM team. Not a great start.

IBM had set up a skunkworks in a leaky old warehouse in Boca to try to develop a PC outside of normal channels, which had been fatally slow in three attempts to produce a PC. By the time an IBM product was ready to launch, the quicksilver market had already moved on to better technology. Apple had launched its Apple II all the way back in 1977 and was getting buzz that embarrassed IBM more and more by the day, as it failed to respond. Frank Cary, IBM's fierce CEO, walked around demanding of his executives, "Where's my Apple?"

IBM had done its due diligence and settled on Microsoft as the right supplier of a PC operating system, but there were plenty of doubters, and no one wanted to risk Cary's wrath if this latest attempt failed, too. Microsoft had all of 32 employees at the time, and its CEO and public face, Gates, could have passed for 15 or 16 years old. So IBMers packed the room and pelted Gates with questions. 

He's in his element in any technical discussion and quickly won the room over. But that still left the contract. 

Jack Sams, the IBM executive who had found Microsoft, told me he had counseled Gates to be bold. Sams reasoned that Microsoft was a key supplier, so IBM needed it to be healthy for years. He told Gates he could even ask for $1 million (about $4 million in today's dollars) in return for an exclusive license of the DOS operating system.

But Gates had a better idea. He just asked for a tiny royalty per computer sold, while retaining the right to license DOS to other companies. IBM accepted the offer, and Microsoft today has a market cap of $3 trillion.

Why IBM missed the boat is a complicated story: I wrote some 130,000 words on the subject in "Big Blues." Here, I'll focus on why Gates got things right. 

In fact, he didn't get everything right. Far from it. He told me he didn't think IBM would sell that many PCs. The product just didn't impress him. He also didn't fully understand how much an IBM PC would set the standard for the whole industry, creating the wildly lucrative opportunity for him to license his operating system to companies making "IBM-compatible" PCs. In fact, he thought Microsoft's big money maker would continue to be programming languages: Microsoft software that let programmers use common languages such as BASIC, Fortran and Cobol as they coded on PCs.

But Gates got more important issues right because he and his Microsoft co-founder, Paul Allen, had been on the cutting edge of the PC revolution before PCs even existed — Allen had been tracking developments in microprocessor technology since the early 1970s, waiting for one they thought could be the heart of a desktop computer. When they saw their opportunity, they founded Microsoft in 1975, five full years before IBM came knocking. In those intervening years, they had piled up plenty of small successes and some failures that educated them about the new world of PCs. 

In particular, they had what was initially a great experience but then became a horror story with a startup, MITS, that was the early leader in PCs. Microsoft's languages became standard on MITS computers and rode the MITS wave in the second half of the 1970s, but the companies came to blows over contract language about what exclusive rights MITS held and thus about Microsoft's ability to sell its languages to MITS competitors. Microsoft eventually won in arbitration, and MITS had to pay about $100,000 in royalties that it had withheld, but cash at Microsoft got so tight for a bit that Gates borrowed from an employee to meet payroll. So he was in no hurry to grant anyone else anything that smelled of exclusive rights, even if it meant getting the imprimatur of IBM. 

Gates had also seen — actually lived, for years — the Moore's Law doubling of computing power on a chip every year and a half, so he saw the coming, monumental shift toward increasingly powerful, relatively inexpensive PCs in a way that those who had long lived in the mainframe world could not.  

To me, the origin story of Microsoft shows the value of being early on a fundamental shift in technology — not entering the battlefield in some grand way that assumes you have all the answers in a still-forming market but in a way that lets you have the sorts of small successes and failures that educated Gates and let him outmaneuver IBM. 

My longtime colleague and frequent co-author Chunka Mui took that idea of early immersion a step further last week, based on what he saw in the initial internet boom, when his book, "Unleashing the Killer App," was pretty much the bible for innovation and based on what he's learned since through consulting, speaking and research. 

Of the five lessons he offers for innovating with generative AI, I'll underscore two. He writes:

"It's Not Enough to Adopt the Technology; You Need to Find the Value. Satya Nadella, the CEO of Microsoft, recently observed that while Microsoft survived the transition to the Internet and the Web quite well, it missed out on the biggest business model shift in value. Instead, Microsoft and others let Google—a company that barely participated in the original Dot Com bubble or bust—capture the lion’s share of the trillions in high-margin revenues stemming from search-based advertising since then. Prior technology leaders, like Kodak, Sears, Best Buy, Blockbuster, and Yahoo, were even less fortunate. Likewise, AI will likely shift the value proposition and profit distribution in a wide range of industries. Recognize that adopting AI is only half the battle; understanding the business model implications is what will separate the winners from the also-rans."

And:

"Think Big, Very, Very Big. We are entering a golden age for entrepreneurs and innovators to reset business plans and goals to build a better tomorrow—and prosper enormously by doing so. Right now, the opportunities are better than ever for people and companies seeking to tackle the biggest problems facing our world: sustainable energy, carbon capture, housing, hunger, food production, transportation, water quality, and more. Companies that help solve these grave problems are increasingly valued by investors, especially as the costs of key technologies are plummeting to nearly nothing while their capabilities grow exponentially. Focus on long-term value rather than short-term gains. As Astro Teller, Captain of Moonshots at Alphabet’s X, points out, 'Making a [huge] problem go away is unlocking enormous value in the world. Have faith. If you solve that problem, the money will find your organization.'”

How gen AI may transform the insurance model isn't at all clear to me. If it were, I'd quit my day job and go become a multibillionaire. 

But I do think there's one obvious area for exploration: the use of insurance data and expertise to predict and prevent losses, as opposed to merely compensating policyholders once they happen. Gen AI allows for the gathering and analyzing of vast amounts of data that weren't previously possible. And everything can happen almost instantaneously. Gen AI no longer just has a brain, either, as AI always has; gen AI has a voice. So it can not only gather and analyze vast troves of information in real time but can tell us what risks it sees, heading off water leaks, the spread of wildfires, auto accidents, you name it. 

At the moment, insurance companies generally monetize their data and expertise through products, but it seems to me that there could be a massive new pool of service revenue for those that get in the game early and figure out how to define it and tap it. Yes, that requires a new business model, but think back on Gates and IBM: There was no such thing as a PC software industry until Microsoft pretty much invented it.

Cheers,

Paul 

2025 will be a defining year for the insurance industry. With leading insurers now investing billions in AI capabilities, even traditional carriers are racing to adapt or risk obsolescence. The stakes couldn't be higher: Those who master AI's potential will capture market share and dramatically lower loss ratios, while those who lag may find themselves struggling to compete in an increasingly tech-driven marketplace. 

Here’s what insurers can expect to see AI do for the industry this year:

1. Hyper-Personalized Underwriting and Pricing

The era of one-size-fits-all insurance policies is rapidly fading. AI models are now capable of analyzing vast datasets encompassing behavioral patterns, IoT sensor data, and demographic information to create highly personalized risk profiles. Insurance carriers are increasingly deploying machine learning algorithms that can dynamically adjust premiums based on real-time data. These sophisticated models can process thousands of variables simultaneously; this year, we will see an increase in tailored policies that more accurately reflect individual risk levels.

See also: How AI Will Transform Insurance in 2025

2. Climate Risk Assessment and Mitigation

As climate-related risks are set to intensify, AI will be an indispensable tool for insurers. Insurers will use advanced AI models for processing complex climate data, satellite imagery, and both historical and real-time weather patterns to better predict and assess climate-related risks. These systems identify properties most vulnerable to flooding, wildfires, or storm damage with unprecedented accuracy.

This year, insurers will also rely on these insights to adjust their risk models and help insureds implement preventive measures. AI-powered early warning systems can alert property owners to imminent weather risks, while predictive maintenance algorithms can identify potential vulnerabilities before they lead to climate-related damage.

3. Claims Processing and Fraud Detection

The claims process is undergoing a dramatic change through AI automation. Computer vision systems can now assess vehicle damage from photographs with high accuracy, while natural language processing algorithms can quickly extract relevant information from submitted claims documentation, significantly reducing processing times and improving customer outcomes. 

In fraud detection, increasingly sophisticated AI systems will quickly identify suspicious patterns and anomalies, helping the industry head off more instances of potential fraud before they happen. Machine learning models can analyze historical claims data, social media information, and other external data sources to flag potential fraud cases for investigation. These systems learn and adapt in real time and will help insurers stay ahead of evolving fraud tactics.

4. Ethical Considerations and Challenges

The expanded use of AI in insurance raises important ethical questions that the industry will face head on in 2025. Algorithmic bias is a critical concern, particularly in ensuring that AI-driven pricing models don't unfairly discriminate against certain demographics. Insurance companies will implement robust testing frameworks to identify and eliminate biases in their AI systems, and that issue will come to a head this year.

Data privacy and security present a significant challenge that insurers will resolve in 2025. As more personal data is collected and processed, we will see strong safeguards implemented to protect sensitive information while expanding transparency about how this data is used in decision-making processes.

See also: AI in Insurance: 2025 Predictions

5. Generative AI Applications

Generative AI will take customer communication and scenario modeling to a whole new level. Chatbots and virtual assistants powered by large language models handle complex customer queries with human-like understanding, allowing insurers to provide 24/7 support across multiple languages. These systems will be used to explain policy details, guide customers through claims processes, and offer personalized insurance advice.

This year, we will also see generative AI used to create sophisticated scenarios for stress testing insurance portfolios. These models can generate thousands of potential risk scenarios, helping insurers better prepare for various contingencies and optimize their risk management strategies.

6. Evolution of Risk Pooling

We’re about to see a big shift in how insurers approach risk pooling, thanks to AI. Machine learning algorithms are creating more granular risk pools based on sophisticated pattern recognition across vast datasets. This year, we will see the emergence of micro-pools that can offer more competitive pricing for specific risk profiles while maintaining the fundamental principles of risk sharing.

Looking Ahead

As we progress through 2025, two key predictions stand out:

1. We'll see the emergence of "AI-first" insurance companies that build their entire operations around AI capabilities, challenging traditional insurers to accelerate their digital transformation.
2. The integration of AI with IoT devices will lead to the widespread adoption of "preventive insurance" models, where insurers help clients prevent losses rather than simply paying claims after the fact.

The insurance industry is at a pivotal moment. AI is fundamentally changing how products are designed, priced, and delivered. Our success this year will depend on finding the right balance between embracing these new technologies and allowing the industry’s human expertise to shine.

Insurance Thought Leadership

Let’s start with the Southern California wildfires, as long as Nearmap was so involved in helping carriers respond and as long as the disaster is so on point for our Predict & Prevent focus this month. What did you see?

Dave Tobias

Interestingly, we had flown over the LA area, including the Palisades, on Jan. 1, just before the fires started on the seventh. This is part of our normal cadence, as we capture new imagery three to four times a year depending on the region.

We had planes in the air within five hours of the fire starting. We maintain a nearly 24/7 operations team outside Washington DC that monitors events, weather, and plane locations, and we were able to start streaming this imagery to insurance companies within hours after these flights.

We run AI analysis on every flight, and in catastrophes we conduct damage detection via AI. For wildfires, we're assessing total versus partial losses, though these fires typically resulted in total losses. While a hurricane typically moves through an area and is done, this fire kept spreading, and areas that were initially safe were later destroyed.

I happened to be in Hartford during the fires, meeting with some of our largest insurance customers. I witnessed firsthand how they were using our data. One top-five carrier had integrated our imagery and AI analysis into their mapping system, using it to guide their call center in contacting insureds who were evacuated. The reps were often the first to inform people about whether their homes had survived. These insurers went to great lengths to locate their customers, even searching social media platforms like Facebook and TikTok to reach them.

The human element really stood out to me. Insurance executives were reaching out after seeing my LinkedIn posts, asking me to check on their childhood homes or family members' properties. I found myself delivering news to about 20 people personally. It reinforced that, during a crisis, whether you're an insurer or insured, people want certainty. They need to know what's happening so they can start planning, regardless of the outcome. That's really one of the fundamental elements of insurance – providing certainty for people moving forward.

And in a catastrophe like this, resources become very constrained. Whether it's apartments, contractors to clear debris, or other services -- there's only so much available in the area. The sooner insured homeowners can start taking action, the better position they'll be in.

I heard this sentiment echoed by many insurers we work with. In cases of total loss, they could immediately process claims for policy limits because everything was gone. Seeing them use AI and aerial imagery to facilitate this process was remarkable -- it's the first time I've witnessed that kind of straight-through processing.

Insurance Thought Leadership

Based on your aerial imagery from January and earlier, what insights are insurance companies gathering to help homeowners and communities better protect themselves against fire damage?

Dave Tobias

Everyone has seen that one home that survived on the block because it had more robust building materials. But really, the easiest thing everybody can do, and the data makes it very clear, is have good defensible space around their buildings.

When you have hundred-mile-an-hour-plus winds and embers in the air, sometimes there's nothing that can be done. But you definitely see the homes that had good defensible space around them versus the ones that didn't -- their survivability went up quite a bit.

The nice thing about defensible space is it's something a homeowner can do as step one without a lot of investment. That's what I would call the base-level mitigation: Clear the shrubs, cut down some trees, use nonflammable plants.

Another issue I see, even in my neighborhood in Burlingame -- where wildfire isn't really a threat, except in the hills -- is what people put right next to their building. They put wood mulch literally touching the building because it looks nice. But it's kindling. Wood mulch is kindling. You might as well put a bunch of matchsticks up against your home.

We've all done it. My old home had it. But you're putting very flammable material right up against the structure.

These are things people can act on now as preventative measures. The Palisades, specifically, everybody knew was a wildfire danger zone. There's a lot of negative press about insurers canceling policies ahead of the fire, like they knew the fire was coming. The reality is the insurers and everybody else knew this was a wildfire zone for a long time.

Insurance is just math at the end of the day. If you can charge enough premium, you can insure anything, but the regulatory environment in California makes it difficult to charge the right rate, so insuring properties in a highly dangerous wildfire zone is really expensive.

I think it's going to be interesting to see how the rebuild happens in some of these areas, and if some of these risk-mitigating factors change. There are plenty of great materials and building guides from IBHS (the Insurance Institute for Business and Home Safety) and others on fortified homes for wildfire. I'm hopeful, but it's not going to change the fact that these areas will continue to be arid and have high winds.

Insurance Thought Leadership

How can insurance companies better encourage homeowners to maintain proper brush clearance year after year, especially given the mixed success of community efforts like those in the Palisades?

Dave Tobias

When you have houses in close proximity to each other, if some homeowners maintain their property while others don't, it diminishes the value of community protection. We need to create better incentives for people to maintain their properties.

There's the inherent carrot-and-stick approach. Doing certain things might bring down your insurance rates. We see some states implementing programs, like with fortified homes and fortified roofs. In areas that experience massive hail events annually, where people need new roofs every year, some states provide rebates or funding to insurers or homeowners to install more sustainable roofs that meet specific fortified standards.

But we need to start implementing these sorts of programs now. These events aren't going to stop happening, and people are going to continue living in these areas.

While some homeowners will take initiative on their own, my hope is that we'll develop a more cohesive strategy around prediction and prevention at the state level, and maybe someday even at the federal level. That's really the only way some of these areas will remain insurable.

Insurance Thought Leadership

What if you used your aerial images to show homeowners how their properties compare with their neighbors’, similar to how utility companies share data on how my energy usage compares with similar homes in my neighborhood?

Dave Tobias

Absolutely. The technology and data exists today. Insurers have a lot of this data -- they're buying from companies like us and others. When you log in to pay your insurance bill, you don't see this data that insurers have, at least I don't with my insurer. That's a big opportunity.

I think there's huge potential for sharing downstream preventative measures. Take defensible space. The AI can show your current defensible space profile and indicate that if you clear out specific zones, it will reduce your risk by a certain amount. The same applies to roof condition. We can monitor your roof and share that information with you as an insured, pointing out problems like missing shingles or staining that might need attention.

You can track issues over time, which is valuable because most people don't regularly inspect their roofs -- out of sight, out of mind. I think sharing more information downstream with agents and insureds would benefit everyone. That's a last-mile problem we hope to solve.

The concept of Predict & Prevent isn't new -- I and others have been talking about it for years. What's new is the technology to assist in it, like the information we can get from aerial imagery and how we've been able to unlock it with AI. But we're not doing anything to act yet. We need to add some level of action to that prevent step.

Insurance Thought Leadership

How do your hurricane monitoring and tracking methods differ from your wildfire surveillance?

Dave Tobias

With hurricanes, we typically know they're coming and can plan accordingly. Even before the hurricane hits, we can identify which properties will be most susceptible to damage.

The Predict & Prevent aspect is crucial. With hurricanes, you can see fascinating examples where two neighboring properties experience the same storm conditions -- identical wind speeds and everything -- yet one roof survives without a scratch while the other gets completely ripped off. This demonstrates how taking preventative action, like installing fortified roofs, can prevent hurricane disaster damage.

Insurance Thought Leadership

What is your approach to areas that aren't obviously at risk? How do you handle coverage in places like Kansas or Minnesota that may not seem like immediate priority zones?

Dave Tobias

For our impact response, we'll fly anywhere. Milton and Helene hit some areas that weren't as populous, but we flew them. We flew 118 flights. We analyzed over 5 million buildings.

We can fly areas we've never flown before, and that still provides tremendous value to insurance companies. They're trying to triage and decide where to send their claims adjusters and get everything moving in the right direction. The sooner they can do that, the better for everybody.

I like to say that every carrier is a CAT carrier now, because every state has had at least one catastrophic-level peril that's starting to hit it. When I started in insurance, you would talk about certain carriers just dealing with catastrophic stuff in Florida and Louisiana, while others would say "we're in Colorado, we're not really a CAT carrier." But that's definitely changed because of the severity of these events, the frequency of these events, and where populations have moved to.

Insurance Thought Leadership

Looking ahead two to five years, where do you see your technology evolving in terms of predicting risk factors?

Dave Tobias

I think we're going to have to evolve, because otherwise too much of the country will become uninsurable. We're going to have to change the mindset and have insurance companies, insureds, and agents all partner together to maintain properties at an insurable level.

To achieve this, insurance companies need to share more information with the insureds. We need tools from companies like Nearmap to make that sharing easy and interactive, so insurers can easily assess the condition of their roof and defensible space profile and improve them. That's the only way to get closer to an equilibrium of rate to risk. Right now, in certain areas of the country -- Florida and California being extreme examples -- we don't have that equilibrium or anything close to it.

Five years from now, I think Predict & Prevent is going to be a cornerstone of insurance policy and framework.

Insurance Thought Leadership

Is there anything we haven't covered or any final thoughts you'd like to share?

Dave Tobias

Obviously, I'm biased, but I think not enough gets told about how proactive insurers were during the fires and how they were really trying to help people. They weren't just canceling policies and doing the things that the news has described. I think we need to tell the story of carriers who were tracking people down on TikTok just so they could be there to help.

I was talking to one carrier whose claims adjusters were sometimes spending three or four hours on the phone with insureds because they were being counselors. They were helping people figure out how to replace their pictures and other personal items. These companies were really going above and beyond.

Insurance Thought Leadership

That seems like a great note to end on. I’ll certainly try to do my part to spread the word.

Thank you for taking the time.

Dave Tobias

We love talking about this stuff, and there's so much to discuss.

After decades of manual and low-tech document processing, business process outsourcing (BPO) is due for an AI transformation. 

The scale of document processing in insurance is staggering. A typical mid-sized retail agency processes thousands of policies annually, with each policy requiring multiple reviews and comparisons. With staff spending an average of 70% of their time on manual document processing, the industry faces a critical efficiency challenge. 

The Next Wave of Insurance Operations Efficiency

The BPO model today delivers significant cost savings, and insurers and agents are counting on artificial intelligence (AI) technology to deliver further efficiencies throughout the insurance value chain. The automation of policy and agency document processing alone will prove to be transformative to carriers, retailers, wholesalers, MGAs, and customers. Manual tasks of policy checking, quote comparisons, policy data extraction and analysis, and dozens of other use cases can now be automated thanks to AI. 

The evolution of AI technology has been particularly meaningful for insurance operations. Early automation attempts often struggled with the complexity of insurance documents and the need for contextual understanding. Modern AI capabilities, enhanced by advances in machine learning and natural language processing, can now effectively handle intricate insurance documentation while maintaining accuracy. This technological maturity, combined with established BPO processes, creates new possibilities for operational efficiency.

Consider policy checking, a traditionally labor-intensive process. Where previous automation attempts could only handle basic data matching, today's AI can analyze complex coverage forms, identify potential gaps, and flag discrepancies while reducing processing time by 75%. Similar advances in quote comparison and data extraction capabilities are transforming how insurance organizations handle routine but critical tasks.

See also: Balancing AI Innovation With Consumer Protection

The Importance of Human Oversight

The insurance industry's reliance on judgment and expertise means that technology alone isn't the answer. Experience across the industry shows that maintaining quality standards while achieving efficiency gains requires finding the right balance between artificial intelligence and human insight. This "human-in-the-loop" approach ensures that AI outputs align with industry standards and business objectives.

Even with the most advanced AI systems, it’s critical these tools are supported by experienced professionals who understand:

• Complex risk assessment nuances that require human judgment
• Program business dynamics across multiple carriers
• Authority compliance requirements and monitoring
• Market relationship management and development
• Strategic growth opportunities identification

The impact extends beyond operational efficiency. Insurance providers implementing this balanced approach report improved customer service through faster, more streamlined processes and fewer errors. They gain deeper insights into customer needs and can provide better risk advisory services. Financial benefits emerge through improved forecasting, better carrier relationship management, and more effective tracking of performance metrics.

Maximizing AI's Value Through Professional Insight

Insurance professionals provide the critical thinking and industry expertise needed to transform AI outputs into strategic advantages. Most importantly, for the foreseeable future, they will be key to providing the strategic insight and analysis necessary to holistically achieve elevated customer service and business optimization. 

The results of this balanced approach are evident in several key areas. Organizations implementing AI-enhanced BPO typically see dramatic improvements in processing efficiency while maintaining or improving accuracy. Quote comparison times drop from hours to minutes, leading to faster client response times and improved close rates. Policy data extraction becomes more thorough and consistent, enabling better carrier negotiations and risk assessment.

With the right AI and BPO partner, Insurance providers can dramatically improve customer service. This means faster and more streamlined purchase and renewal processes; a deeper understanding of customer profiles and needs; an ability to provide risk advisory services using loss runs data; and far fewer errors and mistakes. 

With the right balance of technology and human capital, agencies can run more profitably. Areas for immediate gains include improved forecasting and management of revenue and margin by customer vertical or geography; analysis of retail brokers’ relationships with carriers – and carriers’ relationships with retail brokers; better management of the placement of policies with the best carriers; and the tracking of performance toward earning carrier contingent payments, to cite just a few.

See also: Blending AI With Human Interaction

Conclusion

The future of insurance operations lies in finding the right balance between AI technology and human expertise. While AI provides unprecedented efficiency and accuracy in processing insurance documents, the industry's complexity demands that we maintain human oversight to ensure quality and strategic insight. Organizations that successfully combine AI's processing power with experienced professionals' judgment will gain significant competitive advantages. The key to success isn't just implementing AI technology but creating an integrated approach that leverages both technological capabilities and human expertise to deliver superior results for clients and stakeholders.

The expression, "Mind the Gap," dates to the 1960s, when it was first announced on the London Underground. The purpose was to warn passengers of the potentially dangerous gap between the train door and platform, which are not perfectly aligned. The expression has since evolved to become a general warning about the danger of open space or gap between two points. 

It applies especially well to the many risks and headwinds faced by the insurance industry today. If unattended, the gap may be irreversible or much harder to close.

The P&C industry is, by design, resilient, with layers of financial insulation. Reinsurance, surplus capital and low-risk and liquid investment portfolios are just some of these layers, with individual state oversight to monitor financial stability. The insurance model has been tested during high inflationary periods and catastrophes and alternating hard and soft market cycles. However, the last three years are arguably the most challenging, because of fluctuating inflation and worsening climate risks. Meanwhile, there are emerging and widening gaps that both threaten and are reshaping massive segments, such as real estate and homeownership.

Climate Resilience Gap

As made painfully obvious by the recent series of extreme weather catastrophes, government and public agencies’ collective ability to respond to these new and greater risks has proven inadequate, while the insurance industry is more vulnerable than ever. Each event seems to outpace the last, taxing FEMA, illuminating dated infrastructure and financially straining insurers. 

Protection Gap

It is estimated that 50% of insurable global risks are actually insured – in some countries and socio-economic groups, the gap is much larger. The impact of this lack of coverage is the high, and in some cases unexpected, cost of covering losses and replacing property. Frequently, insurance companies take the brunt of the blame for not properly advising policyholders at the front end. Affordability is driving the gap further as trade-off decisions are made to partially or fully self-insure. Most are ill-prepared for this new paradigm.

Trust Gap

Consumer trust and policyholder loyalty is at an all-time low within the insurance industry, including in health and P&C. The reasons include; years of double-digit premium increases, well beyond inflation; protracted and frustrating claims payment experience in the face of losses from increasingly extreme catastrophes; unexpected coverage denials; and a trust deficit as policyholder driving data and personal information is being collected and commercialized without explicit permission. All of this is exacerbated by the stark differences between insurance industry customer service levels in comparison with other modern digital experiences. Finally, insurer profits, whether in reality or just perception, are widely considered excessive.

See also: Embedded Insurance: A Major Disruptor

Transparency/Information Gap

The process by which premiums are calculated and claims are adjudicated remains opaque. Policy language is lengthy, technical and in parts vague and open to debate. Most policyholders are unaware of what information is collected and calculated or disagree that factors such as credit scores somehow accurately predict risk. Either way, there is a missing link between premiums and perception of risks, such as one’s self-evaluated driving skills. Most believe they are good, safe drivers, for instance.

Legal System Abuse Gap

While the plaintiff bar systematically optimizes the tort system, there are widespread abuses that enrich them with oversized fees resulting from astronomical jury verdicts, fueled by litigation funding and mass marketing. Conversely, the insurance industry has basically failed to exert its influence to reform the legal system and has been unable to keep pace. The industry needs to organize itself and fund a concerted effort to address this problem. Consumers are aware that these sky-high verdicts ultimately translate to higher premiums and expect insurers to do more to protect them.    

Talent Gap

The "silver tsunami" is a term used to describe the aging of the baby boomer population. It refers to the potential impact of this demographic shift on the workforce. Many baby boomers are retiring at an accelerated rate. The aging workforce is leading to a “brain drain” as older workers leave their jobs, taking their rich insurance knowledge to the pickle ball courts.

The recent shift from analog to digital business processes requires that the workforce receive appropriate upskilling or retraining, but the insurance industry continues to lag in these initiatives.

Finally, attracting the best and brightest young adults – most of whom are “digital natives”– to insurance careers has proven elusive. It is incumbent on the industry to work together to address the gap, starting with image and purpose. 

Empathy Gap

As insurers work to leverage new technology, there is a loss of human empathy across the enterprise. Claims is especially vulnerable because policyholders are suffering anxiety and stress. Efforts to automate often lead to fewer people resources, to meet ROI objectives, or are disjointed and yet to be perfected, resulting in a bumpy claim process.  

Insurers will need to do more to deploy, integrate and orchestrate new technology and coordinated provider services, especially AI, while improving and not degrading customer service and satisfaction. Loyalty and retention are at stake.  

Marketing Gap

The P&C insurance industry – specifically personal auto and home carriers – continue to offer essentially the same products they have been selling for decades. However, today’s consumers bear no resemblance to those in the past. Needs, expectations and preferences have changed dramatically, and legacy insurance institutions are quickly becoming irrelevant when making purchasing choices.

Product Gap

One prominent characteristic of the “new consumer” is their expectation of personalization in goods and services. This is the opposite of the “one size fits all” approach that the legacy insurance industry still pursues.

Consumers want dynamic, real-time, fit-for-purpose, bespoke insurance products, and if one carrier cannot provide it, there are others that will. Record-high insurance shopping rates are a reflection of these preferences.    

Consumers have embraced connected devices (cars, smartphones, watches, sensors) and the associated products and services, but insurers are badly lagging other segments in leveraging these from a product perspective, exposing themselves to competitive risk from technology providers. 

See also: Does the P&C Insurance Cycle No Longer Exist?

Distribution Gap

Independent insurance agents and brokers place about 62% of all P&C insurance premiums in the U.S. (including commercial lines and personal lines), yet they are not as effective as they could be. 

Brokers do a fair job of marketing new prospects but are generally much less effective at customizing coverage to personal needs and even less so at staying in touch with relevant communications and basically go silent until policy renewal approaches.  

Although the vast majority of auto insurers offer telematics-based insurance products, market penetration stands at only 16% of policies. Agents typically do not promote these products because they are not proficient at explaining them and fear alienating their prospects.

Embedded insurance (insurance bundled at point of sale of a product or service) is seeing rapid growth outside of insurance, but carriers are behind the curve. This deficiency not only represents lost revenue and the loss of new customer acquisition opportunities but allows non-traditional providers to take market share.   

Innovation Gap

Insurance C-Suite executives talk up innovation and transformation, but very few invest sufficient effort and resources beyond catching up with technology, and even fewer have strategic plans to close this gap. Yet technology is making a difference in numerous areas and is expected to do so well into the future.

It is incumbent on insurance CEOs to regularly communicate and clearly articulate their support of innovation and to ensure that adequate resources are being allocated and applied. It requires nothing less than a cultural makeover, addressing outdated constructs that impede breakthrough progress. 

Closing the Gaps

The role of innovation and insurtech cannot be overstated for an industry that historically is people- and labor-intensive. Closing these gaps is vital for the insurance industry and its contributions to the economy and consumer livelihoods. Long-term insurance stability is in the best interests of investors, financiers and risk takers of all types, including businesses and consumers. 

Minding the gap is foundational for industry success in 2025 and beyond. 

Climate change is amplifying property damage and business interruption exposures by increasing the frequency and severity of natural catastrophe events such as floods, wildfires and storms.

Understanding amplified physical risk exposures

Last year, natural catastrophes caused more than $350 billion in economic losses globally, with insurance covering less than a third of these losses, at just over $100 billion.

Between January and June 2024, the U.S. experienced more than $30 billion in insurance claims due to an above-average number of tornadoes, hailstorms and straight-line wind events. Texas, meanwhile, recorded its largest wildfire, which burnt 426,600 hectares. The damages involved in these events often far exceeded businesses’ risk scenario planning considerations.

What can companies do to better identify, quantify and mitigate potential damage and ensure both effective insurance protection and more resilient operations in the face of escalating physical climate challenges?

Organizations need smarter, more dynamic and comprehensive approaches to understand and respond to the risks. 

See also: What Trump 2.0 Means for Climate Initiatives

A smarter way to address physical climate risks

By evaluating the aggregate hazard scores of each of a company’s assets – the metric to evaluate the likelihood and potential impact of a specific hazard occurring – companies can understand their exposure to various natural catastrophes. Smart hazard scores can also combine historical data and predictive insights with expert judgment, providing the comprehensive risk assessments organizations need to address property damage and business interruption risks in today’s context.

More sophisticated risk evaluations will help to identify high-risk assets and prioritize actions to mitigate potential damage. Organizations can better detect vulnerabilities, such as the presence of basements with critical equipment in buildings or plants in flood-prone regions, or identify with more precision secondary peril risks such as landslides following heavy rainfall.

A combination of traditional insurance, captives and alternative risk transfer (such as parametric solutions), as well as cost-effective and sustainable adaptation on site level, can help business operations or value chains recover more quickly.

Using a combination of "what-if" types of stress testing, risk engineering and numerical or theoretical modeling can put companies on the front foot to manage the landscape of increasingly complex risks. The same is true of looking beyond an organization’s boundaries to better assess the potential vulnerabilities across their value and supply chain in light of more frequent, more severe disruption.

See also: Insurers Must Evolve to Survive Climate Crisis

How to avoid under-insurance using analytics and valuations

Many businesses could be under- or overestimating their property and business interruption risk in the context of heightened climate-related exposures. Some insurers, meanwhile, are potentially mispricing property risk, in part because their models don’t capture what used to be "black swan" events – those events that are almost impossible to predict yet seemingly inevitable, after the fact. Once rare, such events are now much more common due to climate change.

Because many models call on claims experiences, they effectively play back what’s already known, rather than forecast future likelihoods and impacts. This can lead to underestimating the value of assets and subsequent underinsurance, leaving businesses vulnerable to significant financial losses in the event of a claim.

A life and annuity (L&A) insurance service staff (policy administration or claims) serves as a critical intermediary between policyholders and insurance companies. Their role involves policy maintenance, investigating claims, assessing impact, and ensuring that settlements are processed fairly and promptly. 

To transform an L&A service staff into a “superpowered” professional, disruptive technologies would enhance efficiency and accuracy, empower staff with the ability to get the job done, and ultimately improve customer satisfaction. 

Below is a snapshot of a typical day for a service staff with SUPERPOWERS (i.e., good data, automation, and an AI assistant):

See also: A Season of Change for Life Insurance and Annuities

Human in the Loop Work Orchestration: 

• Review personalized dashboard on critical items needing attention.
• Respond to overnight emails and messages from policyholders, internal departments, or other external stakeholders in your enterprise workflow solution. Update any notes or set any reminders.
• Review and start working on pending/new cases that are automatically prioritized and routed based on deadlines, severity, or complexity.
• Analyze insurance policy information and document summaries to understand eligibility, request type compared with policy information such as coverage limits and exclusions for new requests in one user interface. Contact policyholders via their communication choice if additional information is required.
• Handle urgent requests or disputes that may require immediate attention.
• Update policyholders/stakeholders on progress and resolve questions or concerns per communication choice of their choosing. Handle disputes or escalations when stakeholders disagree with assessments or coverage decisions, using facts and empathy as data surrounding the decision is in one interface.
• Submit for approvals/denials based on authority limits
• Review and adjust ad hoc letters for any complaint/denials/complex workflows. The correspondence engine automatically provides a recommended language based on the action.
• Review payout calculations that need oversight due to the size and nature of the request. The calculation logic is presented for review and approval.

Agentic Workflows (Superpowers) in Action

• Natural Language Processing (NLP): Real-time, multilingual customer interaction and document interpretation. NLP tools like chatbots and voice assistants handle policyholder queries, extract key data from documents such as medical records or death certificates, and summarize complex documents, ensuring faster resolution.
• AI-Enabled Workflow Automation: Lightning-fast processing aimed to un-fragment various solutions into one experience. With agentic flows, repetitive tasks such as checking eligibility, retrieving and summarizing required documents, and initiating payouts are automatically done, which reduces human error and processing time.
• AI-Driven Triage: Instantaneous work categorization, prioritization, and routing of work. AI models analyze request details, policyholder history, policy information, and third-party data to recommend next steps, flagging fraudulent activity and urgent payouts.
• Third-Party Data Integration: Access to real-time data from various sources to retrieve meta data or specific info such as death data. Service staff leverage data from these data sources to validate events (e.g., accidents or health conditions) and expedite processing.
• Quantum Computing Insights: Instant risk assessment and fraud detection. Quantum computing processes complex datasets to identify fraud patterns or optimize payout models faster than traditional systems.
• Hyper-Personalization With AI: Tailored customer experiences and communication. AI analyzes policyholder demographics, behavior, and preferences to customize communication and processes, enhancing satisfaction.
• Sentimental Analysis for Empathetic Support: Detecting emotional states for tailored communication. AI models evaluate a stakeholder’s tone, language, and sentiment during interactions, helping staff respond empathetically while managing expectations.
• Advanced Analytics and Insights: Data-driven decision-making. Predictive analytics tools identify trends in requests, uncover potential risks, and suggest ways to enhance underwriting or streamline future processing.

See also: AI Bias in Life & Annuities Insurance

By blending these technologies, the L&A service staff becomes not just a processor but a proactive problem solver, delivering exceptional service while minimizing inefficiencies and errors.

At carriers that adopt these technologies, operations staff can focus on more complex, human-centered aspects of their roles while ensuring accuracy, consistency, and efficiency in handling work, providing a personalized customer experience.

When British mathematician Clive Humby said in 2006, "Data is the new oil," he might not have realized just how applicable that statement would be to the insurance industry's growth and profitability 19 years later.

Humby's quote has been interpreted to mean data will surpass oil as the driver of the global economy. Whether that ultimately proves to be the case is unimportant; comparing data and oil is apt. The value and usefulness of both depend on how they are processed and applied.

Insurance agents and brokers have a complex array of data at their fingertips, and maximizing the value of it all is challenging. There is, however, an area where they can tap significant revenue opportunities with minimal effort: placement data.

Insurance intermediaries collect vast quantities of data every day related to placing coverage, not only on their customers' risks but also from the insurance companies that accept those risks. This data can serve as a roadmap to consistent financial outperformance, if brokers can unlock it.

Even though placement data reflects potential revenue, brokers can't realize those earnings until they connect the dots between client need and carrier appetite and they complete coverage placements. What's needed is a reliable way to speed that process.

See also: 4 Challenges in Adopting Broker Technology

Accelerating placements

Accelerating the placement process and making it more efficient is an opportunity for every agent and broker. Beyond speed, maximizing the value of placement data means gaining clear visibility into opportunities that drive growth.

Identifying growth opportunities in placement data is a bit like matchmaking. Brokers must consider: What coverages do insureds need? What are underwriters looking for? Where do insurers have an appetite to write more business? By bringing both sides together with agreeable terms, the intermediary fulfills its mission and forges relationships that can deliver long-term benefit to all parties.

Imagine how much faster a broker could achieve revenue goals by analyzing placement data and finding opportunities it didn't see before. What could happen when a broker sees the possibility of offering additional coverage to an existing customer, or consolidating multiple lines with an insurer that is paying more commission for that business? Growth and profitability could increase for the brokerage, while the client gets more protection for its risks.

Consider the following hypothetical – though common – scenario:

ABC Insurance Brokers serves a wide range of midsize and large clients by procuring property and liability insurance policies. Even though ABC has placed its clients' risks with more than 50 different insurance companies, 80% of its book of business is placed with just 10 carriers. A great deal of time and effort is expended maintaining relationships with 40 insurers that account for a fraction of ABC's clients. In addition, of the 10 core insurers, five generate more than 60% of ABC's commission income. Seeing this, it becomes clear to ABC that the brokerage can generate more income by consolidating placements with fewer insurers, where doing so makes sense for the clients.

Moving up the ranks

A MarshBerry analysis of U.S. brokers shows the largest 50 firms account for 96% of the revenue of the top 100, while the bottom 50 have only a 4% share. With mergers and acquisitions forming a key building block of growth for most brokers, achieving organic growth through better use of placement data is a highly cost-efficient alternative – or supplement - to M&A.

The five-year compound annual growth rates (CAGR) for brokers in the top 100 varies by revenue size, MarshBerry found. Average five-year CAGR for brokers ranked 11-50 in 2023 was 18%, while it dropped to 9.5% for those ranked 51-75. The brokers ranked 76-100 had the lowest average CAGR, at 4.7%. This shows how smaller brokers struggle to consistently achieve growth.

Privately held brokers pursue growth to meet different objectives. Some prefer to remain independent, while others look to maximize their appeal for sale to a larger firm or private equity buyer. In either case, better use of placement data is a key to achieving sustainable, consistent growth.

See also: How Insurance Brokers Can Stay Competitive

Sharpening the line of sight

Gaining insight into the revenue opportunities within placement data is difficult with existing agency management systems. Those platforms excel at supporting agents' and brokers' workflows, but they fall short in providing strategic insights about placement. Innovative technology now exists that works hand-in-glove with brokers' existing core systems to analyze placement data and bring growth opportunities to the fore.