Sorry for being delinquent about publishing my newsletter over the past few months: It has been due to a lack of time (I was writing three white papers) and inspiration. The newsletter has now reached its third anniversary, with 43,219 of you choosing to subscribe. Respecting your time over these 36 months, inspiration worthy of your attention has struck me just 21 times.

Many of you have asked when I might provide my perspective on the recent facts and figures of the trio I have followed: Lemonade, Hippo and Root. Now, with their annual financial results available, is an opportune moment to examine the performance of the three publicly listed U.S. P&C insurtech carriers.

There is, for sure, some good news for their fans (and shareholders).

Lemonade

Significant growth. The company almost reached the 2.5 million customer milestone, and the last two quarters showed an increase of the customer base not seen since 2021 (excluding the effect of the Metromile acquisition), with growth aligned with the 2022 promises.

Cash flow positive. For the first time in Lemonade's history, the operative activities generated positive cash flows in the past two quarters ($16 million in Q3 and $11 million in Q4).

The loss ratio has progressively improved (73% '24 gross loss ratio compared with 85% in 2023).

Hippo

The top line has grown. Total generated premiums – which includes the iconic Hippo’s homeowner business, premiums generated by their agency, and the Spinnaker fronting business – has grown from $1.1 billion to $1.3 billion in 2024

The company had its first profitable quarter (after a historical series of losses): $44 million net income in Q4 ‘24

The combined ratio (gross) significantly improved, with a healthy landing below 80%.

Root

The top line has grown to $1.3 billion in '24 from $800 million in '23.

Profitable. For the first time, they close the year with a positive bottom line ($31 million in profits in ‘24 vs $144 million loss in ‘23)

Combined ratio (gross) healthy, below 100%. The loss ratio has significantly improved – consistent with market trends – and the administrative cost incidence has been under control.

BUT there are significant reasons for not being too optimistic about these insurtech ventures.

Lemonade

The company still loses a ton of money. Net losses accounted for about $200 million in ’24 (a bit less than the $218 milliion in ’23), bringing the cumulative losses since the creation to $1.27 billion and reducing shareholder equity below $600 million.

The gross combined ratio is still well above 100% (each dollar of premium has cost them more than $1.20).

They are sill far from being an efficient insurance carrier. All their costs (excluding claims, loss adjustment expenses, and marketing) still gravitate above 30% of premium. “Collapse cost” [thanks to my friend Adrian Jones for the snapshot below] can be seen as a hope, an over-promise, or a bul***it depending on your taste for Lemonade.

Hippo

The positive results of the last quarter have been boosted by $46 million thanks to the sale of First Connect (Hippo’s independent agent platform).

The fronting business is the only profitable business, and its top line grew double digits. As the last newsletter edition highlighted, “The only segment consistently generating profits is the business of giving UW capacity to MGAs [...] further confirming that the acquisition of Spinnaker in 2020 has been the best management decision in the history of this venture.” No significant changes here: The fronting business ("insurance-as-a-service") made $24.4 million in profit, while the original Hippo business (HHIP) lost more than $50 millon in '24.

Hippo’s original homeowner business (HHIP) has been further pruned, landing a 73% gross loss ratio in ’24 (101% in ’23). A cherry-picked sub-$300 million homeowner insurance portfolio is a humble position from which to (re)start. After burning $1.27 billion to build this business, this doesn't exactly seem a milestone to celebrate.

Root

Vanished portfolio growth. Root has been stuck slightly above 400,000 policies for the past four quarters, with prudent marketing spending and constant increase of the average premium, which allowed them to keep the gross combined ratio below 100%.

But the magic moment when the auto insurance market dislocation allowed them to grow, even significantly increasing prices, is gone. Now, almost all the big incumbents are back to profitability and will start chasing new business again. How will Root deal with this scenario? Will they be able to consistently show the growth you expect from a “challenger”? Or, will their journey fail to create anything relevant in the market's competitive dynamics and only slowly repay the $1.7 billion they have burned until now.

Much of Root's equity narrative, and a substantial portion of Lemonade's projected upside from its investor day, revolve around automotive telematics. Yet, compared with current telematics best practices, both appear rather amateurish.

Telematics (when used well) is a social good because it increases the availability and affordability of coverage. This happens when the carrier becomes able to provide the same level of coverage for a lower price to a significant part of the portfolio while maintaining the target level of profitability. To do this, telematics data must be used to 1) match rate to risk better, 2) manage claims better, and 3) reduce expected losses.

Our dear insurtech Lemonade talks only matching rate to risks, or pricing sophistication (Lemonade had one slide on claims at its investor day and 21 charts about telematics. Lemonade makes promises about the future (as always).I

Root, meanwhile, talks about a current capability, their supposed superiority in matching price to risk. So let’s compare Root performance with the best practice (Progressive) in using telematics data for pricing sophistication. The competitive gap emerges clearly: Progressive has grown the number of policies by more than 16% in the past nine months, Root only a modest 3.5%.   

About the second telematics use case: Telematics and claims seem to be a match made in heaven. Instead of waiting for the policyholder's first notice of loss, the insurance carrier is informed in a timely way that something happened and has objective information about the dynamic and probable consequences of the event. 

The third usage of telematics data, totally ignored by our dear insurtechs, is to keep accidents from happening. Let's focus on one of the less-known but more important approaches: real-time actions. About this, I want to share an abstract of the interview with Massimiliano Balbo di Vinadio , vice president of sales LA at Targa Telematics , one of the members of the IoT Insurance Observatory .

MC: What is Targa's history, and how did the journey lead to the acquisition of Viasat?

MBV: "Targa Telematics is a technology leader with over 20 years of experience in developing cutting-edge solutions that help businesses, organizations, and communities fully leverage the Internet of Things and AI. The company offers a wide range of software solutions for vehicle rental companies, financial institutions, insurance companies, brokers, and large fleet managers. These include insurance telematics, fleet management, and asset management solutions.

In 2006, the company acquired Targa Infomobility from Fiat Auto, which specialized in infomobility services, satellite anti-theft systems, and fleet management. In 2012, Targa Drive was established to provide insurance companies with telematics solutions.

In 2023, Targa took a significant step by acquiring the Viasat Group, expanding its presence in key European markets such as Italy, France, Portugal, Poland, Romania, Spain and the U.K., but also in Chile. This acquisition strengthened its position in the insurance market, allowing Targa to offer advanced telematics insurance solutions, meeting the increasing demand for data-driven, personalized insurance.

In January 2024, Targa expanded its telematics portfolio by acquiring Drive It, a spin-off from Earnix. This acquisition has introduced MaaS (mobile as a sensor) functionalities and further strengthened Targa's AI capabilities.

With its extensive experience and continued innovation, Targa Telematics now offers a comprehensive portfolio of insurance solutions."       

MC: Risk prevention has been discussed frequently at the plenary sessions of the IoT Insurance Observatory. What is Targa's experience with real-time feedback to drivers? Can you share any facts and figures about the risk reduction achieved?

MBV: "Risk prevention is a significant topic and Targa Telematics is at the forefront of this. Our experience with real-time feedback to drivers showcases the power of telematics in fostering safer driving behaviors and reducing insurance risk. A standout feature of Targa Drive is its coaching module, which delivers real-time audio notifications to guide drivers during their journeys, helping them adjust unsafe behaviors on the spot. Drivers also receive daily or weekly feedback aimed at improving their driving style and promoting sustainable driving habits over time. This personalized approach has led to significant risk reduction and behavior improvement among our users.

The drivers can be further motivated through metrics on streaks (continuous safe driving days) and trends that offer an objective view of their progress. A customized reward program can be also made available for insurers, allowing them to deliver promotions and incentives tied to the driver's recorded improvement. This helps insurers enhance engagement while fostering a continuous improvement culture among policyholders.

We also see notable success with our windscreen devices, which are equipped with advanced sensors, including GPS tracking, and three-axis accelerometer. These devices collect crucial data for crash management, speed monitoring, geofencing, and emergency call services. The coaching function in these devices, delivered through non-intrusive LED indicators, provides real-time guidance to help drivers improve their habits. Several of our customers have successfully integrated this device into their operations, reducing accident rates and promoting safer driving. On average, customers who have adopted this solution have reported a 30% improvement in their drivers' scores."

MC: What is your vision about the future of auto insurance?

MBV: "IoT and AI are set to revolutionize the mobility landscape and therefore key players such as insurances, leasing and rental companies just to name a few. By focusing on prevention through better driving behaviors, combined with the power of data analytics, the industry can reduce claims frequency and severity, delivering more sustainable and customer-friendly outcomes."

Dr. Robert T. Reville is the CEO and cofounder of Praedicat, the liability risk analytics company.  Praedicat’s risk models are used for underwriting and risk management by leading P&C insurers and global industrials. Prior to co-founding Praedicat, Bob was Senior Economist at the RAND Corporation, where he conceived and led an R&D project mining the text of peer-reviewed science to identify emerging "next asbestos" risks. The project provided the foundation for Praedicat and Bob traded policy research for start-up life. Bob's research career focused on liability, risk and insurance. He was the Director of the RAND Institute for Civil Justice, a liability research center which published influential research on asbestos; and co-director of the RAND Center for Terrorism Risk Management Policy, which published research on terrorism insurance that was cited in congressional debates over the Terrorism Risk Insurance Act. Bob has also written over a dozen studies on workers' compensation. He received his Ph.D. in economics from Brown University.

Here is the interview transcript:

Insurance Thought Leadership

Congratulations again on being a finalist for the Global Innovation Award. I thought I'd start out by asking you to tell us a bit about what you've been doing at Praedicat.

Robert Reville

Sure. Well, thank you for having us here and for the honor of being a finalist. Praedicat is a liability emerging risk analytics company. We started calling ourselves a casualty catastrophe modeling company back in 2012, and we quickly learned that the industry didn't really understand what casualty catastrophe was. When we explained what it was, that we were an emerging risk modeling company, they said, Oh, well, that makes sense.

We stopped calling ourselves casualty catastrophe back then, though we are returning to it now. Essentially, what we do is we identify emerging risks early, ideally seven to 10 years before litigation can even start. We do it by using AI on scientific literatures. We're trying to find where a scientist is hypothesizing in journal articles that some chemical or product or business activity results in bodily injury or environmental damage. We then we track the science as it evolves into a literature that can potentially be used in litigation as scientific evidence.

Once the science gets to a certain critical mass, we model the potential litigation that could emerge. We convert the model into company profiles, and we sell it as a SaaS [software as a service] product to insurers, who use it for underwriting, exposure management and, increasingly, for informing pricing and reserving and the like.

Insurance Thought Leadership

You had some pretty impressive examples of how many years you were ahead of a number of issues that are cropping up, like talcum powder. Do you want to talk about a few of those?

Robert Reville

Sure. When we were first launching our product, which was in 2013, the system already had in it the PFAS chemicals and talc and Roundup and chlorpyrifos. All of those are in litigation today, but the litigation started really after we launched. And every mass litigation that has started since 2013, when we launched our product, was in our system before the litigation began.

Some of them were completely off the radar screen of the industry. Sometimes, there's already a certain amount of buzz around something, and it, you could argue, is not that hard to catch. But there were some things that we caught that no one was thinking about, and then litigation started shortly thereafter. And we were found to really have delivered some useful early warnings.

Insurance Thought Leadership

There were a couple you mentioned that I'm curious about, that you say are in the pre-litigation phase now. There's one whose name I can't pronounce: phthalates.

Robert Reville

Right.

Insurance Thought Leadership

You'll say it right. And microplastics. I wonder if you could talk a little bit about those.

Robert Reville

Sure. Phthalates is a chemical that is an additive to plastics, typically added to polyvinyl chloride, which I think is possibly the most widely used plastic. It essentially makes polyvinyl chloride softer and flexible. So it's used in medical tubing. It's used in toys, things like rubber duckies. It's used in food packaging. It's used in all kinds of consumer packaging. 

It's so widely used, in fact, that it recently started to be called the everywhere chemical. Everybody is talking about forever chemicals for the PFAS. The everywhere chemicals are the phthalates. 

Recently, at the end of 2022, litigation started over hair relaxers, alleging that people who have their hair straightened frequently, that the chemicals that are put on their scalp, that they get into the bloodstream and can lead to uterine cancer. The scientific literature around these hair relaxers is pretty small, probably not strong enough to support litigation, but the plaintiffs’ attorneys have put in their complaints about the ingredients that go into the hair relaxers, and the number one ingredient that they highlight is phthalates.

What the plaintiffs are arguing is that it's the phthalates in the hair relaxers that cause the uterine cancer. The science is a little bit stronger about that than it is about the hair relaxers themselves.

Insurance Thought Leadership

To probe a little bit on that. When you spot something like this, insurance companies are buying this information from you, and they're changing how they underwrite? Or what exactly happens once you identify a problem like this potential one?

Robert Reville

When an insurance company works with us, the first thing they normally do is they take their casualty book of business and they enter it into our system. We model it, and we identify the exposure to all of the emerging risks in their portfolio. 

A typical situation would be, let's say, a particular company runs their model, and we find that the number one emerging risk in their portfolio is phthalates. At that point, they'd say, Oh, we need to control our total exposure to phthalates. So they develop an underwriting strategy that says, Well, if it's a chemical company, then we don't want to write that any more.

Then if there’s a downstream user of the chemical, such as a metal tubing manufacturer, we have a referral process. We want to evaluate the way the company handles the chemical, and then we want to control our total aggregations. 

All that data flows into an underwriting strategy, and then the underwriters at the company will follow the instructions that go with the strategy. So they have a new submission or a renewal, and they call up [the instructions]. They see that there's exposure to phthalates. There's either an exclusion required or a referral, and then when [a policy] is actually written, it goes into the exposure management system to control the total aggregation. That's an example.

Insurance Thought Leadership

Okay. So I cut you off. You were saying….

Robert Reville

Well, I was about to say that the question on phthalates in hair relaxers is, if the science has accepted that the phthalates are causing the uterine cancer, then what we expect is that it'll spread from hair relaxers to all these other uses. Then we'll have a full-on, everywhere chemical litigation that's happening at the same time we have the forever chemical litigation. That's potentially a worrisome situation for casualty insurance. 

Insurance Thought Leadership

Okay. And then microplastics?

Robert Reville

Microplastics are the breakdown particles as plastics degrade in the environment. And, as I mentioned, we track science from the time of the early studies as an early warning system. The literature around microplastics has grown faster than any literature we have been tracking since the beginning of Praedicat. There are now about 15,000 studies published that are examining the impact of microplastics in the environment, the way in which microplastics can enter the body, the way in which they're carried by weather around the globe, where they go once they enter the body, how they end up in the brain. 

Recently, there was a study that actually was looking at how microplastics, which are in the atmosphere primarily in urban areas because of tires -- they come off of tires – actually attract water vapor at different temperatures than clouds normally form at. They start to form clouds and can change weather patterns.

The extent of impact of microplastics in the environment is so great that the potential avenues for litigation being identified in the scientific literature are pretty enormous. We think the impact could come out in many different ways and are working with our clients around exactly how to think about where the exposures might be. There has been some litigation, nothing insurance-relevant yet, but consumer litigation and the like. We are seeing 65 cases in the U.S. courts right now…. We can start to get a sense of who the defendants might be and start to work with our clients early on what their total exposure might be.

Insurance Thought Leadership

That's fascinating. Any other things we ought to be watching for?

Robert Reville

Well, we have 300 in our system. 

I would say that another area that is worth talking about is generally climate. Climate is an area where there has been some litigation. In particular, there are about 50 cases in the U.S. courts, typically brought by states’ attorneys general, and they are alleging that, typically, oil and gas companies have caused climate change. Those cases are really the first wave of potential litigation over climate. And when we say climate, we expect there's going to be potentially litigation over what caused climate change. That may also be followed by litigation over failure to protect against the consequences of climate change. We've already seen some of this. 

I'll give you a quick example, though, of the kinds of unexpected things that will happen as a result of climate change. The scientific literature, in the mid-2010s, about 2015 or 2016, started to identify this issue that increasing droughts and increasing heat were causing concentrations of arsenic in soil. Rice plants tend to pick up the arsenic from the soil, and so some scientists started to argue that because of the fact that baby food uses rice as its backbone, that there would be litigation over elevated levels of arsenic in rice in baby food. We actually caught that literature and highlighted it to our clients before the litigation began. Then in 2021, a congressional report came out looking at heavy metals in baby food, specifically identifying elevated levels of arsenic, and the litigation was off to the races. 

It's still going on. There are, I think, both baby food manufacturers and retailers named as defendants. There are, I think, over 100 defendants so far, thousands of cases, and we'll see where it goes. But the interesting thing is all that was caused essentially by the changes in the environment from climate change.

You could argue that's the first product liability that resulted from climate change. Those kinds of things, we expect to see more of. 

We're also doing a lot of work on potential liability consequences after urban heat waves. Scientists have argued that in coming years the potential is for there to be heat waves that are worse than anything we've ever seen. If combined with blackouts, there could be a large amount of deaths in urban areas. Given those types of models, we have looked at the potential liability consequences for companies that would arguably have been responsible for taking care of vulnerable parties. So nursing homes, schools, day cares, etc., also habitational real estate. 

This is a phenomenon that hasn't yet happened, but it's worth working through the liability consequences, given the projections coming from the climate scientists. 

Insurance Thought Leadership

Great. A bunch more reasons for me not to sleep at night. 

Thanks for taking the time. Congratulations on being a finalist, and I'll be fascinated to follow your work.

Robert Reville

My pleasure.

Until recently, it was said that the only constant was change – now the only constant is uncertainty. 

Uncertainty is at a generational high in almost every aspect of our lives: socially, financially, politically, and technologically. One of the most serious consequences of this uncertainty is its impact on risk assessment across all lines of insurance. However, it also represents a major opportunity for insurers.  

The model of risk transfer is centuries old and thrives on predicting when and how much known exposures are likely to happen and what the costs involved are. Thus, not all risks are insurable -- such as moral hazards where the incentives are misaligned. Risk transfer is further disrupted when doses of uncertainty distort predictive models.  

Uncertainty exists when the magnitude (frequency and severity) of possible future events is obscured, making reasonably accurate forecasts unreliable. As uncertainty grows, the ability to effectively manage risk is proportionally reduced.

The implications of this new normal for insurance are existential for some insurers and more expensive for all, as it becomes harder to assess and properly price risk in the face of so much uncertainty. Not to mention the havoc that uncertainty wreaks for most consumers and businesses, including on insurers’ ability to plan and adjust. A result is uncertainty about insurance availability, degree of premium increases and extent of reduced coverage.

To make matters worse, several carriers seeking to contain risks have been withdrawing from regional markets where recent losses have unexpectedly spiked as a result of unprecedented losses from extreme weather exacerbated by ill-prepared mitigation. These pullbacks, which already target approximately 15% of U.S. property, are not only detrimental to policyholders in the affected regions but also undermine the benefits of risk pooling for all policyholders.     

Yet the idea of insurance is to provide a promise of protection and safeguard against uncertainty. This goes beyond the functional insurance contract and strikes an emotional nerve, as well – peace of mind. The proverbial security blanket serves in more than one way, and the industry will hopefully find the right balance.

Trade/Geopolitical Uncertainty

In the wake of President Trump’s on-again, off-again, up-again, down-again trade tariff announcements – and the retaliatory counter tariffs from the world’s largest countries – economic uncertainty has evolved almost overnight. Markets are similarly volatile, prompted by the uncertainty of how far tariffs and reciprocal action will go. At present, we are now officially in a stock market correction, in which a stock market index drops by more than 10% and indicates pessimistic investor sentiment.

Facing unexpected market volatility and geopolitical uncertainties, normally optimistic dealmakers are sounding a more cautious note for the coming weeks and months but are confident the pace of mergers and acquisitions will pick up later this year.

The costs associated with auto and property insurance are especially exposed to tariff impacts, including increased cost for new and used vehicles, repairs and replacements parts. Bob Passmore, department vice president of personal lines at APCIA (American Property Casualty Insurance Association, the primary national trade association for home, auto, and business insurers), estimates that the impact of tariffs on personal auto insurance could range from $7 billion to $24 billion.

Undoubtedly, even higher premiums will follow quickly, and the insurance protection gap will continue to widen should retaliatory tariffs actually stick. Either way, insurers are watching loss costs closely.

Consumer Sentiment

Consumers sentiment is down significantly month-over-month and year-over-year. It slid nearly 10% from January and fell for the second straight month. The decrease was unanimous across groups by age, income, and wealth. The Consumer Sentiment Index fell to 64.7 in the February 2025 survey, down 9.8% from 71.7 in January and 16% below last February’s 76.9.

Consumer sentiment is considered a leading indicator of economic activity. Sentiment levels can also affect consumers’ willingness to make large purchases such as automobiles. Over the last 18 months, policyholder behavior has changed around smaller losses. They forgo making claims for fear of premium increases or select higher deductibles and drop coverages. Meanwhile, credit card debt is over $1.21 trillion; negative equity in auto loans has reached a record, and late payments are on the rise.

Executive Stress

More than two-thirds of executives polled in a recent survey reported feeling more stressed at the beginning of 2025 than they did at the start of 2024. The survey, conducted by Wakefield Research on behalf of Sentry Insurance, found stress levels elevated in 67% of participants. At the same time, 74% of executives said they were not completely confident that their company’s current insurance coverage is adequate.

Economic uncertainty (47%), supply chain challenges (44%), costs of employee health care (41%), labor shortages (38%) and inflation (36%) ranked as the top five concerns among the survey participants.

Extreme Weather Uncertainty

The continuous increase in extreme weather events, and the attendant economic and human losses, are not new but are being made worse by what is now emerging as compound weather events. Cascading extreme weather events are unleashing billions in additional damages. This was clearly and tragically witnessed from the LA area wildfires, where fire prevention and responses proved shockingly inadequate. Add in regulatory rate suppression, and this becomes an untenable scenario.  

More than 100 fires ignited in South Carolina, Oklahoma and New York last weekend, fueled by a combination of arid air, dry fuels, and gusting winds, all compound weather events. We have much less data and research on these so-called secondary weather perils as compared with hurricanes. And convective storms have proven to be more challenging to translate into risk management.

Researchers and experts warn that the frequency and impact of compounding events will increase and that developing better models and preparedness strategies is crucial to mitigate the risks ahead, with some looking to Japan's earthquake preparedness culture and massive investment as a potential model.

Managing Uncertainty in Insurance

Even in periods of extreme uncertainty, there are several strategies available to carriers aside from rate actions.

Rising catastrophe losses, technological transformation, and evolving risk landscapes are forcing insurers to fundamentally rethink their approaches to underwriting, claims processing, and customer engagement, according to Datos Insights.

Insurers can diversify their portfolios to reduce the impact of any single line. At present, profitable auto lines are now highly coveted as competition has surged. Just a couple of years ago, insurers were shedding personal lines policies, as rates could not keep pace. Auto insurance lines are now forecast to have favorable loss ratios through 2027. The advantage goes to carriers growing their auto books profitably with rate-friendly tailwinds.

Excess and surplus lines grew 12%, reaching $81.6 billion in premiums last year, further demonstrating diversification opportunities. Similarly, the MGA distribution model expanded hand-in-glove, serving specialized markets and regions such as coastal exposed areas.

Carriers have always used sophisticated pricing and underwriting models, and the application of AI is expected to make them even better when it comes to ingesting more data and testing risk models -- as in digital twin comparisons and visualizing impacts well beyond just numbers on paper. This is extremely valuable in projections because historic models look backward to look ahead.

Likewise, investing in claims is a priority as worthy efforts to streamline are balanced with controlling loss costs at a time when adjuster resources are squeezed from retirement “brain drain” at the most skilled levels. Technology investment must go beyond core system upgrades to greater digitization while orchestrating the multitude of new tools, integrated provider partners and the numerous insurtech opportunities circling the tower and waiting for a landing spot.

New insurance products, high consumer awareness translating to greater insurer/policyholder engagement and joint risk management are evolving and opportune. 

Now more than ever in our insurance history, greater resilience and innovation coupled with a transition to a Predict & Prevent defensive posture is critical and urgent. 

Paul Carroll 

Things are so crazy in Washington DC these days that I can’t ask you for the sorts of precise predictions on inflation, GDP, prospects for the insurance industry, etc. that we usually discuss. What passed for U.S. economic policy this morning could be rather different by this afternoon. So I’ll ask you, more generally, what key trends we should watch out for in terms of the effects of tariffs and in terms of the broader economy.

Michel Léonard

Yes, while our conversations are generally pretty evergreen, I’ll note that we’re talking on March 7th at 1:00 PM Eastern time, which is relevant given yesterday's announcement about suspending some tariffs on Canada. Let me outline where we stand and the key baselines we should consider.

Regarding the economy, while growth has been diminishing, the economy has remained resilient. The key question now is whether this resilience is sufficient to survive the current instability and uncertainty. As of this first quarter, I believe we still have enough GDP momentum to weather what we're seeing now, even if these conditions continue for a full quarter. However, the risk of GDP contraction rather than growth is certainly present.

On inflation, we've seen it coming down to sustainable levels, which we define as 2% to 3%. The Fed has indicated it will tolerate inflation up to 3% before taking action. Looking at the baseline for interest rates and monetary policy over the next year, the trend line remains accommodative, with two main concerns: inflation resulting from tariffs and potential policy misjudgments. 

As [former Fed Chairman Alan] Greenspan used to say, the medication must fit the disease. It's important to remember that rising interest rates are effective when inflation is driven by consumption. Higher interest rates can drive down demand. However, when inflation is driven by tariffs or other factors related to consumption, raising interest rates doesn't work.

We're likely to see inflation hovering between 2.5% and slightly above 3%, without factoring in geopolitical risk. Continued geopolitical risk will put upward pressure on inflation. 

Looking at the big picture for the economy, I still see this year being resilient, ending with flat to slightly positive growth.

Paul Carroll

The Atlanta Fed recently forecast a potential 2.5% to 3% annualized decrease in GDP for the first quarter. Is that an outlier, or might that be correct?

Michel Léonard

When considering benchmarks for comparison, I think back to the first year of COVID, when we faced tremendous uncertainty around March 2020 regarding GDP projections. Firms like JP Morgan and Goldman were suggesting potential contractions of up to 30% -- numbers that were unprecedented but that made sense given the unique circumstances.

We're again in an environment of extraordinary uncertainty. We may be getting tired of describing everything as unique and new, but this situation truly is, perhaps even more so than before. 

At this point, I don't think we can clearly distinguish where performative policymaking ends and where the real impact on growth and growth expectations begins. Just yesterday, we saw another 30-day postponement in the imposition of tariffs, and there's fatigue around that. The market today is hovering flat after one of the worst weeks in a year, and there's fatigue there, too, as we would expect. While I traditionally focus on the real economy as an economist, my current concern is market sentiment.

The resistance in the market that keeps prices from going even lower stems from those of us who remain optimistic about growth this year -- and there are fewer and fewer of us on the optimistic side. Each time there's a performative announcement, the market's recovery within the following days becomes less robust. 

That exhaustion could lead to the Atlanta Fed's -2.5% projection happening for the full year, but that would require a very significant correction in this quarter and next quarter, and I don't think we're there. I don’t think that sort of contraction in the first quarter alone is possible. 

Paul Carroll

How much do you think Trump’s tariffs could drive up replacement costs, which have been such an issue for insurers in recent years?

Michel Léonard

Double-digit tariffs are not marginal adjustments. They're not about moving production -- they're about stopping production entirely.

Let me break this down step by step. First, as a baseline, we can look at what we experienced during COVID. Certain segments of the economy and insurance were particularly affected -- especially the auto sector. Due to supply chain issues, used auto prices soared. Interestingly, autos and motor vehicles are also key targets of potential current and future tariffs, so there should be some parallel with the COVID situation.

The impact of tariffs is already visible through uncertainty alone. People are already changing their purchasing decisions regarding cars. For example, in Canada, buying patterns are shifting. I'm originally from Canada, and my brother, who owns two American cars and was considering a third, suddenly changed his mind about buying another American vehicle. Similarly, bourbon producers in Kentucky are seeing demand drop because Ontario's liquor board, the world's largest buyer of alcohol, followed by Quebec, is already making different purchasing decisions.

For motor vehicles, we will inevitably see a significant drop in underlying growth, even if tariffs are suspended indefinitely, because the uncertainty is already present. This affects replacement costs for parts and repairs, though less so for labor. During COVID, replacement costs for motor vehicles -- both personal and commercial -- rose around 60%, largely due to used auto prices. I could see this happening again, following a similar timeline.

Ultimately, I believe we'll retain some version of Auto Pact, the predecessor to NAFTA. We'll likely end up with a cosmetic renegotiation -- remember, the current North American free trade agreement was negotiated by President Trump. The real question is timing -- whether it takes one month, three months, or six months. Insurance underwriters and industry professionals should be prepared for increases that could approach those COVID-era numbers for motor vehicles, the longer this situation persists.

And these double-digit increases in tariffs on lumber, auto parts and other materials don't just mean higher replacement costs – they mean many materials aren't available through the supply chain.

During COVID, lumber was still available, but we just couldn’t get auto parts and used cars. Now, we need to anticipate that goods will be stuck in transit at borders, creating significant delays. For people on both sides of the transaction – whether it's carriers handling rebuilding and repairs or homeowners getting their properties repaired – the issue is going to be time. We'll likely see more delays and uncertainty than we did during COVID.

Paul Carroll

I suspect we’re just getting started on the effects of these policy changes and all the uncertainty that surrounds them. Even if Trump’s protectionism proves short-lived – and I’m not sure it will – companies will have to rethink their global strategies. That could cause major changes to supply chains… and the companies that insure them.

Michel Léonard

As an American who immigrated from Canada, I've been shocked by how seriously other countries are taking these developments on protectionism. Those of us looking at this professionally know these are serious issues, but we also see a performative form of policymaking.

Those of us in the U.S. lived through the changes during the first Trump term, but it doesn't seem the rest of the world experienced it the same way we did. I've been surprised by that, and I think it's significant in terms of the damage done. It's quite difficult to imagine that the same level of trust will remain, for better and for worse. 

There are certain areas where change is good, and even if it's constructive destruction, sometimes it is useful. But I do think there is a great deal of damage. 

Paul Carroll

Do you see any historical parallels to what we’re going through?

Michel Léonard

What we're facing is potentially comparable to Margaret Thatcher's first two years as prime minister in the U.K. When Thatcher came in, she cut government spending, privatized industries, and moved extremely rapidly. She was actually on track to lose her position until the Falklands War came about and allowed her to recover politically. During this period, the U.K. experienced one of the deepest recessions since World War II.

That's the kind of economic pain we could be talking about here, but potentially on an even larger scale because it's the U.S. The agenda we're seeing now is even more transformative. The individuals involved in the current administration are much more like outsiders compared with those in Thatcher's administration, which makes this an even more striking parallel.

We're potentially looking at unemployment reaching high single or double digits, which in the U.S. has rarely happened since the Great Depression. This is why I'm concerned about the scale of transformation. We're not just looking at a typical stock market correction of 5% or 7% -- we're potentially looking at something that combines the impact of all previous corrections together. 

I haven’t given up. I’m still an optimist. But the potential implications go far beyond simple replacement costs, and that's what makes this situation particularly challenging.

Paul Carroll

Thanks, Michel. Fascinating, as always. 

In 2009, I gave a talk to a group of about 20 Silicon Valley CIOs, who were focusing on a novel question: what to do about all the personal smartphones employees had begun using since the introduction of the iPhone two years earlier. 

The inclination was to ban them for business purposes, or at least to tightly restrict their use. After all, employees had almost exclusively used company-issued electronics for their work, and CIOs liked the control that ownership of the devices gave them. 

Besides, smartphones introduced all sorts of complications. What if a company sanctioned the use of personal phones and an employee got distracted and had a car accident? Would the company be liable? What about protections for corporate data? If employees routinely used personal devices for work, they could much more easily walk off with company secrets. How would you even incorporate all the different flavors of smartphones into the IT infrastructure?

Now that we're a bit more than two years into the generative AI revolution, we're about to face the same sort of adjustment and discomfort because "bring your own" AI to work will happen more and more.

The good news is that, as employers and employees cope with the confusion, we can learn some lessons from what happened with smartphones and other waves of innovation. 

Let's have a look.  

The first lesson is that employers can't resist the trend toward BYOAI any more than King Canute could command the tide to stop coming in. Current employers are getting accustomed to using generative AI and will want to keep using the same large language model (LLM) when they move to a new employer. All the digital natives entering the work force from college will expect to have access to the AI tools they've been using in coursework or experimenting with on their own. 

Employers will have more control with BYOAI than they did with smartphones, because licensing fees for LLMs can be steep, and most employees will rely on their employers for access, rather than just heading to Best Buy and purchasing something on their own. In addition, as insurance companies increasingly develop specialized tools for agents, claims representatives, underwriters, etc., employees will have to fit into the corporate system.

Still, some uses of generative AI, such as individual productivity tools for research and writing, will be based on personal preference, and employers should be prepared to try to accommodate employees. Employers should actually encourage experimentation with models and templates built on top of them. That's because, while most innovations need to be sponsored by a manager or even the C-suite, a lot of innovation with generative AI can bubble up from the lower ranks. Yes, rethinking a claims process is a major, departmentwide or companywide endeavor, but individuals are finding ways to improve productivity for themselves and the small groups they may work in, and that sort of progress should be encouraged.

A second lesson from earlier technological leaps is that there will be legal issues. There are always legal issues. 

One will concern just what I can bring with me if I go to a new employer. If I've finetuned an editing template on top of an LLM you've bought me access to and did the work on your time, is that template my property or yours? I suspect it's yours, but those are the kinds of issues courts will sort out. 

Generative AI will also make it easier for people to walk off with information that companies will view as proprietary data and trade secrets. Part of the magic of generative AI is that it can amalgamate data from so many different sources, so quickly, and many companies are using that capability to speed underwriting and other capabilities. But that ease of access also means many employees may be able to get into far more internal systems than they could in the past. 

There will also certainly be copyright violations, because generative AI systems scoop up so very much information and sometimes don't flag that what they're producing in reply to a prompt is drawn almost verbatim from text or an image. That's a problem, in general, but will be more severe with LLM use that happens outside of corporate standards. 

The third big lesson I see is that BYOAI will make it harder to have a "single version of the truth," just as spreadsheets and PowerPoint presentations did. With spreadsheets and PowerPoints, individuals would use corporate data but would interpret it in their own way. They would sometimes get the data wrong or misinterpret it. They would also supplement the data with other sources. When they were done, they had come up with their own version of the truth, and it stayed on their computer, generally not available to others and not synched up with others' versions of the truth. 

CIOs have been fighting the battle over data consistency for decades, and they'll face it again with generative AI, in general, and with BYOAI, in particular. People will again download information, process it with AI, add their thoughts and produce a version of the truth that will generally stay on their computer. That so many companies operate in the cloud these days could make synching up easier, but CIOs will have to work to make sure they don't face the kind of splintering that happened with earlier technologies.  

How, then, should insurance companies react to the issues that BYOAI will raise?

Some MIT researchers have three general suggestions, as reported in the MIT Sloan Management Review.

They warn, off the top, against banning BYOAI tools:  

“If we restrict access to these tools, employees won’t just stop using generative AI. They’ll start looking for workarounds — turning to personal devices and using unsanctioned accounts and hidden tools. [In that case], rather than mitigating risk, we’d have made it harder to detect and manage.”

Then, they recommend:

"1. Build specific guidance. 

Leaders should develop clear guardrails and guidelines that enable employees to experiment safely with generative AI tools. Company experts in technology, law, privacy, and governance should be tapped to develop policies on sanctioned and unsanctioned generative AI use and specify which tools are acceptable and under what conditions.... 

"One leader on the MIT CISR Data Board [said] their organization clearly communicated approved uses of generative AI to employees, such as using publicly available information in their AI queries, versus off-limits uses, such as uploading data that contains personally identifiable information, strategic information, or proprietary data. The organization also had a clear process in place for anyone who was unsure about whether AI use was appropriate....

"2. Develop training and establish communities of practice. 

"Organizations should develop AI direction and evaluation skills to help employees use generative AI tools effectively. This training should cover the AI models that power generative AI tools, ethical and responsible use of AI, and how to critically judge AI-generated content....

"For example, the data and analytics unit at animal health company Zoetis holds twice-weekly office hours during which employees can learn how to start using generative AI tools and ask questions. This helps employees learn, improve over time, and build confidence..... 

"3. Authorize certain generative AI tools from trusted vendors. 

"Staying current with the ever-evolving market for AI tools requires considerable time and effort. To crowdsource this process, create a cross-functional team tasked with evaluating tools and giving feedback to IT about which tools promise real value....

"To simplify AI access and encourage employee use, Zoetis set up a generative AI app store in which employees can apply for tool licenses and learn about effective and responsible use. For each tool, employees can access guides for getting started, watch training videos, read the organization’s AI policies and guidelines, and more. Employees are also encouraged to submit stories describing how they used a tool. This feedback has helped the organization understand which tools deliver the most value for employees."

I suspect we'll wind up feeling our way through a lot of the issues, through trial and error, much as those Silicon Valley CIOs wound up doing with smartphones. But at least we can get a sense from history of the sorts of issues employers and employees will face as they adjust to generative AI and can avoid some of the potholes we've hit in the past.

Cheers,

Paul 

While third-party administrators have a long history of serving the insurance industry and have bright prospects, they face a once-in-a-generation change: generative AI.

AI Incoming

Prognostications on the impact of AI are ubiquitous – with insurance claims ripe for transformation. Several opportunities exist for AI to enhance or redefine the claims process, such as:

• Fraud Detection

• Claims Prioritization

• Claims Processing

• Settlement

• Subrogation

While the possibilities are nearly endless, the trend is clear – AI is changing the nature of the claims business in a way that will affect the relationship between third-party administrators (TPAs) and carriers.

First, AI is changing the nature of claims administration by challenging where human interaction (and judgment) is needed. Simple claims will see auto-adjudication without the need for an adjuster. We are already seeing carriers experimenting with this approach in the event of simple auto claims where photos and documentation result in near-instant decisions.

Second, AI should have a deflationary impact on the cost of administering claims. Pricing assumptions to manage claims on behalf of another entity are largely driven by labor costs. AI will change this by creating capacity for claims personnel, achieving both margin improvement for the TPA and potential cost savings for the TPA's client.

Third, AI will affect non-claims administrative work, such as in the contact center. AI use cases are often focused on call deflection, but everything from workforce management to key contact center metrics (e.g., average handle time [AHT]) will be affected by AI, creating additional capacity and challenging key assumptions in the TPA model.

A Brave New World For TPAs

AI will challenge the TPA market, but it will also present opportunities for those nimble enough to take advantage of them. The market has had an 8% compound annual growth rate (CAGR) over the last five years, and the increased cost associated with claims administration will only increase growth for TPAs. 

There are three opportunities for TPAs to provide greater value to insurance carriers:

1. Embrace the Complex – AI will drive down the volume of simple claims that require adjusters. It will also highlight the need that carriers, managing general agents (MGAs), employers, and others in the insurance ecosystem have for expertise to process the most complex claims. TPAs that possess the expertise to manage these claims will be in a position to grow market share.
2. Provide Data and Analytics Services – TPAs have an opportunity to leverage AI in their own operations to provide valuable insights to carriers and employers. Specifically, they can focus on providing data on what is driving claims for carriers to better underwrite in the future. This has historically been an area where carriers have struggled to gain insights.
3. Loss Prevention Services – In an era where the frequency and severity of claims are increasing, understanding how to mitigate or even potentially prevent claims provides even more valuable insights, both to TPAs and their clients. TPAs that can gain insights from their data and engage in root cause analysis on behalf of their clients can develop business units focused on loss prevention.

Why Now?

The TPA market has historically been controlled by large players. Specifically, TPAs servicing large/jumbo carriers and employers for claims administration have been able to keep entrants out due to their size.

AI changes all of this. The ability to leverage AI and other technologies successfully will allow traditionally smaller players to compete with medium and large TPAs.

In addition to this, carriers, MGAs, and others in the insurance ecosystem are exploring creating their own TPAs to meet their unique needs. What once was an expensive capability is now significantly more affordable due to technical innovations.

TPAs that do not look to enhance their existing offerings with new value risk losing significant market share. TPAs can no longer afford to simply rely on their size and scale to keep entrants out of the market, particularly if they are not price competitive.

The recent wildfires in Southern California have had a devastating impact, further straining the insurance industry and exposing serious gaps in traditional home insurance. With at least 200,000 displaced residents, 16,000 structures destroyed, and $250 billion in estimated economic losses, this catastrophe is poised to become the costliest natural disaster in U.S. history, surpassing even Hurricane Katrina.

As severe weather becomes a pressing reality for more Americans, insurers must reexamine existing policies and explore new models to ensure both consumer protection and industry sustainability. This latest catastrophe underscores the need to address three critical areas: population growth in disaster-prone areas, extended seasonal disaster threats, and the role of immediate services and assistance to displaced policyholders. By recognizing these challenges, we can develop solutions that better serve clients and support their financial stability.

Increasing Risk in Fire-Prone Areas

Housing development and population growth in disaster-prone areas present a growing challenge for the insurance industry. As residents move to these regions seeking affordable housing, they may not fully understand the exposure to potential loss associated with their location. In the last 30 years, the populations of high-risk counties have grown three percentage points faster than low-risk counties. From an insurance perspective, underwriting policies in these high-risk zones has become increasingly difficult. Insurers must account for heightened risk factors through higher premiums, reduced coverage options, or, in some cases, complete withdrawal from certain markets (such as California and Florida).

Extended Seasonal Threats

Furthermore, the Southern California wildfires occurred outside the typical wildfire season (June to October), highlighting the consequences of extended seasonal threats. Data from the NOAA illustrates how wildfires and other extreme weather events are beginning to persist year-round, beyond the scope of traditional risk planning. While factors like prolonged drought conditions can be managed and mitigated, insurers must account for today's increasingly unprecedented climate landscape in their policy offerings. This is also where local municipalities can collaborate with state and national funding programs to tackle projects designed to protect and future-proof infrastructure and property.

The Challenges of Displacement

In the aftermath of a wildfire, affected residents are faced with a slew of immediate hurdles, including finding temporary housing and accessing funds for essential expenses. The emotional and financial toll can be overwhelming, exacerbated by delays in claims processing and uncertainty about when or if their losses will be fully covered.

While insurance plays a crucial role in disaster recovery, the current claims process is often too slow to meet urgent needs. Policyholders may struggle with steep deductibles, lengthy claim assessments, and documentation requirements that hinder the rebuilding process. While many insurers cover temporary housing and other costs while a policyholder's home is uninhabitable, disbursement of these funds is frequently delayed by claim verification procedures, exclusions or coverage limits, leaving people responsible for significant out-of-pocket expenses. The average claims cycle for catastrophic events reported in 2023 was over 34 days, prompting a look at supplemental coverage to secure one's more immediate needs in the aftermath of a disaster.

The Need for Comprehensive Coverage

With these concerns in mind, the industry can look to parametric-style insurance solutions to expedite flexible financial relief. Payout models based on predefined triggers, like a wildfire, can ensure that policyholders have the resources they need when they need them most.

Multi-peril supplemental coverage, like Recoop Disaster Insurance, can diversify protection across multiple hazards while stabilizing premiums and reducing financial strain on traditional insurers. Partnerships between traditional home insurers and supplemental disaster insurers can establish robust, comprehensive coverage, particularly in high-risk regions where traditional policies are becoming increasingly unaffordable or unavailable. By offering lump-sum funds for a variety of perils within a single policy, the industry can simplify the process for homeowners and provide timely, critical first dollar coverage and financial assistance needed for meaningful recovery when the insurance industry's response threshold is tested most.

Forging Ahead

The Southern California wildfires serve as yet another wake-up call for the insurance industry. Traditional models are struggling to keep pace with the growing scale and frequency of natural disasters, leaving both insurers and the insured in a precarious position. By adapting to changing risk landscapes, exploring multi-peril coverage solutions, and putting client support at the center of industry strategy, insurers can evolve to provide more resilient protection for an increasingly uncertain future.

Insurance leaders are rapidly adopting tech tools. Following a few key steps can make the purchase process nearly painless.

Generative AI is primed to disrupt insurance and all other sectors. A recent IBM survey found that 77% of insurance executives say they must adopt AI quickly to keep up with their rivals. Beyond AI, the insurance technology market is predicted to grow 27% by 2033.

So, what happens when it's time to adopt new technology? For any tech solution that has the power to transform your business, you must meet disruption with deliberation.

Consider why the technology is needed and how it fits into the business. Then start your purchase by thinking about the decision process.

Identify key stakeholders

Before heading down the road of deploying new technology, identify everyone affected by it: the staff who use it, the clients who benefit from it, and the executives who approve the budget. Then, make sure to bring them along.

Getting support from each of these stakeholders takes more than just a pitch. Be transparent and remember that communication involves listening as well as sharing feedback.

Talk to stakeholders about why the new technology is needed and listen to any concerns. Technology should help meet business goals—such as improving renewal rates, reducing claims cycle times, or enhancing agent satisfaction—rather than being a trendy upgrade. Keep those goals in mind, and note challenges, wants, needs, and expectations.

Staff might have concerns about their job security, for instance. Be honest about those impacts. Emphasize that the goal isn't to replace them but to reduce repetitive work so employees can focus on higher-value tasks.

Or it might seem like leaders are resistant to change. Many independent agencies like paper and have been using their current processes for a long time. Make it clear why change is needed.

Launch a search—and prepare for responses

Organizing the search is a key step to finding the best partner for the job. Whether launching a formal request for proposal (RFP) or conducting an internal evaluation, detailing the process will help make a transparent, predictable, and auditable deal.

Here are the four steps of crafting a great request for bids:

• List goals. Detail how the new technology will be used. The vendors are the experts. By sharing your goals, vendors can help find unexpected ways to accomplish those goals.
• Outline the scope of the project. Transparency starts right away. List the expectations for the vendor and get ahead of any potential hurdles.
• Set the budget. Be clear about how much money can be spent on the project. And discuss internally how much extra to set aside in case the project grows beyond the original scope.
• Lay out the timeline for making a decision. Set a timeline for the decision process and stick to it. Let vendors know what steps are along the way and how communication will happen.

Laying out each of these pieces helps the communication process with vendors and makes it easier for them to know how to respond with all the useful information.

Self-evaluation, then evaluation

Maybe the most important step is what comes after the search: evaluation.

Before even looking at the first response, detail the decision process including the criteria that will be used for evaluating responses and how internal disagreements will be resolved.

Putting the decision process in writing can help in the tricky situation of getting too many good responses that need to be narrowed down.

If the call is tough to make, consider what is most important for meeting business goals. The lowest-price vendor might not offer key features or integrate with other tools. Or the technology with all the bells and whistles might be more than what's actually needed.

When evaluating a vendor, consider everything they have to offer. Not only should they meet the project's goals but also assess whether they can provide continuing support and if you trust them as a partner, because relationships matter.

Once you're ready to make a deal, stop to make sure everything lines up with the criteria that was set in the first place. The end goal is to find the solution that will best serve clients. Don't lose sight of that.

Know when to pivot

Ending an agreement or restarting a search isn't easy. When a vendor just isn't working out, don't fall for the sunk-cost fallacy. Refer back to the original criteria.

It's time to pivot when you've exhausted all possible workarounds. If the business doesn't meet the needs of the three stakeholder groups—clients, business leaders, and employees—or can't meet the terms of an agreement, it's time to pull the plug.

Flexibility is key to adapting when things don't go as planned.

When implemented thoughtfully, technology can benefit insurance agencies and carriers tremendously. These steps can help focus the decision-making process on what matters most and avoid common roadblocks.

With the right approach, new technology can help enhance customer service, improve operational efficiency, and stay competitive in an evolving market.

From real-time threat intelligence and continuous risk assessments, to penetration testing and cyber awareness training, the range and sophistication of tools and services designed to help businesses strengthen their cyber resilience strategies today is impressive.

Yet many U.S. businesses — even those that are larger, with typically bigger security budgets — still do not fully use proactive cybersecurity services. The 2024 Cybernews Business Digital Index, for example, shows that 84% of analyzed Fortune 500 companies scored a D or worse for their cybersecurity efforts, while small businesses often lack the resources to implement robust cybersecurity measures themselves.

Looking more granularly, there are further gaps to uncover across businesses of all sizes. For example, GetApp research suggests that 72% of C-suite executives — who hold critical business data — are targeted by cyberattacks, yet 37% of companies provide no extra protection for them. Meanwhile, just one in five companies say they're "very well prepared" to defend against high-volume AI-powered bot attacks.

These gaps sit alongside the fact that cyber threats are increasing in frequency, complexity and severity, triggered by geopolitical instability, out-of-date encryption methods and, of course, advances in AI. The result has seen the 2024 global average cost of a data breach reach $4.9 million — the highest figure yet and a 10% increase from the previous year — while ransomware alone costs an average of $5.2 million, with thieves having stolen over 1 billion records.

While some businesses operating among these risks have recognized the importance of investing in strategies that anticipate and mitigate risks before they materialize, gaps still remain.

Recognizing this, the cyber insurance industry is stepping in with efforts to strengthen the cyber defenses of its policyholders.

A shift benefiting policyholders, brokers and insurers alike

Aside from rising cyberattacks necessitating change, cyber insurance providers are also aware that any efforts that encourage businesses to be more proactive in this field are beneficial to all parties involved.

• Brokers: By positioning themselves as a trusted adviser and key part of businesses' resilience strategies, brokers can offer clients more than just policies.
• Policyholders: By following integrating advanced security solutions as part of their insurance adoption, businesses can not only reduce their exposure to cyber risks but also strengthen their overall security posture. What's more, some insurers even offer enhanced coverage benefits for policyholders who fully implement these defenses, reinforcing the value of leveraging insurance as a tool for resilience even more.
• Cyber insurers: By positioning themselves as partners in resilience, rather than just claims support providers, insurers can help businesses strengthen their cybersecurity posture, ultimately leading to fewer claims and a more robust underwriting model. As policies are increasingly structured and priced based on real-time risk assessment and continuous security improvements, rather than just historical data, the shift will ultimately transform the future of underwriting and claims.

Cybersecurity services and tools on offer

With the above in mind, many insurers are now offering their policyholders a range of cyber services at no additional cost. Examples include:

• Micro penetration testing: Preliminary penetration tests that uncover hidden system weaknesses before adversaries can exploit them.
• Phishing simulation and cybersecurity training for new policyholders: Advanced phishing simulations that mimic real-world attack methods to train employees to spot and avoid social engineering tactics.
• Cyber risk insights and recommendations: Comprehensive scans and diagnostics to quickly identify potential vulnerabilities, coupled with recommendations on remediation.
• Continuous risk assessment: of networks, endpoints, and cloud environments—ensuring any anomalies or threats are flagged in real time.
• Integration with leading security and IT platforms: Quick and seamless integration, enabling real-time risk scoring and insights.
• On-demand surveillance: of actively exploited vulnerabilities that have the potential to affect policyholders during widespread cyber events.

Alongside these, some are also branching out into offering subscription-based cyber resiliency services. These aim to offer advanced capabilities that will significantly enhance policyholders' cybersecurity posture, without requiring costly in-house resources. Examples include Managed Detection and Response (MDR) Security Operations Center (SOC)-as-a-Service, Penetration Testing-as-a-Service (PTaaS), Cybersecurity Training-as-a-Service (CTaaS), and monitoring of user access to cloud services.

The new industry standard

As cyber risks continue to evolve, it's my view that this proactive model of cyber insurance — one that goes beyond financial protection to actively enhance security resilience — will become an industry standard. And in the long run, businesses that embrace this shift early will be better equipped to defend against cyber threats, while allowing insurers to benefit from stronger risk profiles and brokers to play an even greater role in safeguarding their clients' digital assets.

Cyber insurance is no longer just about recovering from cyberattacks — it's about preventing them in the first place.

Over the last few years, artificial intelligence (AI) and machine learning have become integral to the insurtech industry. According to PwC, the global AI insurance market size was $4.59 billion in 2022 and is projected to reach approximately $80 billion by 2032, with North America leading the way. Most companies, whether they are traditional insurers or insurtechs, have a plan to implement artificial intelligence into their business operations and propel the industry forward.

As an insurtech, Cover Genius has embraced AI and machine learning since our inception to provide dynamic recommendations through our API. However, as LLMs (large language models) and generative AI continue to evolve, they promise to revolutionize even more business processes, such as integration, content creation, claims processing and distribution.

Streamlining integration

One area where AI can significantly support insurtechs is by streamlining integrations. Insurance policies are inherently complex, with different structures depending on the region, geography and underwriter. This complexity often makes launching an integration a time-consuming process, requiring extensive testing to ensure the right policy reaches the right customer in the right market.

However, AI is transforming this process by automating test cases and improving launch times. This technology enables faster, more efficient integrations, allowing brands to easily update or launch new offerings across markets. Previously, these changes required significant investment, making companies hesitate to change their offerings, even if it meant making them better.

By automating and streamlining the integrations, AI empowers insurance providers to improve and evolve their offerings with minimal investment, saving valuable time and resources while ensuring their policies meet regulatory requirements.

Content creation and claims processing

Another key area where AI is changing the insurance industry is content creation and claims processing. AI can assist in automating email responses, Web UI (user interface) translations and copy generation, leading to more personalized customer experiences, improved engagement with insurance offers and faster operations.

Additionally, AI enhances the claims process by facilitating document translation and data extraction during the claims process, making it easier for insurers to verify claims against policy coverage. By automating routine tasks such as data extraction, document verification, and initial claim assessment, companies can reduce manual intervention and human error. In addition, AI-driven chatbots and virtual assistants can handle repetitive, administrative queries from clients, freeing staff to concentrate on higher-value-added tasks, such as coverage-related queries.

Complex claims cases will always require human oversight, but this approach helps speed response and resolution times so customers are not out of pocket on expenses for too long. At Cover Genius, we combine AI capabilities with human expertise to create claims experiences that are faster, more personalized and supportive of customers in their time of need.

Distribution and personalization

In distribution, AI enhances customer support by answering questions throughout the policy lifecycle – not just at the time of a claim. For example, advanced demand modeling and automated segmentation can contribute to more tailored offerings. If a customer books a winter flight to Switzerland, they can be identified as a candidate for ski coverage in addition to standard travel protection. As segmentation becomes more sophisticated, it unlocks new ways for customers to interact with platforms, making it easier to access relevant information and coverage quickly.

Balancing risk and compliance

AI is still a new technology, so while it is a powerful tool that can improve aspects of insurance, companies must proceed with caution, especially in areas where they are providing consumers with information about insurance products. For example, AI chatbots have often provided false answers or bad advice that do not align with actual business policies. From a risk perspective, insurtech companies must ensure they are not providing consumers with coverage advice while AI technology is still in its infancy.

Additionally, companies should remain aware of data considerations, such as customer consent and data ownership, when implementing AI measures. By carefully weighing the benefits and risks associated with AI adoption, insurtech firms can harness the full power of this groundbreaking technology while minimizing potential pitfalls.

Conclusion

AI has already transformed many aspects of the insurtech landscape, and its continued evolution promises even greater advancements. By leveraging AI for integration, content creation, claims processing and distribution, insurtech companies can maximize efficiency and deliver better services to their customers. However, balancing innovation with risk management is essential to ensure responsible and sustainable growth of AI in the insurtech sector. With careful planning and strategic implementation, AI has the potential to reshape insurance and create a more efficient, customer-centric industry.