The title of this article brings to mind two famous quotes from American culture. Mark Twain is reputed to have said, “The reports of my death are greatly exaggerated.” The saying could also apply to the frequent statements by insurtech detractors who have recently pronounced its death, following an incredible eight-year run, give or take a year. To appropriate another famous line, Dorothy, in "The Wizard of Oz," said, “Toto, I’ve a feeling we’re not in Kansas anymore.” The phrase has come to mean that we have stepped outside normality; we have entered a place or circumstance that is unfamiliar and uncomfortable—as we most certainly have over the past three years.

Conflicting Evidence

To be sure, there are several good reasons one might suspect the death of insurtech, including the recent collapse in share prices and unsustainable underwriting ratios of public insutechs such as Root, Lemonade and Hippo. Private insurtech valuations have slid along with those in the tech sector overall. Many insurtechs have laid off staff to conserve cash. Some have merged with others in response to adverse market conditions as inflation concerns and spiking interest rates have altered the investment and economic landscape. All combined, it is understandable that insurtech has at least been declared unhealthy.

In fact, 2022 was the first year to see an overall year-on-year drop in insurtech investment since 2016. Globally, annual funding halved between 2021 ($15.8 billion) and 2022 ($7.98 billion). Quarterly insurtech funding for Q4 2022 fell to the lowest level since Q1 of 2020, decreasing 57% quarter over quarter from $2.35 billion in Q3 to $1.01 billion in Q4, according to a recent Gallagher Re report.

However, there are a number of private insurtech businesses reaching real scale, including Zego, ManyPets, Next Insurance, Ethos Life, Alan, At-Bay and Coalition, to name just a few. Their loss ratios are good, their unit economics are sensible and they are growing. An impartial review of the marketplace reveals that there are numerous insurtechs that are succeeding, even if operating under very different business conditions than before. And just days ago, Equisoft, which provides digital solutions to the financial services industry, including life insurers, announced a sizeable $125 million in funding to fuel international expansion and R&D.

Funding vs. Results

It’s ironic that a common perception of insurtech success was most recently and mainly based on the amount of funding raised and accompanying valuations, characterized by our fascination with “unicorns” (private companies with valuations of  $1 billion or more) and even a few “decacorns” ($10 billion).

Revenue and EBITDA were rarely addressed, if they even existed. But customer acquisition costs for these insurtechs were too high, retention not high enough. Investment experts are quick to point out now that easy (cheap) money and inflated and unrealistic valuations were a big part of the “bubble” that burst starting in 2021. The erroneous theory at the time was that the more capital these startups could attract, the faster they could scale to profitability. In today’s world, revenue, growth, traction, margin and EBITDA are now the most meaningful measures of success in a return to business fundamentals, particularly for new-entrant insurers.

See also: Is Insurtech a Superpower?

“Insurtech” Confusion

Further confusing this discussion is the interchangeable use of the term “insurtech” to describe two very different categories of companies:

• start-ups and early-stage companies that incorporate technology and develop solutions for use within the insurance ecosystem, and
• “pure play” insurance companies that have developed partial or “full stack” businesses from scratch employing digital and other new technologies, selling and servicing insurance

Although the relatively small latter group has had less market success than the former, too many industry pundits have lumped them all under the same banner of insurtechs, of which there are thousands.

It’s important to describe what’s in the scope in the definition of insurtech.  Although many simply consider new insurance entrants, such as digital-first native companies, as “insurtechs,” the vast majority fall into the category of solution providers or enablers. In other words, companies that partner and therefore are dependent on existing carriers are the broader picture. They may be less flashy compared with a new digital insurer boasting that it will change the insurance world, but they are smarter, faster and nimble. In retrospect, the over-played disruptor moniker did a disservice to the vast insurtech movement.

The “full stack” insurtechs have failed to capture the level of meaningful market share their founders and investors envisioned because they have run headlong into the reality that selling insurance profitably is hard and that no amount of exciting technology alone can overcome that. Factor in the extreme inflation, and it is evident that most are ill-equipped to ride the storm.

Some of the other “insurtechs”—let’s call them technology solution providers—have succeeded or are on the road to success because they have developed valuable solutions and learned how to sell them to legacy insurers, which is an extremely nuanced act itself. 

Insurtech Success Stories

Many insurtech technology providers are thriving. Among the most successful categories: cyber risk/insurance, distribution, embedded insurance, connected devices including telematics, virtual claims inspection, automated damage estimating, digital customer communications, aerial and geospatial underwriting and claims solutions, e-payments for billing and claims and predictive analytics including fraud detection and claims workflow management.

And there is another wave of insurtechs that are nearing success with innovative solutions leveraging blockchain and virtual and augmented reality.

Partnerships, Platforms and Marketplaces

The market downturn has caused insurtechs to become even more creative in their search for traction and growth. Partnerships, platforms and insurance technology marketplaces are three beneficiaries of this strategic shift.

A few selected examples of insurtechs that have partnered with other insurtechs, information providers or insurers:

• Tractable has teamed up with Verisk to offer AI-powered estimates for property damage. Leveraging AI, the identification, classification, and measurement of property damage will be possible. And both Tractable and Verisk customers will now have access to end-to-end, automated property claims.
• Zendrive and Sfara have partnered with CCC Intelligent Solutions to deepen and broaden their telematics capabilities, including connected car data to drive better insights and claims experiences for auto insurers and drivers.

Several insurtechs are creating purpose-built platforms (vendor hubs) that enhance the value they deliver to their insurance clients by quickly adding relevant technology capabilities while avoiding the cost and time of developing these capabilities internally. One of the better examples of this strategy is Betterview, a property intelligence and risk management insurtech platform that P&C insurers use to identify and mitigate property risks of many kinds, including wildfire, hurricane, hail and catastrophe.

Over the past year or so dozens of insurtechs have joined one or more so-called marketplaces, basically core systems provider platforms used by insurance carriers to access a wide variety of point solutions and services:

• Guidewire, Duck Creek, Majesco and EIS have all seen tflock to their electronic platforms or “marketplaces,” through which insurance clients of their cloud-based core systems can access these point solutions on an as-needed basis without leaving their core system environment through relatively simple API connections
• Guidewire Marketplace alone now has 140 “partners,” and Duck Creek Content Exchange has almost as many; some providers reside on both platforms.

Follow the Money

Boston Consulting Group research shows that it took seven years, from 2012 to 2018, for $15 billion in equity funding to be invested in insurtech. In 2019 alone, $15 billion was plowed into insurtech, only to increase again in 2020 and 2021.

Even though the success of an insurtech is no longer measured in funds raised alone, VCs are still considered as savvy a breed of investors as may exist—especially so in today’s economic environment—so we still value their opinion when they vote with their checkbooks.

There were more than 20 funding events in the insurtech sector during each of January and February 2023, according to a review by Digital Insurance, including Ushur ($50M), Wefox ($455M), OpenEyes ($18M),  Floodbase ($12M), Flock($38M), EvolutionIQ ($33.1M), Goose ($4M), Joyn ($17M) and BOXX ($14.4M), as well as the earlier-referenced Equisoft ($125M). 

Consolidation and M&A

Consolidation is one effective business strategy for insurtechs that have developed valuable technology but are running out of cash and unable to attract more capital. While this typically results in dilution for founders and investors, it ensures that management and employees remain employed and able to see their vision realized while still participating in the overall success of the combined business. One of the better-known examples of this is the acquisition of Metromile by Lemonade.

See also: Outsourcing 2.0 to the Rescue

Looking Ahead

One of the most important and valuable contributions of the insurtech movement has been the stimulation of greater innovation and the acceleration of much-needed transformation in the insurance industry. Indeed, several large carriers have recognized and embraced this value by creating separate corporate venture capital investment funds to encourage the growth of these companies and the further development of these insurance technology solutions.

In addition to these significant investments in insurtechs, insurers have incorporated their underlying technologies into their own strategic planning around automation, digitization and modernization. Often labeled as slow to change and encumbered by legacy technology, insurers have come to recognize these realities and have embraced the opportunities to address them as embodied in insurtechs. Going it alone is no longer viable for any forward-thinking business.

We should not confuse the relatively slow adoption and implementation cycles often displayed by insurers with any lack of interest or enthusiasm for change. Insurance corporate culture will simply take time to correct as change management initiatives take hold. But make no mistake: Insurtechs and the insurance industry at large are co-dependent and will become increasingly so.

2023 will likely also present opportunities for legacy insurance carriers to acquire some of the technology-enabled solutions and talent they are interested in, and at a reasonable cost.

Dave Wechsler, a principal with OMERS Ventures and lead insurtech investor, recently shared with us his prediction that “those who can optimize their businesses and drive revenue around slower adoption rates will do fine.” In January 2023, OMERS led a $17.7M investment in Joyn, which integrates insurance, data and technology expertise to underwrite and bind E&S policies.

It is generally recognized by insurers and investors that insurtechs, and the broader tech-enabled startup community, is a highly valued contributor to innovation, employment and the economy overall. Friday’s federal government intervention in the Silicon Valley Bank to make the SVB depositors whole, including startups, VCs and investors, is strong and encouraging evidence of that recognition. Despite this unnerving development, numerous insurtechs have assured investors, employees and customers that the demise of SVB will have no direct impact. 

To be clear, some insurtechs will struggle, and there will even be some fatalities, but the majority of insurtechs are making the necessary adjustments and operating successfully while basically sheltering in place and preparing for the next exciting phase in the evolution of this critical “movement,” which is very much alive yet quite different.

Listen Now:

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ITL:

Hi, I'm Paul Carroll, the editor in chief at Insurance Thought Leadership. I am joined by Dr. Michel Leonard, who, among the many hats he wears, is the chief economist and data scientist at the Triple-I, the Insurance Information Institute. We're having our quarterly chat about all things economics, in particular where inflation goes from here, the economic growth rate and, of course, what it all means for insurance. Michel, I thought, as long as you have done a report that you kindly shared with me on your latest thinking, maybe I'd start just by asking you to lay out what you think the basic legitimate targets are for economic growth, inflation and then P&C economics this year.

Michel Leonard:

Hi there. Nice to talk with you, as we do regularly. In terms of thinking first of our overall expectations, growth overall for the economy, as most of us know, has decelerated significantly from 2021 to 2022. Let's remind ourselves that we were at almost 6% in ’21;  that was the post-COVID bump. Then, coming out of last year, the figure was 2.6%. So, a significant decrease. But let's remember that 2.6% for 2022 is still very good compared with the last years we've had. Going into this year, 2023, a consensus among economists is that we'll probably see an increase to a little bit above 3% growth; the Fed is a bit more optimistic, at around 3% to 4%. Our view is that there are some risks, especially on the geopolitical side, that could prevent us from getting as much growth as the most optimistic folks at the Fed and other central banks think.

ITL:

Okay, and then inflation.

Leonard:

When it comes to inflation, we kind of have a view that we have a base inflation that we should expect to be around 2% to 3%. However, again, here we have the geopolitical risk drivers. And to try to make sense of this, we're looking at two drivers.

Let's look at the base of 2% for inflation. That's what the Fed has been talking about for a long time. But then we have the dislocations of COVID. So, there was a supply issue that pushed prices up. And that really brought us about 2% more. So, we went from that “basis” of 2% to 4% or 5%. Then, on top of that, we had the war. That disruption was mostly for food, and some considerations of oil and energy. That added another 3%. So, you're basically in this range of 8%, where we were last year when we came to December. Looking to 2023, we're taking that roughly 2% base and looking at what happens to that dislocation due to COVID and the war, and we're really around 4%.

ITL:

One more question, and then we'll dive into some of the specifics. What do you see as the basic outlook for the P&C industry this year?

Leonard:

It's been such a tough environment. I hate to say that we have light at the end of the tunnel, because the challenges remain. But there are improvements. Things aren't getting as bad as rapidly, especially around growth and especially around replacement costs.

Now, on the growth side, traditionally we recover more slowly than the rest of the economy. But the economy has been recovering, and growth is accelerating, so we should see improvements in the P&C industry. In 2021, we were a fraction in terms of the growth of the rest of the economy. We were at 1%, while the overall economy was at 6%. Basically, this year, we can expect the growth rates will be about the same. So, the overall economy goes up 3%, and, all things being equal, P&C should be growing at a comfortable pace.

On the replacement cost side, that's where there's even more of a silver lining. A lot of those items that were significantly driving replacement costs, such as prices for autos and construction materials, those rose faster than the general rate of inflation -- double the rate – and now their growth is slowing much faster. Looking into this year, we're still going to have replacement costs rising a bit above overall inflation, but nothing like the twice as much that we had last year. At one point in the last couple of years, we had replacement costs for P&C at 16% inflation, with overall inflation at 6%.

ITL:

Thanks. So where should we dive in first? I know one thing you said in your report is that the growth will be lumpy, right? You're expecting problems more in the first half year of the year than in the second half of the year. Is that right?

Leonard:

We're still gathering data from Q3. Economists want to see if the actual numbers really improved after Q2. There is a lot of caution, but we could find that Q3 was indeed much better. Forecasts could ease if we see that growth wasn’t as challenged going into Q4 last year. And I'd say to our listeners and our readers, you really could see significant changes here, with whiplash.

ITL:

Makes sense. I want to talk a little bit about how the Fed is, obviously, the 800-pound gorilla here, throwing its weight around. I know you're not a fan of some of the things they're doing. That issue starts to bleed a little bit into the inflation discussion, but, anyway, I thought I'd ask you to comment on what the Fed is doing, and how it may or may not help.

Leonard:

I like it when you say this makes sense. It makes me feel good. [Chuckles]

What I'm trying to say is that, when it comes to the Fed, it's an issue of the underlying stance that the Fed took: that inflation was transitory, whether caused by the dislocation from COVID or from the war. But those events, of course, lasted quite a long time and, certainly on the war issue, are still there. The Fed’s position was very much in agreement with some politics that came into this, about the need to push inflation down. As soon as that happened, the Fed probably overreacted, and the medicine didn’t fit the disease.

The Fed’s monetary policy is increasing rates somewhat aggressively, and that coincides with a reduction in inflation, but that’s a coincidence. The Fed did kill demand. It did kill confidence. But it didn't address the underlying source of inflation. By not addressing the underlying source of inflation, by going directly after confidence and so forth, the Fed really overcorrected and brought us into this area where we're concerned about a recession. And the concern is quite real if one looks at corporate investments and corporate expenditures. They dropped significantly between Q1 and Q4 of last year, and that brings an economy to a halt.

ITL:

I'm probably parroting back to you something that you said to me once before, which is why it sounds smart in my head. I hope it's recognizable to you.

In general, the idea of raising interest rates is to make it more expensive to consume something. I'm less likely to buy a house with a higher mortgage rate. I'm less likely to buy a car if I'm financing it, if it has a higher rate associated with the loan. But a lot of what we're going through now relates to unreliable supplies of oil and gas. And raising interest rates isn’t going to produce more energy by making Russia stop screwing with international markets. With food inflation, you have another supply chain disruption that higher interest rates won't fix. Ukraine has long been the breadbasket of Europe and big parts of Asia and isn't able to supply that kind of food now.

Leonard:

That's exactly it. Traditionally, inflation is demand-driven. It's very rare in the last 50 years that prices have risen because we've had competition over the goods themselves. But cars aren't available, new cars in particular; there's a six-month delay for some models. I went on Amazon a couple of days ago because I needed a new microwave, and I was quite annoyed, frankly, to see that I couldn't get my microwave. What is that about?

Interest rates match well as a medication when we're trying to decrease demand-driven inflation, but that's not what we're seeing.

ITL:

Another issue that intrigues me about inflation is how long this will go on. We've talked about how it's steadily coming down, and that’s great. But, as you said, the Fed has traditionally had this 2% inflation target. Is that now done? Are we ever going to get back to it? If not, what's the longer-term outlook for inflation?

Leonard:

I think it's done. I’m not hedging, like traditional economists.

ITL:

That's right. You’re being a one-handed economist.

Leonard:

We were able to have increased demand for decades because supply of goods was being increased, also. Global labor was being supplied by rural China, other parts of Asia and so forth. But that environment is falling apart – the global supply chains, entry of new workforce, cheap labor, and so forth, that allowed for two or three computers a house because the computers were getting cheaper. There's not much cheap labor left around the world.

And that's a fantastic thing. Let's remember that it's great that people actually are paid for their labor. But that means that we are getting an environment where, regardless of the COVID dislocation in supply chains, we may actually see more often that things are missing on Amazon, so you have to wait a week or two. That's going to remove some of the controlling forces on labor and other costs.

Then think about global trade wars, such as with China, and the “reshoring” that is happening, which will affect capacity.

And we have a large, new generation coming in that will soon achieve a place where they can fully consume in terms of their income potential. That will further drive prices up.

So we probably end up with a new equilibrium that’s above 2% annual inflation.

ITL:

That makes total sense to me. And I think that's worth considering because inflation isn't just a 2023 problem. It's something that insurers have to crank into their long-term calculations.

Leonard:

We’re approaching what is almost the definition of stagflation. I started using the term very carefully a couple of years ago, and started using it in writing about a year ago. It’s where we're heading if the inflation is structural and at a higher level.

Without getting into a whole snowballing explanation here, what about immigration? Does immigration continue on the same scale? One of the ways we've been able to grow in the U.S. is because of immigration. But traditionally when there's tension over supply chains and reshoring, those produce political tensions, which also extend to immigration. The U.S. has had a period of historical immigration in terms of the number of Americans like me, who are foreign-born. But what happens now?

And does that point to a different growth story and a different inflation story. We could head back toward the attitude of the Great Depression generation, that things aren't going to get better. We haven't really learned to live with that attitude as a society.

ITL:

Those are profound topics. I've long thought that what you say about immigration is getting lost in the discussion. Because while people are talking about the border, and they're upset, and there are all kinds of political issues, we are robbing ourselves of a workforce that traditionally has helped the economy grow and has helped manage inflation.

Leonard:

If you have a reduction in growth and then we have structural inflationary pressures, that suddenly brings us into a position where, at a minimum, the improvement in quality of life and standards of living and so forth is decelerating. That's what we're really talking about. We're in an environment where the accumulation of wealth above and beyond inflation becomes more and more challenging.

ITL:

Yep. I wish we could be cheerier.

Well, I could go on all day, but to bring this around to a close in sort of the normal time we ask people to spend with us, maybe I'll ask you to come back to insurance and explain the scenario you lay out in your report that would lead to more homes and cars being bought and, thus, more insurance being bought.

Leonard:

You're seeing significant recoveries in those areas that have been worst-hit for the insurance industry. Costs for construction materials went through the roof. Prices for cars went through the roof. Replacement costs went through the roof. And those prices are coming down. As they're coming down, demand is coming back, as well, for cars and homes.

It’s happening first on the homeowner side, a little less on the commercial side, but we're in a position where our growth will pick up in homeowners and commercial property. It is picking up right now.

And then our costs will go down. We have several steps to get there, but we do see a light at the end of the tunnel there.

ITL:

As always, I appreciate your time and insights. I found the conversation kind of bracing, but in a way that I think certainly will help me think about things and that I hope will help our listeners and readers think about things. So, I'll just encourage people to check out you, Michel Leonard, and iii.org, the Insurance Information Institute. And, of course, I hope people sign up for the Six Things newsletter I do every Tuesday and check out the good work that people do for us with the articles we post at insurancethoughtleadership.com.

Michel, thanks.

That whoosh you felt coming out of Silicon Valley on Friday and then out of Washington, DC, on Monday was the wind shifting on regulation. And you can expect the wind to keep blowing in the direction of stricter regulation for quite some time, likely years.

The collapse of Silicon Valley Bank could also cause the Fed to slow its aggressive raising of interest rates, which would complicate life for insurers. Their investment portfolios have been benefiting from the higher rates, and they've seen the increases in costs, such as for replacement parts, moderate as the Fed attacked inflation. Any change in interest rate policy could slow or even reverse those recent gains. 

I should note up front that the regulatory backlash to the banking crisis may not affect insurers directly. Sean Kevelighan, CEO of the Insurance Information Institute, told me: "I doubt insurance will get wrapped into any of this. The insurance industry has worked hard since the crisis of '08/'09 to help better inform policy makers about the different model that is insurance, and why, because it’s built more on long-term capital trajectories, there is little to no likelihood of 'runs.' Nonetheless, we will be keeping a close eye on things to ensure there are no misperceptions."

I hope he's right, but I still wanted to call attention to the change in regulatory climate, because history suggests that, when one occurs, it's profound and long-lasting. 

The stock market crash in 1929 led to the Glass-Steagall Act and decades of strict regulation of banks. The Enron and WorldCom scandals in the early 2000s led to Sarbanes-Oxley and much tighter reporting requirements for businesses. The Great Recession of 2008 and 2009 led to stricter controls on financial institutions, including insurers, via Dodd-Frank. 

We seemed to be headed toward a tougher regulatory environment even before banks started failing. The derailment in East Palestine, Ohio, raised all sorts of calls for heightened regulation of trains, even from some members of the Republican party, which has for so long been pro-business and anti-regulation but which has headed in a more populist direction in recent years.

Newly elected Sen. J.D. Vance (R-Ohio) criticized “people who seem to think that any public safety enhancements for the rail industry is somehow a violation of the free market. Well, if you look at this industry and what's happened the last 30 years, that argument is a farce. This is an industry that enjoys special subsidies that almost no industry enjoys.”

Now, we not only have banks failing but have what looks like a total mess at SVB. During the Trump administration, it lobbied hard for and won exemption from the sort of regulatory scrutiny that Dodd-Frank established for the biggest banks and that looks like it could have prevented the bank's collapse. Democrats are already pouncing--for example, here is Sen. Elizabeth Warren (D-Mass.) writing an "I told you so" column in the New York Times. For good measure, SVB executives were paying themselves and their employees bonuses on Friday, just hours before the FDIC took over the bank.

While, as Sean says, insurers have a different business model than banks, the mess that is the homeowners insurance market in Florida has been getting national attention. And the Washington Post just led the paper with a major investigation into what it says is insurers cheating customers in the aftermath of Hurricane Ian. That's the sort of story that has prize potential written all over it, and we're still early in the year, so I'd expect the Post to lean into that story several more times as 2023 progresses. (Major prizes are awarded based on work during a calendar year.)

Because insurers are regulated primarily by states, even a major shift in attitude in Washington wouldn't necessarily affect our industry. But I still think it's worth being aware that, while the pendulum swung hard away from regulation during the Trump administration, it seems likely to swing just as hard in the other direction now. 

In any case, the bank failures may cause the Fed to at least slow its increases in interest rates, given that SVB collapsed because management somehow missed all the signals that interest rates were going to rise quickly. The worry is that continuing the rapid increases could expose other vulnerabilities in the U.S. financial system, as this Washington Post article explains in detail. 

It's not clear, at least to me, how much slowing the increases would diminish the attack on inflation. In a conversation I had recently with Michel Leonard, the chief economist at the Triple-I, he made an interesting point on the topic. He said that raising interest rates diminishes demand, which is why higher rates are the typical means for attacking inflation--but said today's inflation is driven by lack of supply, which high interest rates do nothing to address.

He cited supply chain disruptions, mostly because of COVID but also because the Russian invasion of Ukraine and broad geopolitical tensions are leading to "reshoring" and forcing supply chains to be reimagined. He also cited the disruption to oil and gas supplies and the lack of access to Ukraine's normally bountiful grain harvests for creating key shortages that raising interest rates won't ameliorate. (I'll share the transcript of our conversation here when it becomes available, likely in the next day or two.)

But the Fed certainly thinks that the fight against inflation would suffer if it has to slow interest rate increases. In any case, lower rates would decrease returns on insurers' massive investment portfolios. 

Just when it seemed inflation might be settling down, with job creation still robust, we seem to be back in that old Ray Charles song: "If it wasn't for bad luck, I wouldn't have no luck at all...."

Cheers,

Paul

 

Many new entrepreneurs or those in the gig economy consider on-demand insurance the greatest invention since sliced bread. And insurtech companies couldn’t be happier. Here’s why: In the wake of society relying more on smartphones, apps or other popular technologies, consumers now expect buying insurance to involve a similar user experience as when shopping on Amazon. 

Thus, on-demand insurance was born when technology and insurance merged. Consumers can shop and purchase policies online without the help of an insurance broker or agent. For example, with only a few clicks on their smartphone, a new founder can acquire a general liability or an errors and omissions policy lickety-split.

Many insurtechs provide on-demand insurance in some form, like Thimble with its short-term policies for freelancers. Others, like Pie Insurance, narrow the scope by focusing on pay-as-you-go workers’ compensation coverage, while Metromile provides pay-as-you-go auto insurance.

Commercial insurance brokers are also modernizing with on-demand insurance, using mobile apps to connect with clients. In fact, here at Founder Shield, clients can submit vital documents for renewals or claims, make payments or even invite collaborators to the policy. Although insurance is usually pegged as an antiquated industry, it’s transforming quickly — maybe too quickly.

How AI and Machine Learning Affect Insurance 

Before picking apart the industry for embracing change, it’s worth reviewing how the shift unfolds. And underwriting has played a significant role. It’s old news that artificial intelligence (AI) and machine learning have influenced the job of underwriting. That said, innovative technologies like AI and machine learning hope to shift the insurance industry from its current state of “detect and repair” to “predict and prevent” — a concept that merits a closer look.

Historically, traditional underwriting required real humans to evaluate business risks, methodically combing through them, threat by threat. Now, automated underwriting is a tech-enabled process using algorithms to make more accurate decisions. This approach streamlines risk management for thriving 21st-century businesses.  

Still, we would do well to remember the not-so-distant past. Here’s why:

Insurance could qualify as being “too on-demand.” We’ve witnessed some of insurtech’s efficiencies, namely automated underwriting, cause complications regarding coverage and scalability. While these streamlined solutions are ideal for more vanilla risk or smaller companies, the accessibility of securing on-demand coverage has bled into more complicated risk profiles that require a professional touch (i.e., fintech, crypto, etc.). 

See also: The Rise of AI: a Double-Edged Sword

Why On-Demand Presents Unique (and Overlooked) Risks

Very few would argue that on-demand insurance is a step in the wrong direction; it’s not. It’s been a game-changer for plenty of folks. However, we must consider that such innovative processes come with their own set of risks. 

Let’s look at the primary and two-fold risk: adequate coverage. For one, tech-dependent brokers don’t consistently provide proper guidance to clients regarding what to apply for. Next, these brokers leave clients guessing how to structure their coverage or classify the business. 

We’ve heard about consumers making important insurance decisions alone, with little to no guidance from their broker, often resulting in significant coverage gaps. As you may have guessed, this approach usually leads to claim denials or gray areas in coverage applicability. Of course it does! Clients can now change vital coverages, including limits and deductibles — all details that an insurance-savvy individual should tackle.   

Furthermore, automated underwriting can create additional scalability issues as more significant risks are underwritten in line with lower-risk businesses. Once a human underwriter sees what slipped through the system, they quickly non-renew or increase rates exponentially to match the actual risk.  

Viable On-Demand Insurance Solutions

The insurance industry understands that clients want differing levels of attention from their brokers, redefining the role of a commercial insurance broker to an extent. Some require one-on-one attention, while others would handle insurance tasks using an app instead. Still, most clients have come to expect quick responses from their insurance carriers. Plus, some underwriting data is quantitative, so most carriers rely partially on the automated version.  

We should expect continued advancement of automated underwriting among legacy players and insurtech companies. That said, most life insurance companies have relied on these digital processes. Commercial lines will also likely grow more heavily reliant on automated underwriting, supporting the notion of “predict and prevent.” 

At the end of the day, on-demand or automated insurance solutions have a place in this industry. Still, we must recognize limitations where clients, brokers and underwriters acknowledge the need for professional attention and expertise. Teaming the human experience with technology is doable — but only when the two forces accept the other’s strengths and weaknesses for what they are.

We are continuing to face a very uncertain environment — war in Europe, higher inflation, the lingering effects of the pandemic, increased likelihood of recession, questions on the right direction and speed of movement on climate/ESG, evolving market pricing cycles, and moderating rates. We suggest 10 ways CEOs should be positioning their organizations in 2023 to make the most of the Age of Acceleration.

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Sponsored by ITL Partner: Oliver Wyman

 

 

Read Majesco’s new research report that highlights the growth opportunity for insurers by providing the right products, value-added services, and experiences to help SMBs navigate market challenges and growing risk to help protect and grow their business. It underscores the significance for insurers to have strategic discussions on how they will plan, prioritize, budget and manage the changing needs and expectations in the SMB market.

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Considering the pivotal role played by insurers, all data must be given accurately and all processes compliant. So, insurers must be able to count on the effectiveness and stability of their operations--and robotic process automation can help. 

Robotic process automation in insurance refers to the use of software bots to replace rule-based tasks and procedures, including onerous or repetitive manual processes like data input, report production and document updating. 

Employees can then concentrate on activities that call for emotional intelligence, logic and creativity. For a distributed workforce and remote operations, RPA, together with artificial intelligence and natural language programming (NLP), are ideal:

• Data can be copied and pasted between programs. 
• Information can be removed from emails and other documents, then transferred to a central system. 
• Front-end and back-end operations can be synced up.
• Whole workflows can be automated by integrating with legacy systems and rules engines already in place. 
• Customer service can be enhanced by automated messaging.

Automation has already been widely accepted by the banking and financial industries. It is high time for insurers to adopt RPA. 

Challenges for Insurers

Now, let's look at the major hurdles that complicate the life of insurers:

1. Regulation and Compliance

Many laws and guidelines, including HIPAA privacy regulations, PCI standards and tax laws, must be followed by insurance businesses. The consequences of disobeying are severe fines and punishments. 

Moreover, it is difficult for insurers to comply with these laws and regulations because they are frequently updated or altered. As RPA software is rules-based, it can easily comply with regulations. And changes established in one location affect all operations, eliminating the requirement for manual system modifications. 

2. Scalability and Innovation

Customers' demands for exceptional experiences and individualized services have increased. Manual procedures, however, obstruct growth and innovation by causing delays and bottlenecks. 

By integrating data from several systems at the business process level, RPA bots can automate entire workflows. This makes it possible for smooth information exchange, improved coordination and increased workflow effectiveness. This gives the insurer more room to grow and explore the opportunity for product innovation. Innovative companies have already introduced fresh goods and services, including interactive consumer portals, on-demand quotations and policy management apps. 

Agility is essential for organizations undergoing digital transformation to adapt to a business and technological environment that is changing quickly. It is more important than ever to deliver on and surpass organizational expectations using a solid digital mindset supported by innovation.

3. Customer Experience

A poor client experience can damage a company's reputation. Sadly, clients today do not excuse agents for a "poor day" or a "sick leave." In the age of mobile insurance, consumers are constantly searching for the ideal solution with the highest level of loyalty, dependability and transparency.

Because RPA automates tedious processes, people can personalize and improve the customer experience, while producing a more contented workforce.  

See also: The 5 Top Trends in AI and RPA

4. Cumbersome Data Management

RPA improves the efficiency of data operations, not to mention making them quicker and error-free. A McKinsey study found that RPA for insurance may bring down the data processing time by 34%.

The processing of data is ultimately far more effective, and less bored employees can engage in complex activities and be more productive. 

5. Cutting Cost & Errors

According to research by Capgemini, RPA can enhance productivity in insurance companies by at least 50% and reduce turnaround times for services by 80%.  

The bots reliably identify risks, identify even the smallest mistakes in data reconciliation and insurance periods, verify claims, run background checks automatically and perform claim verification. Companies are exempt from fines because the bots update compliance policies on a regular basis. 

Insurance Industry Seals Operational Excellence with RPA 

A sizable number of large and mid-sized insurance companies still need to transform their existing systems to achieve superior customer experience and operational excellence, even though leading insurers have already implemented automation solutions across HR, finance, IT and other departments.

The climate crisis has swept across the globe, forcing companies to adapt. “There is nothing natural about the new scale of these disasters,” UN Secretary-General Antonio Guterres said. “Floods, droughts, heatwaves, extreme storms and wildfires are going from bad to worse, breaking records with an alarming frequency.” The UN’s United in Science says greenhouse gas concentrations are at record highs and fossil fuel emission rates are now above pre-pandemic levels after the lockdown trough. The climate crisis will continue to escalate, bringing with it damaging and unpredictable weather patterns.

Climatewise, a global network of 29 insurance industry organizations based at the University of Cambridge, warns that the disparity of uninsured or underinsured assets has quadrupled over the past 30 years, posing considerable risk to society. Data shows that if more people are insured at the time of a disaster, the recovery is quicker and less money is taken from the taxpayer. AI can be an ally in narrowing the protection gap and the answer for insurers wanting to stay ahead of the climate threat.

Storms, floods and fires caused $260 billion in losses in 2022. With uninsured losses come large bills that customers, businesses and governments must pick up. As insurers tighten their rates in the areas affected most by climate disasters, insurance premiums have risen to unaffordable levels for low- and average-income customers. Ironically, these are likely to be the same people most affected by climate change. Thus, the protection gap – the difference between total losses and insured losses – widens.

AI Is an Insurer’s New Best Friend

Artificial intelligence is already used daily within our personal and private lives, for example in voice assistants, image recognition, weather monitoring, shopping, online banking and healthcare. AI and deep machine learning also have the potential to make significant contributions within the insurance industry, making processes more accurate, secure and efficient.

Through AI, insurers can price competitive premiums and personalize policies to customers. Artificial intelligence can be used to collect large amounts of accurate, real-time data. With this high-quality data obtained from aerial imagery, properties can be accurately 3D-mapped at scale. Insurers can then use this information to predict the likelihood of a claim being filed as well as the likely cause of the claim. For example, when pricing a home insurance policy, information about the property’s location, roof condition, risk of flood and such like, can help insurers set premiums based on defining criteria. Insurers would be able to predict and prevent claims before they happen, ultimately saving time, money and resources.

AI can also make claims processing quicker and easier while maintaining efficiency and accuracy. Currently, application processing and check distribution takes weeks or even months, with teams needing to physically inspect damages. AI could automate the process to hours or even minutes, for example by using footage from street and garage cameras to reference vehicle damage after an accident, prompting customer loyalty. For those uninsured or under-insured, the reduced transaction costs of automated technology also mean that AI can make insurance more affordable and easy to use.

Extended reality can be used to automate underwriting by leveraging virtual and augmented VR. Insurers are able to virtually inspect homes both before issuing a quote and after a claim is filed. Rich and precise data allows companies to perform online adjustments to claims rather than physically inspecting damages, painting a more accurate picture of the value of the claim. This would reduce the number of employees needed for time-consuming processes around claims management and payout.

Insurers also have the opportunity to help communities prepare for climate disasters and better equip them with the tools and knowledge needed to evolve with the climate crisis. Using collected data, companies can advise communities against bad planning decisions, such as erecting high buildings near coastal flooding zones, or by encouraging building resilient infrastructure that will mitigate rising sea levels. Insurers can also contact property owners directly, advising them on their property’s current state and hazards. By reaching out to customers before a disaster, highlighting, for example, problematic trees and foliage growing on or around their property or a nearby wildfire risk zone, insurers have the ability to thwart disasters, saving time, money, resources and, in extreme cases, lives.

The cost of insurance fraud is more than $309 billion a year – nearly $1,000 for every American. Data collected and curated by AI can spot repeated behaviors and trends and can help insurers detect fraud and prevent risk. It can spot abnormalities in data as well as false information that customers use to get bigger claims payouts and lower premiums. Similarly, AI’s ability to can help insurers identify inconsistencies and can draw attention to fraudulent claims, preventing unnecessary payouts and drawn-out investigations. Artificial intelligence would also assist in the learning of customer habits, making valuable recommendations by simplifying how products are categorized and promoted.  

See also: Time to Embrace AI in Climate Change Fight

The Importance of High-Fidelity Data: Climate Change and Beyond

Reliable, top-quality data will give insurance companies the competitive edge they need to survive the climate crisis. The quality of AI models will only be as good as the data on which it operates. AI systems that use outdated historical data are ill-equipped to assist insurers with the ever-evolving threat of climate change. Rich data is therefore essential for AI to operate effectively and be accurate enough for insurers to use. Thus, one of the biggest trends we can expect to see is the dramatic increase in data veracity and a move toward making data more accurate to ultimately allow better business decisions.

The gathering and refining of in-depth, high-quality data can help insurers set risk, determine premiums, develop products, triage claims, prevent fraud, enhance customer loyalty and decide on what markets to target. AI can assist insurers in adopting a whole-system planning approach when responding and preparing for a climate emergency, fortifying the industry against this systematic threat.   

Insurers, governments and businesses must work in cooperation to protect both society and the economy from the adverse implications of climate change. Thus, organizations should be aiming for cross-sector collaboration, building a system of risk management fueled by intelligent data. The insurance industry is on the verge of a tech-driven shift that relies on the sharing, using and refining of data and AI resources.

Extreme weather caused 18 disasters in the U.S. last year costing $165 billion in damages, $10 billion more than the 2021 total, making 2022 the third-most-costly year since records of major losses began in 1980.

Insurers need deeper, more detailed insights into individual properties to underwrite accurately. Advanced technology can provide high-resolution satellite imagery of residences, allowing for desktop analysis of individual properties. By applying machine learning and AI technology to this aerial imagery, insurers can assess risk factors and, when necessary, quantify damage with increased efficiency and speed. High-resolution aerial imagery has the potential to bring data to life, helping insurers to competitively and sustainably underwrite properties.

Climate Change and Insurance

Using aerial imagery analytics within insurance has a range of benefits. It can be particularly useful when surveying properties that are hard to access, for example rural or coastal residences. Risk factors can instead be measured at a distance. High-quality images can contribute important property condition elements to quoting and renewal underwriting, ultimately saving businesses time, money and resources.

One major risk factor that influences the underwriting of a property is roof condition. Roofs are particularly vulnerable to constant wear and tear, as well as potential hazards, such as overhanging trees. These are also major impact areas during damaging weather catastrophes such as storms, tornadoes and hurricanes. Roof claims caused by severe weather are sometimes filed a year or more after the storm has passed. As a critical underwriting attribute, it is essential that the assessment process is accurately informed to ensure the client is completely covered for any damage. Current manual methods of assessing risk are outdated, relying on historical data that is often inaccurate and inefficient. However, with the assistance of modern aerial imagery technology, more robust data for each residential property can be ascertained. Damage from extreme weather has individual consequences for specific locations, thus, more granular data such as building elevation and soil conditions also need to be taken into account.

Aerial imagery can highlight potential hazards and capture how the roof condition is changing. An aerial perspective can also identify expensive attachments, like solar panels, as well as differentiate various materials, from shingle, tile, concrete or metal. The gradient, shape and surface area or the roof can also be pinpointed. This information can be combined with location-specific weather data, roof replacement cost estimates and claims insights on surrounding residences to help manage risk and ensure accurate underwriting. As a critical property underwriting attribute, aerial imagery can be used to collect specific and unique data points on the roofs of properties to ensure full and competitive insurance coverage.

Extreme weather events are categorized within the insurance industry as "low-probability, high-consequence," but the probability is only rising, meaning so, too, are the consequences. As threat levels dramatically increase, underwriters are under more pressure than ever to undertake new approaches and better modeling to underpin their decision making.

Another key factor insurers must consider when underwriting properties within a landscape dominated by climate catastrophe is wildfire risk and damage. Between 2021 and 2022, wildfires accounted for over $11.2 billion in damage across the U.S. Areas in the West, such as California, Nevada and Arizona, which suffer from long stretches of arid climate and little rain, are especially susceptible to wildfires. Wildfire damage is particularly hard to predict and measure as it is incredibly data-intensive and the risk profile can vary widely.

What is therefore required is up-to-date, location-specific data points that survey the topography of the landscape to identify areas of wildfire susceptibility. Action points can then be taken to reduce risk of damage, such as removing or trimming thick vegetation. Vegetation is identified on aerial visuals by its relatively consistent shape, color and texture. As a result of its low height, vegetation does not portray any shadow, and its variance in texture makes it detectable from the sky.

Aerial imagery can also reveal property elevation, as well as characteristics such as the defensible spaces between structures, vegetation and potential fuels in high-risk fire hazard areas. By using this data, insurers can not only assess which properties are prone to fire damage and are susceptible to wildfire risk, they can also understand which properties would need to be evacuated in the case of a climate disaster. This can be reflected in both their underwriting as well as in community disaster plans and future building regulations.

See also: Global Trend Map No. 4: Industry Health

Accurate Data Collection and Aerial Imagery

Moody’s Risk Management Solutions estimated there were $67 billion in insured losses from Hurricane Ian, which hit Florida at the end of September. Before the storm, the Florida insurance market was already in a precarious state following a recent spate of insurance company insolvencies over the past couple of years. Earlier in the year, six Florida property insurers had already declared themselves insolvent amid widespread financial problems within the industry.

Furthermore, Hurricane Ian was the most devastating hurricane since Hurricane Katrina in 2005. Officials have said this was down to a lack of preparation, not serving evacuation orders fast enough and a suboptimal approach to defending key infrastructure. This is why better data analytics and modeling is needed: so both insurers and their customers can better prepare for climate disaster through more accurate predictions about their properties.

In delivering damage reduction action points, insurers, reinsurers and brokers can sustain insurability and reduce losses for themselves, their customers, wider communities and the insurance industry as a whole.

Aerial imagery is one of the ways in which insurers can raise the standards of reliable, cost-efficient property data. It has the potential to enrich underwriting through identifying each properties unique risk factors.

By undertaking an integrated approach, combining high-quality images with expert interpretation, insurers can more confidently assess risk and underwrite profitably and sustainably. In the light of the climate disaster, insurers, now more than ever, need to adapt and update their methods of operation and delivery to keep the insurance industry afloat.

The number of ransomware attacks declined substantially in 2022, leading to a 40% decrease in the payments from victims. Whether a short-term trend or indicative of a permanent change in cybercrime activity, fewer attacks and better-prepared organizations have shifted the focus in cyber insurance. 

While ransomware claims may be in a lull, cyber insurers are finding themselves busy with a new wave of cyber claims stemming from class action lawsuits and enforcement actions due to data privacy violations. Once seen as a low-risk cyber coverage grant, cyber underwriters and claims teams are now scrambling to revise their policy language (and rates) to address the growing data privacy risks in their books.

Over the past six months, there has been a wave of data privacy lawsuits and enforcement actions on several fronts hitting cyber insurers’ policies:

Hospitals inadvertently share patient data with Facebook via the “Meta Pixel.” Examples include Dignity Health and UCSF in California and Advocate Aurora Health in Illinois. 

Retailers collect and share consumer data via online session replay tools. Examples include Zillow, Lowe’s and Expedia, sued in September. 

Financial services providers are sharing data with the Meta Pixel on tax preparation websites. 

Online news, sports and quick-serve restaurants share customers’ online video-watching behavior with social media networks. Examples include the recent Chick-Fil-A lawsuit (January 2023), as well as CNN and NBA lawsuits in 2022.

Why Are Cyber Underwriters On Alert?

Beyond the significant legal expenses related to the allegations and regulatory fines levied by state AGs, in some instances the privacy violations have escalated to reportable HIPAA breaches, which bring additional notification and remediation costs. For example, BayCare Clinic in Wisconsin recently informed the U.S. Department of Health and Human Services about a breach involving 134,000 of its patients who had been affected by online tracking technology. BayCare said the trackers potentially sent patient information to third parties, including the dates, times and locations of scheduled appointments; the type of appointment or procedure; patients' proximity to a practice location; and their insurance information.

Similarly, in 2022, the Advocate Aurora Health online privacy violation led to a reported breach of 3 million patients’ personal data. The health system of over 500 healthcare facilities in Illinois and Wisconsin reported itself to the Department of Health and Human Services on Oct. 14, saying the breach involved unauthorized access or disclosure. 

Beyond healthcare, insurers are also seeing claims activity among media networks, retailers and financial institutions, as allegations of violations of the Video Privacy Protection Act and state wiretapping laws are growing nationwide.

In light of these growing claims, some cyber underwriters are adding exclusions for coverage. Others, eager to build their customer relationships, are looking for opportunities to underwrite with greater intelligence about these privacy risks. 

See also: How Insurance Can Halt Ransomware

As With Ransomware Response in 2015, a Privacy Economy Is Growing Today

Insurers, attorneys, regulators, tech service providers, forensic firms, PR agencies and consultants rallied as the cybercrime wave grew over the past 10 years. Insurtech innovation was also fueled by the growing cyber threats.

Today, we see similar activity in the data privacy ecosystem. Federal regulators and state legislatures are implementing new laws, stimulating the plaintiffs bar to pursue class action lawsuits. This, in turn, drives insurers to create coverage for these new risks that their policyholders will face. Subsequently, tech innovators are creating tools to help provide intelligence to insurers during underwriting, while also creating better software for companies to not only comply with the new laws but mitigate the risk on their end. All the while, everyone in the "privacy economy" is seeking to learn more about the risks and how to protect themselves.

Building Greater Privacy Risk Intelligence 

With each new data privacy lawsuit and regulatory enforcement, cyber insurance underwriters are going to develop new language for their cyber policies to help protect their policyholders (and their loss ratios). Insurers, having learned from the ransomware and cybercrime waves of the past, are building intelligent underwriting tools that can help them assess privacy risk prior to issuing coverage and, likely, will be adding new tools to help their clients mitigate risks, as well.

Cyber threats and cyber insurance are in constant evolution. What started as "data protection" for a business’ network security issues, evolved to cover HIPAA regulatory risk, which then quickly evolved to cover broader customer data breaches, which then evolved to cover cybercrime and business interruption. Behind the rapid growth of cyber insurance has also been a wave of federal and state government regulations pushing companies to take responsibility for cybersecurity, as well as insurers to provide a backstop. Today, the new wave is focused on driving corporate responsibility for online privacy.

See also: Risk Barometer for 2023

The Online Privacy Revolution

In 2023, the regulatory environment is heating up again with new laws (GDPR, CCPA, FTC enforcement actions, OCR guidance and four other newly enacted state laws) around protecting customer data and online privacy. This is driving insurers to consider how to best provide cover for insureds while also mitigating risks. Perhaps this year will be seen as the start of an online privacy regulatory revolution. Not only is the regulatory environment ripe, but consumers are also more aware due to constant spam, scams, tax fraud, cyberbullying and identity theft. 

Already in five states (California, Colorado, Connecticut, Utah and Virginia), new data privacy legislation has been enacted. Huge fines have been levied against Google and Facebook in Europe for privacy violations. And you can’t watch a major sporting event on TV without at least a few ads promoting data privacy as a key reason to buy their phone, insurance, credit card or broadband subscription. 

The insurance industry has been instrumental in shaping how companies around the world adopt new technologies and practices to fight ransomware and cybercrime. It’s time now for the industry to take up the cause for online privacy and help companies evolve how they safeguard their customers’ personal data.