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Examining Potential of Peer-to-Peer Insurers

Recently, I wrote an article where I outlined a simple modeling framework I use when I try to predict how a new insurance product or new insurtech startup is likely to perform. In this article, I will walk through an example to give you a play-by-play on how to put this simple mental model to use.

Can Peer-to-Peer Insurance Succeed?

Peer-to-peer business models really came into their own in the financial arena, where companies such as Prosper and Lending Club were able to create platforms that allowed individuals to loan funds directly to one another. As a Prosper investor, I still recall how neat it was that I could loan a family $25 and be part of a pool of like-minded people who were looking to help others and make a little bit more money than a bank account. (Disclaimer: You can lose your money, too. I have had several borrowers default, and you will need to make up for it on those accounts that don’t default).

Investors, always a group looking for the next unicorn, have applied principles of P2P to others businesses, as well, such as car sharing and file sharing. Even digital currencies such as Bitcoin are P2P-based. Not surprisingly, investors and entrepreneurs are looking into whether P2P would work well in the seemingly tattered insurance industry. Companies such as Lemonade, Guevara and Friendsurance are already selling policies and making a name for themselves. InsNerds.com was very lucky to have Dylan Bourguignon of So-sure insurance, a complete P2P insurer, write an article for us on the topic (be sure to read this article if you want a breakdown from the point of view of an insurer).

See also: 3rd Wave of P2P Insurance  

Let’s walk P2P insurance through the model framework and see what all stakeholders need to see.


The exposure component is the one that deals with claims; past, present and future. The P2P model looks to reduce the frequency and severity of losses by reducing the desire among policyholders to make bogus claims. Because policyholders in a P2P model have some affiliation with each other, the hypothesis is that this connection will prevent policyholders from harming their peers. This seems intuitively possible. If it is true, what would that mean to the insurance coverage?

Fraud is estimated to add 10% to losses in property/casualty insurance. That would equal approximately $34 billion a year! Fraud is most typically investigated in workers’ compensation, auto and health insurance (not necessarily in this order). Traditional insurers spend a lot of money rooting out fraud. Big data vendors such as Verisk and Valen have commercial models available for both workers’ compensation and auto — even homeowners insurance isn’t immune. Reports of widespread false claims after Hurricane Katrina were documented.

The difference between what traditional carriers do and what P2P offers is that P2P subtly promises to remove the fraud BEFORE it happens, while today’s fraud is only caught during the fraud or afterward. If P2P can fulfill this promise, there is a tremendous amount of value it can provide to the market.

If I were an investor, I would look for companies that can show that their P2P network has very tight ties. As the network gets larger, it seems unlikely that the strong ties can be maintained, and you begin to lose the ability to have shame or other social pressures keep fraud under control. Any technology that can strengthen the ties to large portfolio scale could be immensely valuable.

I’ve written about Lemonade, and while the company no longer considers itself P2P, the initial “technology” was to group like-minded homeowners or renters together, and give any excess year end profits to a charity of their choice. If you are following along with where I am going with this, you may see some of the flaws in the model. First, homeowners insurance isn’t in the big three for fraud, so the potential benefits are not nearly as big as they would be in auto or workers’ compensation. Second, I didn’t really see any proprietary technology that could give Lemonade a leg up on any competitors. From all of the press releases, the P2P networks seemed easy to copy, as is Lemonade’s charity angle. That Lemonade dropped its P2P marketing seems to have confirmed that that part of the business model probably would not have produced worthwhile value. As an investor, I’d like to see a direct line to fraud reduction and truly big potential to drop the investments now being committed to detecting fraud, post-event.

P2P needs to bring some new type of configuration of insurance that meets needs not currently being met. The insurers mentioned above are tackling industries with heavyweight competition. I see an opportunity for P2P to unite common insureds in a way that provides coverage or risk reduction in areas where coverage is difficult to obtain or just doesn’t exist. In California, earthquake deductibles are very large. It seems reasonable that property owners could unite to buy coverage to protect each other against losses arising from the combined deductibles. There’s a similar case to be made for flood. I imagine these P2P insurers almost acting as public captives covering very niche risks for similar insureds.


The distribution component of the framework deals with how companies market to and sell to customers. In the P2P model, there is a heavy emphasis on the social element, like-minded insureds telling other like-minded insureds to join. Most P2P insurers are direct to consumer. Thus, P2P insurers must depend heavily on their insured network to do much of the heavy lifting for them, whether that’s through word of mouth or via social media.

If I were an investor looking into this area, I’d want to see some proof of concept that value can be created here to some scale. Brokers get paid well for a reason: it is expensive to find and maintain insurance customers. Advertising on Facebook is more expensive than you think, and, if you are using Adwords, you are competing against GEICO, State Farm and other large insurance companies. Good luck with that.

See also: Is P2P a Realistic Alternative?  

Ultimately, I think distribution will directly depend on the product development and what was discussed in EXPOSURE above. P2P insurers must be able to differentiate themselves. Take Lemonade. As a home and rental insurer, is Lemonade different than a traditional home insurer? Yes. Is it 10x better? I don’t think so. The product is nearly identical; only the customer experience is truly different. It is exceptional, but will that alone be enough to drive customers to buy policies? I think it will, but not by enough of a margin for Lemonade to deliver Uber-like returns. That’s not happening.


Insurance is a capital-intensive business. To start a plain-vanilla company in most states requires $5 million to $10 million in surplus capital. This is capital that is above and beyond capital that is used to pay for claims. That capital must be invested into the highest-quality securities (generally government bonds and AA corporates). Any startup that is more complicated than “vanilla” needs more capital. And any expansion into other states will require still more capital.All of this capital is needed even if you only have one on your books and even if you are ceding all of your business to reinsurers. Startup insurers are behind the eight ball right from the get go and are at a massive disadvantage when compared with the big guns.

State Farm has surplus in the tens of billions of dollars. Those are funds State Farm can invest and through which it can generate investment income that can be used to offset other costs in their. Startup insurers can’t do that and are very vulnerable to any large loss and thus require heavy partnerships. And that isn’t cheap! For startups, cost of capital is very high, and those costs must be reflected in the premium.

This is why Lemonade’s expansion across the U.S. is head-scratching. Though Lemonade is not a P2P, as a startup much of its newly acquired capital for this expansion is sitting in bonds. Unless there is some other news that we are not privy to, using B-round capital as a portfolio does not seem to be a great use of funds. This is a lesson for other P2Ps. An entire P2P strategy can collapse if the capital structure is not maximized. If I were an investor looking at this field, I’d want the P2P to be partnering with a capital source that already has scale, so that the P2P can focus on product differentiation and distribution.


P2P insurers have a terrific advantage in this area. Being born in the digital age means that these insurers can skip over legacy systems and go directly to an entirely modern platform. I would want to see seamless integration and movement of data between marketing, binding, policy issuance, accounting and claims management. I would want to see the ability to easily capture data at the front end, augment data during the lifecycle and put that data to work in integrated plug-and-play models.

See also: P2P Start-Ups From Around the World  

For P2P insurers, Lemonade is providing the blueprint for how this should be done. (By the way, big-time kudos to Lemonade for being so transparent and allowing curmudgeons like me to nitpick the business model). Lemonade’s integration of chatbots to eliminate human intervention in the purchasing of and the filing of claims seems to be an operations winner thus far. In this model, we should expect to see overhead expenses drop. Expenses associated with losses should also drop. If the P2P was not able to show significant decreases in expense, then something is terribly wrong.


I love the concept of P2P. But I don’t think it will ultimately become a great way to invest venture funds. I just don’t think the returns will justify the risks. P2P insurers should be able to provide significant value in operations. If they can differentiate product development, they should be able to attract customers who would be interested in their products. BUT…I think P2P insurers are not going to find very large markets for their niche products. Because of this, distribution costs will be higher than they expect, and they will suffer from capital costs unless they form the right partnerships. Those really inexpensive Lemonade rates likely won’t last. P2P prices may not end up cheap as capital and distribution costs overwhelm advantages obtained in potential decreases in fraud costs and operational efficiencies.

P2P insurance is full of potential, and as a model, will behave more like traditional MGAs. The potential for supersized returns is not high.

This article first appeared at InsNerds.com.

A Simple Model to Assess Insurtechs

“The paradox of teaching entrepreneurship is that such a formula necessarily cannot exist; because every innovation is new and unique, no authority can prescribe in concrete terms how to be innovative.”

― Peter Thiel, Zero to One

Whether we’re talking about telematics, artificial intelligence (AI), digital distribution or peer-to-peer, investing in insurance-related technology (commonly termed “insuretech” or “insurtech”) is no longer considered boring. In fact, insurtech is one of the hottest investable segments in the market. As a 20-plus-year veteran in insurance, I find it surreal that insurance has become this hip. Twenty years ago, I gulped as I sent an email to the CFO of my company, where I proposed that there was a unique opportunity in renters insurance. That particular email was ignored. Today, that idea is worth millions of dollars.

What changed?

Insurance seems to be the latest in a string of industries caught in the crosshairs on venture capital. With the success of Uber and AirBnB, VCs are now looking for the next stale industry to disrupt, and the insurance industry carries the reputation of being about as stale as they come. The VCs view the needless paperwork, cumbersome purchasing processes, dramatic claims settlement and overall old-school look and feel of the industry and think they can siphon those trillions of dollars of premium over to Silicon Valley. It seems like a reasonable thesis.

The problem is, it’s not going to happen that way. Insurance will NOT be disrupted. While insurance looks old and antiquated on the exterior, it is actually quite modern and vibrant on the interior. The insurance industry is actually the Uncle Drew of businesses; it’s just getting warmed up!

The Model

Much of the reason I think VCs are unaware of their doomed quest for insurance disruption is that they are looking at the market from a premium standpoint and envisioning being able to capture large chunks of it. $5 trillion is a lot of money. Without an appropriate model, an outsider coming into insurance can naively think they can capture even a fraction of this. But premium is strongly tied to losses. Those premium dollars are accounted for in future claims.

I once had a VC ask me what the fastest way to $100 million in revenue was. The answer is easy, “slash the premium.” I had to quickly follow up with, “and be prepared to be go insolvent, as there is no digging yourself out of that hole.” He didn’t quite get it, until I walked him through what happens to a dollar of premium as it enters the system. And it was this that became the basis of the model I use to assess new product formation and insurtech startups.

There are four basic components to my model. Regardless of new entrants, new products or new sources of capital, these four components remain everpresent in any insurance business model. Even if a disruptive force was able to penetrate the industry veil, that force would still need to reflect its value proposition within my four components.

Component 1 – EXPOSURE

This is the component that deals with insurance claims: past, present and future. Companies or products looking to capture value here must be able to reduce, prevent, quantify or economically transfer current or new risks or losses. Subcomponents in this category include expenses arising from fraud and the adjustment of claims, both of which can add substantially to overall losses.

See also: Insurance Coverage Porn  

Startups such as Nest are building products that increase home security by decreasing the likelihood of burglary (or increasing the likelihood of capturing the criminals on video) and thus reduce claims associated with burglary or theft. Part of assessing the value proposition of Nest is to first understand the magnitude of the claims associated with burglary and theft and then quantify what relief this product could provide (along with how that relief should be shared among stakeholders).

Another company that is doing some interesting things in this model component is Livegenic (disclaimer: I have become friends with the team). Livegenic allows insurers to adjust claims and capture video and imagery using the mobile phone of the insured. This reduces the expenses associated with having to send an adjuster out to each and every claim. Loss adjustment expenses can be in excess of 10% of all claims, so technology that reduces that by a few basis points can be quite valuable to an insurer’s bottom line and ultimately its prices and competitiveness.

Component 2 – DISTRIBUTION

This component focuses on the expenses associated with getting insurance product into the hands of a customer. Insurtech companies in this space are typically focused on driving down commissions. This can be done by eliminating brokers and going directly to customers. Savings can also be achieved by creating efficient marketplace portals that allow customers to easily buy coverage.

Embroker is one of many companies trying to do just that in the small commercial space by creating a fully digital business insurance experience. Companies such as Denim Labs are providing social and mobile marketing services to companies in insurance. And then there is Lemonade, which is developing AI technology that it hopes will reduce the friction of digitally purchasing (its) insurance and making the buying process “delightful.”  Peer-to-peer (P2P) insurance is a fairly new insurtech distribution model that attempts to use the strength of close ties via social methods for friends and close associates to come together to make their own insurance pools.

Distribution expenses in insurance are some of the highest in any industry. As with the risk component, reducing expenses in this component by even a few basis points is incredibly valuable.

Component 3 – CAPITAL

This component focuses on the expenses associated with providing capital or the reinsurance backstop to a risk or portfolio. For many insurers, reinsurance is the largest expense component in the P&L. Capital is such an important component to the business model that the ramifications of it almost always leak into the other components. This was one of my criticisms of  Lemonade recently. Lemonade will have a lot of difficulty executing some of the aspects of its business model simply because it cedes 100% of its business to reinsurers. So, when it comes to pricing or its general underwriting guidelines, its reinsurance expenses will overwhelm other initiatives. Lemonade can’t be the low-cost provider AND a peer-to-peer distributor because its reinsurance expenses will force it to choose one or the other. This is a nuance that many VCs will miss in their evaluation of insurtechs!

For those seeking disruption in insurance, we have historical precedent of what that might look like based on the last 20 years of alternative capital flooding into the insurance space. I will devote space to this in future articles, but, in brief, this alternative capital has made reinsurance so inexpensive that smaller reinsurers are facing an existential crisis.

Companies such as Nephila Capital and Fermat Capital are the Ubers of insurance. Their ability to connect investors closer to the insurance customer along with their ability to package and securitize tranches of risk have shrunk capital expenses tremendously. Profit margins for reinsurers are collapsing, and new business models are shrinking the insurance stack. It is even possible today to bypass BOTH veritable insurers and reinsurers and put the capital markets in closer contact with customers. (If you are a fan of Michael Lewis and insurance, you will enjoy this article, which ties nicely into this section of the article).

In the insurtech space, VCs are actually behind the game. Alternative capital has already disrupted the space, and many of the investments that VCs are making are in the other components I have highlighted. Because of the size of this component, VCs may have already missed most of the huge returns.

Component 4 – OPERATIONS

The final component is often the one overlooked. Operations includes all of the other expenses not associated with the actual risk, backing the risk or transferring the risk from customer to capital. This component includes regulatory compliance, overhead, IT operations, real estate, product development and staff, just to name a few.

It is often overlooked because it is the least connected to actually insuring a risk, but it is vitally important to the health and viability of an insurer. Mistakes here can have major ramifications. Errors in compliance can lead to regulatory problems; errors in IT infrastructure can lead to legacy issues that become very expensive to resolve. I don’t know a single mainstream insurer that does not have a legacy infrastructure that is impinging on its ability to execute its business plan. Companies such as Majesco are building cloud-based insurance platforms seeking to solve that problem.

See also: Why AI Will Transform Insurance  

It is this component of the business model that allows an insurer to be nimble, to get products to market faster, to outpace its competitors. It’s not a component that necessarily drives financial statements in the short term, but in the long run it can be the friction that grinds everything down to a halt or not.


I have presented a simple model that I use when I assess not just new insurtech companies but also new insurance products coming into the market. By breaking the insurance chain into these immutable components, I can estimate what impact the solution proposed will provide. In general, the bigger the impact and the more components a solution touches the more valuable it will be.

In future articles, I will use this model to assess the insurtech landscape. I will also use this model to assess how VCs are investing their capital and whether they are scrutinizing the opportunities as well as they should, or just falling prey to the fear of missing out.

Originally published at www.insnerds.com,

The Story Behind the Lemonade Hype

I am a sucker for new stuff. I bet many of you are, as well. If news of the iPhone 7’s release date caused you to immediately organize your camping gear for a week-long sidewalk holiday at your local Apple store, then you know what I am talking about. Beyond our excitement for the next iPhone or Tesla, apparently we also get all giddy for new insurance, as well.

Recently, an insurer named Lemonade has popped up on the scene and has caused quite a ripple. Here are some recent news headlines:

Wow! Give that publicist a raise. That is some quality publicity.

But it was when I saw this headline, “The Sheer Genius of Lemonade – A Whole New Paradigm for Personal Lines Insurance,” on InsNerds that I knew I had to speak out. Next thing I know, my good friend Tony Canas at InsNerds convinced me to write this response.

To start, this article is NOT a criticism of Lemonade or what it is trying to bring to the consumer. Insurance is in desperate need of heart and soul. No, what this article will do is splash some cold water on the hype inferno that appears to have taken over the sane minds of our industry. Allow me to go point-by-point with my issues:

Is Lemonade really peer-to-peer insurance?

Whether it is called peer-to-peer — or fashionably referred to as P2P — Lemonade ain’t it. Lemonade is a standard insurance company. You pay premiums, and the company pays claims from the general pool of funds. There are no peer groups insuring one another. There is no distribution model of peer invitations or referrals. The only “peer” element of the business model is that you will, as a customer, be grouped with others like you for the sole purpose of dispersing any underwriting profits to a charity of the group’s choosing. Now, there is a reason for this, but, seriously, was anything I just described even remotely connotative of peer-to-peer? Want to know what peer-to-peer looks like, see Friendsurance or Guevara.

Screen Shot 2016-11-17 at 9.31.55 PM

Is Lemonade really insurtech?

Sure, Lemonade is an online-only firm. And, yes, you can buy its insurance products through an app on your phone, where a bot named Maya will help you with your coverage selections, but Lemonade is still just an insurance company with a fancy website. I can buy insurance from other insurance companies where I can choose from dealing with a website, walking into an agent’s office or calling an agent over the phone. Lemonade has eliminated two options and given me a sole option that is little different from what I could have had before. And before you start screaming, “But I don’t want to call anyone or drive to any office,” just keep in mind that having options makes the experience better. Insurance is complicated enough that, occasionally, I would like to call someone or walk into an office and scream my head off. I deserve that option!

See also: Could an Incumbent Act Like Lemonade?  

What about the bot and the machine language? Isn’t that technology? It is technology in the sense that there are computer scientists engineering a robot to replace a human. But if the experience is crummier than just dealing with a human, it is a wasted effort.

In an attempt to play fair, I will reverse my position on this one — if it can be shown that the robot can handle the firestorm that comes when the company is hit with its first major natural catastrophe.

But isn’t it awesome that Lemonade’s underwriting profits go to charity?

One of the big marketing ideas coming from Lemonade is the unique feature of aligning the interests of policyholders and the insurer by taking excess profits and donating them to charity in the name of the peer group. Fraud is a big deal in insurance, and most insurers have systems in place to detect and counteract fraud. The charity angle from Lemonade is an attempt to prevent fraud from happening by linking the monetary loss because of fraud not to the big-bad insurer but to a softer, more sympathetic victim. Fundamentally, if you are a Lemonade policyholder and your claim is fraudulent is any way, you are depriving some charity of much-needed funds.

It is an interesting concept, but I don’t believe it will have much of a financial punch. The first drawback is that property insurance — being exposed to natural catastrophes (CAT) — is subjected to infrequent but occasionally massive losses. What appear to be underwriting profits in the quiet years between CATs are really opportunities to strengthen your balance sheet for the inevitable hit. As Lemonade expands to other states, its inability to build surplus because of the charity and the corporate status (see below), will really hamper the company’s business model. Lemonade is now, and will fully be, reliant on reinsurance to back its entire program. That by itself is not terrible, but, with full reliance on reinsurers, the excessive profits that the company thinks it will avail itself of, in reality, just go to the reinsurer. Think about this: If the reinsurer is taking all the risk, why would Berkshire Hathaway or Lloyds of London (two of the reinsuring entities for Lemonade) not want to profit from the transaction? These excess underwriting profits will simply transfer from insurer to reinsurer. My prediction is that the charitable donations will, in most years, be nonexistent or minuscule in comparison with premiums paid.

My second issue with the charity angle is that I don’t think it will bring the alignment of interest that Lemonade expects. One reason is that, if I am correct about the excess profits not materializing, then just the intermittent scheduling of charitable givings makes the whole exercise uninteresting to the insured, in my opinion. If Lemonade can’t provide a significant charitable donation in most years, the alignment will lose its appeal simply because the policyholders won’t be able to hang their hats on it. Perhaps worse, the charity angle may lose effectiveness because Lemonade is also marketing that it pays claims “super fast.”  Super fast claims handling (which, on Lemonade’s website, the company touts as a check in minutes), invites fraud. I think there is a major conflict of the business model. If your marketing message is that you can get a claims check in a few minutes without having an adjuster or claims rep work the claim, then your message is music to those upon whom the charitable message will have no impact. An an insurance buyer and seller, I know that out of super low prices, super fast claims handling and excess profits to charities, I can only choose one of those angles. More than one seems difficult. Getting all three strikes me as impossible.

Screen Shot 2016-11-17 at 9.32.08 PM

A broker by any other name…

Lemonade is a broker by another name. Another of Lemonade’s selling points is that insurers have a conflict of interest because they make money by denying claims. Lemonade purports to have absolved itself of this conflict by not actively acting like an insurer. Here’s how:

Lemonade is actually two companies. It is a risk-bearing insurance company AND a brokerage firm. When you buy a policy from Lemonade, the 20% fee goes immediately to the brokerage firm. The remaining 80% stays with the insurer. The paper on which the insurer is based is a B-corporation, which essentially makes it a non-profit. So it is the brokerage part of the business that is the money maker. That is the entity that secured all that seed-funding. Sequoia Capital knows a thing or two about making sound investments. It doesn’t do non-profits. And once the fee from the premiums the policyholder pays gets swept into the Lemonade’s brokerage company, it will not be used to pay claims, at all… ever. It is income, free of insurance risk. If the insuring entity ever goes insolvent, all the fees will be protected.

There is nothing wrong with this. The model has already been used successfully by other insurers. But, by acting as a broker, Lemonade has shifted its risk from the risk of loss or damage of the client toward that of a trusted adviser that only has one product to sell and gets a 20% commission for selling that one product. What if its product is NOT the best choice for the client? Will Maya the bot steer the buyer elsewhere like a traditional agent would? No. How forcefully will Maya point out all the flaws and gaps of Lemonade’s ISO style homeowners policy? Will Maya give direction to the insured about the flood or earthquake policy the client really should have but can’t buy through Lemonade? Somehow, I can’t match the hype and excitement of seeing a broker selling an average product, even if it’s sold via a robot.

See also: Why I’m Betting on Lemonade  

Lastly, I want to challenge the major premise of Lemonade — that insurers make money by denying claims. As a professional in the business for 20 years, I find that this is the one selling point that Lemonade and its marketing keeps touting that upsets me the most. It upsets me because it isn’t true. In fact, I have seen the opposite. I have seen emails or communications from senior executives to staff adjusters onsite during a natural disaster that flat out instructed adjusters to move quickly, be fair and, if there is any doubt about the damage, settle IN FAVOR of the policyholder. I am not naive enough to believe insurers never play fast or loose with their claims handling, but, by and large, insurers pay their claims. In the property area in which Lemonade competes, those policies it sells are legal contracts. Many a court battle has been fought to word the contract so that claims can be settled quickly and fairly. Lemonade is implying that it will be different; it is almost implying that it won’t deny claims. Are there really claims that insurers have denied (and acknowledged via the court system) that Lemonade would not have denied? I seriously doubt it.

Look, I like new things. You like new things. Lemonade is the new thing on the 300-year-old block. But the shiny new aspects that Lemonade is bringing to the table don’t appear to be worthy of the hype, in my opinion. I give them an “A” for effort in maximizing the hype to drive attention and sales. But insurance is all about the long game. The real key performance indicators (KPIs) are retention, combined ratios and customer satisfaction. Those will take years to sort out. Is Lemonade truly in it for the customer; does it really want to revolutionize the business model; or is the exit strategy already in place?

The world is watching. I hope it succeeds.

Why Exactly Does Big Data Matter?

Unless you’ve been living under a rock for the last few years you’ve heard a LOT about big data. But if you’re like most insurance professionals, you didn’t go to school for computer science, and even though it sounds very cool you really haven’t gotten your head around a simple question:


What the heck is big data? And how will it affect insurance?

For the last several years, the world has been creating more data than it ever had in the past. Some call it the digital exhaust: Everything we do leaves a digital trail, and with a smartphone in every pocket, a laptop in every backpack and near-universal access to giant clusters of computers in the cloud, the sheer amount of data we are able to collect on everyone and everything has grown exponentially. Data grew to such large quantities that it no longer fit in the memories computers use for processing it, so whole new tools had to be designed to handle it. We started creating and saving so much data that there was a qualitative change, and all of a sudden we became able to extract new insights and create new value due to the large scale of the amount of data that we can access. Things are now possible that simply could not have been done at a smaller scale.

One of the key changes that happened is that we started recording everything in a digital rather than analog way (computers instead of paper). As recently as the year 2000, only a quarter of all of the world’s information was digital. By 2007, more than 93% of the world’s information is now in digital format and can be much more easily read and analyzed by computerized tools! By 2013, more than 98% was digital.


Why Is Big Data a Big Deal for Insurance?

At its very core, insurance has always been an information business. We don’t make widgets. We help people and businesses manage their risks and help pay for the losses when they happen, and all of this is based on information, not on arranging physical atoms in any way. It’s literally a pure information business.

See also: What Comes After Big Data?  

For centuries, when faced with very large numbers of data points, society has depended on using samples. This applies even more to the insurance industry. Think back to CPCU 500; our ENTIRE business is based on the law of large numbers and on making statistically valid predictions about risk. (If you haven’t done your CPCU, stop reading this article right here and go get started on it! Here’s why, here’s how.) Sampling, and the law of large numbers, was necessary because we lived in a world of limited information, an analog world where most things didn’t get recorded in an easy-to-analyze way. We are now in a different world, in the digital era, and now, thanks to big data, we are approaching a world in which we won’t need to use samples anymore; we’ll have ALL the data. This will have huge implications for our industry.


Historically, we had to work with samples because it was very difficult or impossible to collect all of the data, and because we didn’t have tools that could work with gigantic sets of data. Having ALL the data related to something, instead of a sample of it, allows us to see much more detail. For example: In the old analog world, our actuaries figured out that 16- to 19-year-old drivers were more likely to have an auto accident, and this became a key part of how we price auto insurance. In the new digital world of big data, we might be able to analyze every second a young person has ever driven and make a personalized price for his very own level of risk! That rate will be much more accurate because it is based not on some of the general data (the accidents had by insured 16- to 19-year-olds) but rather by ALL the specific data (every second of driving this person has ever done).

By its very definition, actuarial science, which our entire business is built on, is “the discipline that applies mathematics and statistical methods to assess risk,” and one of the aims of statistics is to “confirm the richest findings using the smallest amount of data.” In other words, our entire business is built on making predictions using limited data. In a world of unlimited data, we will have to quickly become world class at analyzing and reacting to ALL the data, or we might be beat at our own game by those who do.

The Why Doesn’t Matter, Only the What

In the old world of small data, society spent a lot of resources trying to figure out the why behind things. Scientific and statistical studies started with a hypothesis, a prediction of how things worked, and then tested the available sample of data to see if that hypothesis was correct. If it wasn’t, then the hypothesis was modified and tried again. Most data was collected for a specific purpose, and it was very difficult to use it for other purposes without collecting a new sample. Today, with so much data around and more to come, hypotheses are no longer crucial. All that is needed is analysis for correlations.

Before big data, because of the more limited amount of computer power we had, most analysis was for linear relationships (this causes that); with the new tools of big data analysis and the faster computers available today, we can find more complicated non-linear relationships (a, b, c, d, e, f, g independently predict x a little bit but together they predict x very accurately).


It doesn’t matter that your system doesn’t know all the variables that go into a problem, only that it can predict the result. For example, Google has used big data to predict flu outbreaks faster than the Centers for Disease Control and Prevention (CDC) by letting the computer figure out which searches correlate with flu outbreaks. It doesn’t matter whether those people know that what they’re searching about is the flu, just that they’re searching on it and that when those hundreds of identified search terms happen in one area there’s a very good chance that area is experiencing a flu outbreak. In the new world of big data, the why something happens doesn’t matter, it only matters that we are now able to find the hidden patterns and find it or predict it. Society will need to shed some of its obsession for causality in exchange for simple correlations.

One example of how an insurance company is trying to use big data to improve its underwriting is Aviva, which studied the idea of using credit report and marketing data to underwrite some life insurance applicants instead of the traditional blood and urine lab analysis. The idea is to identify applicants with higher risk of lifestyle diseases like high blood pressure, diabetes and even depression. The method uses lifestyle data that includes hundreds of variables such as hobbies, the websites people visit and the amount of television they watch, as well as estimates of their income. The traditional lab tests cost $125 per person while this new approach can be as cheap as $5.  This is an example of a correlational relationship being valuable and more efficient than relying on a causal relationship for prediction of an outcome.

The More Data We Have, the Less Exact It Needs to Be

In the old world of small data, statisticians and data analysts were trained to clean out outliers and try to get data that was as clean as possible. With big data, we are looking at vastly more data, which means that we can get away with less precision. It’s a tradeoff; with less error from sampling, we can accept more measurement error. The old tools (spreadsheets, relational databases, SQL, business intelligence tools, etc) were created to work on exact data; the new tools are designed to work with large quantities of imperfect data. The need for perfect data was a side effect of the limited tools we used to manage small data.

See also: Eating the Big Data Elephant  

Here’s a great example of why we can now get away with less exact data: Suppose we need to measure the temperature in a vineyard. If we only have one temperature sensor for the whole plot of land, we must make sure it’s accurate and working at all times: no messiness allowed. In contrast, if we have sensors for every one of hundreds of vines, we can use cheaper, less sophisticated sensors (as long as they don’t introduce a systematic bias). Any particular reading may be incorrect, but the aggregate of many readings will provide a more comprehensive picture.

Data Is No Longer Stale After Its Original Use

One of the very limiting features of the old world of data is that once a dataset was built for a particular use, it was very difficult to use it for another, so you have to know what you’re looking for before collecting the data.  Because you were collecting a sample of data and inputting it into a very structured format for future analysis, getting the right pieces of information was of paramount importance.

In the new world of big data, all data becomes a new raw material to create value in new and creative ways, most of which were impossible in the old world. Because we are collecting data on everything, and our tools are more sophisticated in ability to arrange and rearrange that data, we are more able to use the information in a variety of ways.

Think about it; that telematics device on your car collects a TON of data. Think about the data your smartphone collects about your habits each day. Every time you search on Google, it’s recording not only what you search for but even the exact amount your mouse spent at different parts of the screen. Soon, we’ll even be able to track your eyes through the webcam when you visit our website. There’s just a TON of data out there that we’ll now be able to analyze and learn about our customers.

Being Free of Sampling Will Allow Us to Know More

Sampling quickly stops being useful when you want to drill deeper, to take a close look at some intriguing subcategory of the data. One of the key benefits of being able to collect ALL of the data about something is that we can dig further into the data and ask it fresh questions that we hadn’t even thought of when we started collecting the data. In the old paradigm of sampling, one would collect only what was directly asked for. If you noticed a pattern in that sample but needed something to explain or verify the pattern that you had not thought to ask for ahead of time, you would need to re-sample and get additional data to confirm what you found.

Data No Longer Needs to Be Structured

Traditionally, the way data was stored in spreadsheets and databases was structured, meaning that each field could fit a very specific type of data; a phone number field, for example, could only hold a 10-digit number. The problem is that only around 5% of all digital data in the world is structured in a form that neatly fits into a spreadsheet or database. That means we had no easy way to analyze the other 95%! Pretty much all data had to be cleaned up before analysis, which made everything smaller and more expensive.

In the new world of big data, new tools such as Hadoop are able to analyze unstructured data in all shapes and sizes, 100% of data instead of just 5%. The tools can even analyze things like books, journals, metadata (data about data), audio, video and much more. Imagine being able to include every second of conversation digitally recorded from your call centers along with all your other data and analyze it all to find trends! This is one of the most powerful features of big data, and it is already being used in many call centers.


Messier Data Will Help Us Insure Messier Things

Big data’s ability to help us analyze messy data could help us insure harder-to-insure things. For example, ZestFinance, a company founded by a former chief information officer at Google, built technology that helps lenders underwrite small, short-term loans to people who have bad credit scores. Turns out traditional credit scoring is based on a few factors, while ZestFinance uses a huge amount of variables using big data, and it produces solid results; in 2012, the company’s loan default rate was a third lower than the industry’s.

Big data might allow us to better underwrite risks for which we don’t have very good data, such as people who can’t get a driver’s license or commercial risks that currently can only be insured in the surplus lines market. Imagine all of the services, microinsurance and other innovations we’ll be able to develop.

From Indemnification to Risk Prevention

One of the techniques used with big data is predictive analytics, and pretty much every carrier is experimenting with it.

The technique is being used to prevent big mechanical or structural failures: placing sensors on machinery, motors or infrastructure like bridges makes it possible to monitor the data patterns they give off, such as heat, vibration, stress and sound, and to detect changes that may indicate problems ahead.

The underlying concept is that when things break down, they generally don’t do so all at once, but gradually over time. If we have sensor data and correlational analysis, we can probably figure out that something is about to break before it actually does. This can allow us to prevent claims from ever happening, thus moving from insurance as a loss-paying service to being a risk-prevention partner.

See also: Forget Big Data — Focus on Small Data  

Acknowledgement: Much of this article comes from Big Data: A Revolution That Will Transform How We Live, Work, and Think. Yes, you should read it! Yes, we get a small commission if you buy it using that link, and it helps us run and improve InsNerds.

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This article originally published on InsNerds.com.

Lemonade: A Whole New Paradigm

We’ll admit it; we were caught asleep at the wheel on this one. We had heard of Lemonade a few months ago and how it successfully raised $13 million in investor funding, but given that there are 500-plus other insurtech startups out there, we didn’t pay that close attention. Then on Sept. 21, it opened for business. Both Carly and Tony were in Hawaii for the CPCU Society Annual Meeting and entirely too busy drinking Mai Tais, err, I mean, working the event to even notice that Lemonade went live. We’re back in the lower 48 now, back at our day jobs and, after almost a month working on catching up, it just recently hit us that Lemonade is a BIG deal. A REALLY BIG DEAL.

A lot of digital ink has already been spilled at ITL with at least three great articles about Lemonade, but we still needed to give our own point of view. As Insurance Nerds, we are completely geeked out, and, as millennials, we can’t help but want to move our own insurance to Lemonade and are actively wondering when the company will expand to Pennsylvania and Georgia, where we live.

Lemonade is not just another insurtech startup. It is an actual, mobile-first, legacy-system-free, licensed carrier offering P2P (peer-to-peer) insurance to delighted customers in the state of New York through a seemingly magical iPhone and Android app. To start understanding what this is all about, you must watch the three short videos in this article:

That first video looks like a VERY snazzy proof of concept, and it almost makes you wonder if this thing will ever go live or if it will simply be vaporware. But it’s already live! Maya, the young lady who asks you in plain English a few simple questions to “get you some great insurance” is not a call center rep in NYC, Des Moines or even in Delhi; she’s an artificial intelligence chat bot. This technology is so new that it was unknown before 2016 and is only starting to be experimented with in the high-tech industry, and it’s live on Lemonade, helping people buy homeowner’s and renter’s insurance.

Notice how, as the user fills in his address, the system automatically pulls potential matching addresses, and once it has a full match it automatically displays a map to confirm. Then it asks whether you have roommates, a fire alarm or a burglar alarm, if you answer yes to any of those, the system knows what else it needs to ask.

See also: Lemonade: Insurance Is Changed Forever  

It immediately pulls data from databases, analyzes all the underwriting characteristics it needs and offers an incredibly cheap policy. Oh, and if you already have a policy, Lemonade will even cancel it for you and get you a refund! Coverages are shown in a simple, graphical illustration, and just tapping on a darkened icon adds that coverage to your quote immediately. Enter your credit card info, and done. The whole video takes about 40 seconds to get to a bound policy. In real life, it probably takes about 90 seconds. You even get to sign your contract right on your touchscreen. It’s downright magical.

The ease of use and freedom from legacy systems by themselves are probably enough to get 70% of millennials (and many Xers and Boomers) to leave their existing insurers and go with Lemonade instead! As Michael Tempany explains, no existing insurer can produce an app like this because of our legacy systems, workforce and processes. It’s simply not possible. He even argues that “the only solution for traditional insurers wanting to compete with Lemonade is to start from scratch. In short, they need to create a company or subsidiary unencumbered by legacy systems, workforce constraints and intermediaries.”

But that’s just the beginning. Rick Huckstep of the Digital Insurer is absolutely right that “This is what insurance is meant to be: mutuality in the pooling of shared risk.” He argues that “the industry has lost its way with the evolution of mass scale personal lines in the 20th century. The profit motive has gotten in the way of trust; the insured and the insurer are both chasing the same dollars. And now, their interests are no longer mutual but are misaligned. The insured wants a helping hand and to be ‘made whole.’ The insurer wants to satisfy its duty to shareholders.” This is true even with mutual companies with no shareholders; the existing model of every other insurance carrier puts the customer’s interests against the carriers interests at least to some extent. While Lemonade is a full-on risk-bearing carrier, it has eliminated the existing dilemma of every other carrier: Lemonade takes a 20% cut of the premium as a fee, and that’s it. If you have a loss, you get paid for it (immediately and without questions), and, if you don’t have losses, and your policy produces a profit, it gets donated to the charity of your choice.

The claims process is also amazing. You open the app, tell it you had a claim, answer a couple of questions, sign on the screen, record a quick video explaining what happened and get paid, on the spot, immediately.

Oh, and by the way, Lemonade is A-rated and reinsured by Lloyds of London.

The second video explains the science that makes it all work and has a great line: “Insurance that is a social good, not a necessary evil.” This tag line is going to be killer awesome. Also, very interesting that Lemonade explicitly explains what Geico’s “15 minutes can save you 15% or more” line has always meant: There are no brokers or agents involved.

Nobody explains Lemonade better than Dan Ariely, behavioral economics expert, Duke professor and Lemonade’s chief behavioral officer. “In the very structure of the old insurance industry, every dollar your insurer pays you is a dollar less for their profits. So when something bad happens to you, their interests are directly conflicted with yours. You’re fighting over the same coin. Basically if you tried to create a system to bring out the worst in people, you would end up with one that looks a lot like the current insurance industry.”

See also: It’s Time for Some Lemonade  

And a fantastic commercial making it all crystal clear to the customer:

Make no mistake, Lemonade will expand beyond New York, and we’d expect it to be in all 50 states within the next five to seven years at the very latest, and it will expand beyond renters and homeowners.

A lot of questions remain open: Will Lemonade have decent underwriting results? Will the underwriting results even matter given the fee-based structure? Will the company be able to come up with an equally genius model for auto insurance? How about commercial insurance?

A couple of things are absolutely certain: Millennials have no issue leaving legacy insurance companies and will be thrilled to try this out; and our industry has changed forever. Lemonade is what we will get compared with from now on. How will your company compete?

Want to support InsNerds?

InsNerds is free, it’s a labor of love and it takes a lot of time. We have a ton of fun doing it, and we would really appreciate your support in keeping it running. If you’ve been helped by one of our articles, if we’ve helped you grow in your career, if you agree that our content is improving the insurance industry and that we are unique in what we do, please consider donating. We’ll use your donation to deliver even more career- and industry-changing content, and to spread the word about that content far and wide in the Insurance Industry.