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10 Insurtechs for Dramatic Cost Savings

Winning insurtechs tap into the key challenges that insurance carriers are facing. In this post, the second of seven different flavors of winners in fintech insurance: insurtechs that drive dramatic cost savings.

Although emerging markets are witnessing significant growth, most mature markets are saturated and experience margin pressure. This will show little or no change in the years to come.

Insurers are looking for ways to operate more efficiently in every major part of the costs column: in claims expenses, costs of operations and customer acquisition costs.

Technology purchases and investments by insurance carriers will further explode in these areas. And so will the number of fintech solution providers that want to cater to that need.

Learn from digital pure players

Technology definitely eroded the barriers to entry. Successful pure-play digital insurers know how to leverage technology to defy the conventions related to cost drivers that incumbents still work with. According to McKinsey research, incumbents for instance are not able to operate profitably with fewer than 1 million policies. They hardly seem to benefit from scale economies, and for incumbents the costs of using broker channels barely differ from using digital channels.

“The difference with pure-play digital insurers like InShared could not be bigger,” says Irene van den Brink, director of business development at InShared, the first fully digital insurer player on the Dutch market. In only five years, it achieved 10% market share in online car insurance, the highest NPS score in the market as well as the lowest cost ratio. “We run 500,000 policies with a core team of only 35 FTE [full-time employees]. But the scalability becomes even clearer when I tell you that 1 million policies could be managed by just a few more FTE and not the doubling of FTE you would see in a traditional model. With our digital model, we have proven to run a portfolio of P&C (non-life) at a 10% cost level, where we see that more traditional direct players have a cost level between 20% and 30% and broker models even higher than that. And this is just the beginning: Adding volume to our operations means we can go as low as 75 to 8% expense ratios, leveraging the full potential of a digital model.”

Apart from how digital new entrants leverage technology, we believe that two other factors are essential that explain the difference with incumbents.

First, having started from a clean slate, digital new entrants lack the complexity of a wide product portfolio, multichannel operations and having to comply with existing processes and IT infrastructure. Second, they understand this and stick to it. Successful digital new entrants are complexity-averse by nature. That is why they succeed in scale economies where incumbents don’t, and that is why they succeed in keeping their cost base that much lower. This is where many incumbents go wrong. Van den Brink says: “Virtually every insurance companies has embraced the need for a digital solution. But merely adding a digital channel or an app is not the way forward. In fact, this only adds costs and increases complexity in the IT landscape, it adds databases, systems and the links needed become an even bigger spaghetti.”

This is important to keep in mind when implementing fintech solutions to achieve substantial cost savings. The fintech solutions should address the root cause; they should dramatically reduce the complexity of current operations.

See also: Top 10 Insurtech Trends for 2018  

Go where the money is

Insurers spend between 60 and 80 cents of each euro of premium on claims. This means ample opportunities for fintechs that provide innovative solutions that reduce this amount. Think of solutions for improved claims management and fraud detection. Due to insurance fraud, 60 billion euro is lost each year in Europe and the U.S. alone. Of all fraudulent claims, 65% go undetected. Insurers spend no less than 240 million euro annually to tackle fraud.

10 insurtech solutions that dramatically reduce such costs

Everledger is using the technology behind bitcoin to tackle the diamond industry’s expensive fraud and theft problem. The company provides an immutable ledger for diamond ownership and related transaction history verification for insurance companies, and uses blockchain technology to continuously track objects. Everledger has partnered with different institutions across the diamond value chain, including insurers, law enforcement agencies and diamond certification houses across the world. Through Everledger’s API, each of them can access and supply data around the status of a stone, including police reports and insurance claims.

OutShared recently launched the CynoSure digital insurance platform, a complete head-to-tail digital insurer-in-the-box. CynoSure is a SaaS solution that covers the back-office system-of-record to all front-end web and app interfaces. For instance, with CynoClaim (one of CynoSure’s key modules) more than 60% of all claims can be managed automatically, resulting in lower costs as well as increased customer satisfaction. The platform can be used for both new market offerings and the renovation of established operations migrated to the platform. Results of the first implementations are promising: as much as a 50% decrease in costs and 40% increase in customer satisfaction. CynoSure takes six to nine months to implement, whether it is new or a migration – quite spectacular in the insurance industry, as well. (InShared is powered by OutShared)

EagleView Technologies provides aerial imagery, data analytics and geographic information solutions. Thanks to a fleet of 73 aircraft (and drones) that capture images on a year-round basis, EagleView’s library contains more than 250 million images spanning 12 years. This provides the most comprehensive current and historical view of properties available. Insurers use the library, data and visualization tools for instance to identify pre-existing conditions and estimate storm damage to roofs, leading to better decision-making in claims adjusting. In most cases, it is not necessary anymore to visit the site. In addition to these cost reductions, faster closing of claims leads to increased customer satisfaction

Enservio software uses demographic and other information to estimate the value of contents in a home. The software is, for instance, used to settle claims. Imagine a house being destroyed by a hurricane. The software allows the insurance company to reduce time-consuming negotiations, to eliminate discussions and to pay the claim three times faster.

Lexmark health insurance solutions provide carriers with the tools to expedite claims processing, simplify communications and reduce costs. The solutions extract data from claims forms with an accuracy rate of 90% or more, eliminating most manual data entry and boosting straight-through processing. Specific content management solutions integrate with legacy systems to provide health insurance document management for unstructured content in any form – paper, email, web forms, faxes, print streams and industry-standard formats – giving instant access to for instance claim adjusters.

AdviceRobo solutions use a machine-learning platform that combines data from structured and unstructured sources to score and predict risk behavior of consumers. AdviceRobo, for instance, provides insurers with preventive solutions applying big behavioral data and machine learning to generate the best predictions on default, bad debt, prepayments and customer churn. Predictions are actionable because they are on an individual level.

Shift Technology leverages data science to detect and model weak and strong signals of fraud, including fraud by organized gangs.
Shift Technology has developed algorithms to model data analysis of insurance policies and insurance claims, and external data while integrating the expertise of insurers. To be implemented and configured, the solution requires limited technical or financial investment. The solution is provided in a SaaS model and charged based on the volume of claims processed. The platform is used by general insurance companies as well as other actors in the insurance ecosystem, such as expert networks.

Not really insurtech, but too interesting not to include: PartsTrader is an online car parts marketplace that U.S. insurer State Farm is using to dramatically improve the repair process.

Repair delays caused by parts ordering issues result in millions of dollars in rental vehicle expenses daily across the industry, and high parts costs are reducing the number of vehicles that can be repaired. Using PartsTrader addresses both problems. The objective is to improve parts availability, quality, order accuracy, competitive pricing and process efficiency.

The LexisNexis Intelligence Exchange data platform allows insurers, among others, to review an incoming claim, for instance against claims made with other insurers, resulting in faster settlement of genuine claims and coordinated investigations of suspicious claims. The platform also detects potential insurance fraud; e.g. misrepresentation and non-disclosure of relevant facts, and lapsing of a policy in the second or third year due to, for instance, deliberate churning by an agent.

QuanTemplate is a cloud platform to analyze, report and communicate bespoke insurance information between parties. The software is built for the complex, collaborative world of the wholesale reinsurance markets. The users can manage their whole workflow within one app.

The platform reduces time and cost spent on reporting and analytics, while increasing speed and transparency.

See also: Global Trend Map No. 7: Internet of Things

The Internet of Things potentially has a huge impact on claims – by preventing an incident or by warning so that the damage doesn’t get worse. Connected devices provided by companies like Nest deploy sensors and Wi-Fi technologies to detect and report things like a leak under the sink before a pipe burst or to automatically shut off the stove when someone leaves home – so that house owners can handle burning toast before it becomes a burning toaster and insurers can avoid hefty claims later. Liberty Mutual and American Family Insurance already teamed up with Nest to decrease costs.

Similar preventive measures are promoted in ever-more-connected cars.

VitalHealth Software develops cloud-based eHealth solutions in particular for people with chronic diseases such as diabetes, cancer and Alzheimer’s. The company was founded 10 years ago by, among others, Mayo Clinic. The impact is huge because chronic diseases account for the majority of healthcare costs. VitalHealth Software features include care providers participating and collaborating in health networks, gaining web-based access to shared, protocol-driven disease management support based on established clinical guidelines, seamlessly integrated to and accessed from within existing electronic health records. Clients and partners of VitalHealth Software include top five health insurance carriers in Latam, Europe and China, eager to improve patient care and health costs management simultaneously.

All solutions that we featured in this blog have one thing in common: On the one hand, they contribute to significant cost savings, but on the other hand they improve customer engagement. Combining the two should be a leading design principle in digital transformation efforts.

Nest, OutShared, Everledger, AdviceRobo and VitalHealth Software are among the insurtechs that will showcase their innovative solutions at DIA Barcelona.

In our next post, we will focus on the third flavor of winners in fintech insurance: insurtechs that play new roles in the value chain. So stay tuned!

You can find the article originally published here.

In Search of a New ‘Dominant Design’

There is little in the world of insurtech happening today that insurers couldn’t arguably choose to do for themselves if they were motivated to do it. They have the capital to invest. They have resources and could hire to fill gaps in any new capabilities required. They understand the market and know how to move with the trends. And yet insurers readily engage with the startup community to do the things that arguably they could do for themselves.  Why is that?

In Making the Most of the Innovation Ecosystem, Mike Fitzgerald observes the main cultural differences between insurers and the startups they court. These differences give us a strong clue as to why insurers engage with startups, even though on paper they do not and should not need them.

Alongside these deep cultural differences, I believe that there is another angle worth exploring to help answer the question. That’s the market’s maturity stage and, with it, the strategies required to succeed.

One model that helps explain this relates to the work of Abernathy and Utterback on dynamic innovation and the concept of the “dominant design.” To accept the argument, you first need to believe that we’re on the cusp of a shift from an old world view of the industry based on a well-understood and stable design toward one where substantial parts of the insurance proposition and value network are up for grabs. You also need to believe that, for a period at least, these two (or more) worlds will co-exist.

See also: Insurtech Has Found Right Question to Ask  

So, here’s a quick overview of the model (in case you’re not familiar with it)…

Settling on a ‘dominant design’

First introduced way back in the mid-1970s and based on empirical research (famously using conformance toward the QWERTY keyboard as an example), Abernathy and Utterback observed that when a market (or specifically a technology within a market) is new, there first exists a period of fluidity where creativity and product innovation flourishes. During this period, huge variation in approaches and product designs can co-exist as different players in the market experiment with what works and what does not.

In this early, “fluid” stage, a market is typically small, and dominated by enthusiasts and early adopters. Over time, a dominant design begins to emerge as concepts become better understood and demand for a certain style of product proves to be more successful than others. Here, within an insurance context, you’d expect to see high levels of change and a preference for self-built IT systems to control and lower the cost of experimentation.

Once the dominant design has been established, competition increases and market activity switches from product innovation to process innovation – as each firm scrambles to find higher-quality and more efficient ways to scale to capture a greater market share. This is the “transitionary” stage.

Finally, in the “specific” stage, competitive rivalry intensifies, spurred on by new entrants emulating the dominant design; incremental innovation takes hold; and a successful growth (or survival) strategy switches to one that either follows a niche or low-cost commodity path. Within an insurance context, outsourcing and standardization on enterprise systems are likely to dominate discussions.

Applying the ‘dominant design’ concept to the world of insurance and insurtech

Building on the co-existence assumption made earlier, within the world of insurtech today there are broadly (and crudely) two types of firms: (1) those focused on a complete proposition rethink (such as TrovSlice and Lemonade); and (2) those focused on B2B enablement (such as Everledger, Quantemplate and RightIndem). The former reside in the “fluid” stage (where the new dominant design for the industry has not yet been set and still may fail) and the latter in the “transitionary” stage (where the dominant design is known, but there are just better ways to do it).

Figure: Innovation, Insurance and the ‘Dominant Design’

Picture4-1024x662

(Source: Celent – Adapted from Abernathy and Utterback (1975))

Outside of insurtech, within the “specific” stage, there is the traditional world of insurance (where nearly all of the world’s insurance premiums still sit, by the way), which is dominated by incumbent insurers, incumbent distribution firms, incumbent technology vendors and incumbent service providers.

So what? 

What I like about this model is that it starts to make better sense of what I believe we’re seeing in the world around us. It also helps us to better classify different initiatives and partnership opportunities, and encourages us to identify specific tactics for each stage – the key lesson being “not to apply a ‘one size fits all’ strategy.”

See also: 8 Exemplars of Insurtech Innovation  

Finally, and more importantly, it moves the debate from being one about engaging insurtech startups purely to catalyze cultural change (i.e., to address the things that the incumbent firms cannot easily do for themselves) toward one begging for more strategic and structural questions to be asked, such as: Will a new dominant design for the industry really emerge? What will be its timeframe to scale? A what specific actions are required to respond (i.e. to lead or to observe and then fast-follow)?

Going back to my original question: What does insurtech have to offer? Insurers can do nearly all of what is taking place within insurtech as it exists today by themselves…but, as stated at the start of this article, if, and only if, they are motivated to do so.

And there’s the rub. Many incumbents have been operating very successfully for so long in the “specific” stage, optimizing their solutions, that making the shift required to emulate a “fluid” stage is a major undertaking – why take the risk?

This is not the only issue that is holding them back. For me, the bigger question remains one of whether there is enough evidence to show the existence of an emerging new dominant design for the industry in the “fluid” stage that will scale to a size that threatens the status quo. Consequently, in the meantime, partnering and placing strategic investments with insurtech firms capable of working in a more fluid way may offer a smarter, more efficient bet.

In a way, what we’re seeing today happening between insurers and insurtech firms  is the equivalent of checking out the race horses in the paddock prior to a race.  Let the race begin!

fortune telling

Fortune Telling for Insurance Industry

In the world of InsurTech, there are distribution players and there are data players. The data players are essentially doing two things:

First, they are enabling and exploiting new sources of data, such as telematics, wearables and social listening.

Second, they are processing data in completely new ways by applying data science, machine learning, artificial intelligence and high-performance computing.

The result is that, for insurers, the InsurTechs are creating opportunities for the development of new products for new customers; improved underwriting and risk management; and radically enhanced customer engagement through the claims process.

Which is why, in my humble opinion, tech-driven innovation in insurance will be data-driven.

As a result, this week I feature an Israeli start-up called Atidot, a cloud-based predictive analytics platform for actuarial and risk management…aka, the next gen of data modeling and risk assessment!

I’ve recently Skyped with CEO Dror Katzav and his co-founder Barak Bercovitz. Both have a background in the Israeli military, where they were in the technological init of the intelligence corps. Both have a background in cyber security, data science and software development.

These are two very smart cookies!

And they have applied their minds to the world of insurance and, very specifically, to data. To change the way that data is cut and diced to provide multiple insights from very different perspectives has been their purpose.

Atidot
The result is Atidot, which in Hebrew means, “fortune telling.”

What’s the problem?

Dror explained it to me:

“Insurers (or rather, actuaries) are not doing all that they could with the data they have. And there are several reasons for this.

“First, they miss the point, Insurers look at data from a statistical perspective and miss out on the insights and perspectives that can be seen from different points of view.

“Next…, the traditional modeling tools that are still being used today are cumbersome, difficult to re-model and rely heavily on manual effort. With new sources of data now available, these tools are simply inadequate to handle them.

“And third, they’re too slow. The frequency of updating the models is too long, measured in weeks and months. This is because many of the current tools are limited in scale and flexibility, unable to cater for the huge volumes of data now available to them.”

How is work done today?

Today, insurers think about key questions to ask prospective policyholders. Do you smoke? Do you drink? Do you have diabetes? What is your gender? What is your location?

Insurers map the customer’s answers onto a statistical table. This linear modeling approach provides a risk rating of a certain outcome, such as the mortality rate for a life product.

But data science does not follow a linear model. It is different and varied. Data is modeled to show different correlations of risk to key variables.

This is what Atidot does.

It applies multiple approaches simultaneously to process a much larger set of data. This will include existing data that was previously ignored, such as the day of the month the salary is paid or frequency of ATM withdrawals, through to new sources of data, such as driving behavior or activity levels.

And while it is still very new for insurers to link, for example, increased levels of activity to mortality rates, there is enough evidence to suggest that it is just a matter of time before they do. You only have to look at the number of competitions on Kaggle to see that!

This shift gets to the crux of the insurer’s problem:

Quite simply, traditional models don’t have the ability to handle the new sources of data. Nor do they have the muscle to process it.

I’ve previously covered some brilliant InsurTechs in the data space, including Quantemplate and Analyze ReFitSense is a data aggregation platform that provides insurers with a new source of data to underwrite life risk differently. The platform collects data from all major fitness and activity tracking devices. The data is then normalized (to weed out differences in the way activity is tracked) and presents the underwriter with a common score to indicate activity patterns and levels (just as Wunelli enables a driver behavior score from telematics data).

However, the challenge for insurers is knowing what to do with this data and how to handle it.

Dror put this into context for me:

“Let me give you an example from a South African life company who were building two life products – accidental disability and severe infection disease. To test our platform, we ran their traditional method alongside ours.

“We found that they had a lot of data about their customers that they were not using or taking advantage of. And even if they tried to, the actuaries did not have the means to group this data and properly assess it in their models.

“Atidot were able to group the data differently using our tech and show them how they could significantly improve the accuracy of their forecast tables.

“We showed them how they could look at data in a different way.“

This all sounded great, so I pressed Dror for examples and we started to talk about a piece of data that seemed irrelevant to a life risk assessment – the day the premium is collected.

Dror showed me a sample of data from a live pilot the company ran for a U.S. life business on a 50,000-customer sample.

It showed that customers who paid their premiums on the 14th of the month had a 20% lower lifetime value than those who paid on the 1st.

Atidot graph
By enabling multiple data models to run simultaneously and picking the best model to better understand customers, Atidot drew a relationship between data that the actuary didn’t have before. Nor would the actuary have intuitively thought of it or arrived at it through a linear modeling approach.

So, is this enough to change the way insurers rate risk? Or change the risk selection criteria for an insurer?

To answer this I turned to Alberto Chierici, co-founder of Safer and an actuarial consultant with Deloitte. He told me:

“One issue to overcome for insurers is communication to the customer and regulators. For example, in some states it is compulsory to communicate to consumers why and how rating factors (gender, age, ZIP code) are used in pricing.

“That is making many insurers reluctant to adopt machine-learning-based risk rating and pricing. Think about the example you cited about people paying the 1st of the month versus people paying the 14th – how do you explain that to customers?”

Alberto pointed me to this discussion on Kaggle to illustrate the point.

One thing is clear, the InsurTech puck is heading Atidot’s way.

 

The original version of this article appeared here.

digital innovation

The 7 Colors of Digital Innovation

InsurTech is now established in a class of its own, no longer a sub category of Fintech. In 2015, $2.65 billion of venture capital was invested in InsurTech. We now have InsurTech-focused accelerators, with the excellent Startupbootcamp in London, the Global Insurance Accelerator in Des Moines, Iowa, (about to start its second cohort) and Mundi Lab announcing its start-ups for its insurance program in Madrid.

In the past year, I have interviewed more than 50 InsurTech start-ups, and I have seen the full spectrum of characteristics and common themes that run through these innovative digital insurance businesses, which i call:

From Distribution to Data, the Spectrum of InsurTech

Red – Distribution

Distribution is all about making insurance easier to buy, consume and understand. Innovators put the customer first and build their insurance proposition from the customer out (unlike incumbents, which organize their business around internal capabilities).

These start-ups are all about the customer, and their propositions are characterized by convenience, on-demand, personalization and transparency (and, of course, digital).

Examples include;

  • Bought by Many
  • Knip
  • Cuvva
  • Insquik
  • PolicyGenius
  • Moneymeets

Orange – Enterprise

Here we see a new breed of enterprise-class software providers. These are software as a service platforms running on the cloud. They have consumption-based pricing models that replace the traditional, million-dollar, up-front license fee and multi-year implementation.

In the main, these InsurTechs have taken hold of the small and mediums-sized business (SMB) space, but it is a matter of time before they prove themselves as genuine enterprise solutions for Tier 1 insurers.

Examples include:

  • Vlocity
  • Zenefits
  • Insly
  • Surely
  • Riskmatch

Yellow – Mutual 

New peer-to-peer business models return insurance to its roots of mutualization and community. The model relies on the notion that social grouping and affinity will change behavior and address moral hazard (thereby reducing claims payouts and premiums).

The question of scalability still hangs over P2P insurance, but, if it succeeds as a business model, it could form the foundation of a new breed of insurer. Just as kids call to their parents in their hour of need, customers will call to the insurer in theirs.

Examples include:

  • Friendsurance
  • Guevara
  • TongJuBao
  • Lemonade
  • Uvamo
  • Gaggel

Green – Consensus

Blockchain technology will fundamentally change the way the insurance industry works (as well as banking and society as a whole, IMHO).

The promise is huge although as yet unproven. From smart contracts to identity authentication, from fraud prevention to claims management, blockchain technology will provide the underlying technology foundations for a trustless consensus that is transparent to all parties.

Examples include:

  • Everledger
  • Tradle
  • SmartContract
  • Dynamis
  • Blockverify

Blue – Engagement

For me, this is the most significant of the characteristics from InsurTech in personal lines. The product becomes integrated in the customer’s lifestyle. It becomes sticky and overrides the annual buying exercise, where price is the key buying criterion. Digital natives are responding well to lifestyle apps that sit on top of the underlying insurance product.

Examples include:

  • Vitality
  • Trov
  • Oscar

Indigo – Experience

The true value of insurance is only realized when the customer makes a claim. New tech solutions that improve the customer journey through the claims process will not only improve the customer experience, they will also reduce the cost of claims and claims payouts.

Examples include:

  • 360Globalnet
  • RightIndem
  • Tractable
  • Vis.io
  • Roundcube

Violet – Data

This is all about new sources of data to rate and underwrite risk. This is about using data science, machine learning, artificial intelligence and high-performance computing to process data in completely new ways.

While distribution is vital to change the way customers interact with insurers, it is the data players that hold the key to fundamental change in the way insurance is manufactured, especially in personalisztion of insurance premiums and policies.

Examples include:

  • Quantemplate
  • Analyze Re
  • Meteo Protect
  • The Floow
  • Fitsense
  • Influmetrics
  • RiskGenius
tech

Where Are the InsurTech Start-Ups?

As a technology investor, I spend my days scouring Europe in search of the next big thing.

London’s FinTech scene has been a profitable hunting ground of late. With the U.K. FinTech industry generating $20 billion in revenue annually, it is not surprising that $5.4 billion has been invested in British FinTech companies since 2010.

A daily journey on the Tube is a testament to how rich the FinTech scene has become, with the capital’s underground trains now wallpapered with ads for Crowdcube, Transferwise, Nutmeg and other innovative companies. And London has played host to FinTech Week, celebrating the contribution these firms are making to the capital’s evolving financial services industry.

But where are the insurance tech entrepreneurs?

It is frequently—and accurately—argued that it is London’s birthright to play host to the poster-children of FinTech because of the capital’s impressive legacy and world-leading position in banking.

Read more: London FinTech investment in 2015 has already surpassed last year’s total.

The same can be said of insurance: The concept of modern insurance was solidified in Edward Lloyd’s coffee house in the 1680s. Yet there isn’t a day celebrating InsurTech— let alone a week of conferences, events and after-parties.

This is even though the insurance industry, with trillions of dollars of annual insurance premiums globally, is comparable in size to the rest of the financial services industry put together. Digital insurance should be an obvious target for technological disruption, especially as traditional insurers have struggled to adapt to the digital age en masse.

Recent research by Morgan Stanley found that consumer satisfaction with online experiences in the insurance industry is well below average, with only real estate and telcos finishing lower in the 16-industry league table. The big insurance brands have very little contact with their end consumer because of intermediaries such as offline broker networks, and, as a result, brand advocacy is often low. Put it this way: When was the last time you raved to your neighbor about your insurance provider?

Technology has the potential to drive worthwhile change in insurance. There are already a few success stories, but only a few. Insurance comparison engines such as Moneysupermarket, Compare the Market and Check24 have fundamentally altered how consumers discover their insurance providers. Black Box Insurance, based on telematics data, has become a mainstream product for young drivers, fueling the growth of companies such as InsureTheBox and Marmalade.

Read more:  These are the most influential people in FinTech

These are all fantastic firms, but there is not a long list beyond these examples.

So, why don’t we see more of this type of innovation? Insurance does have far higher barriers to entry than many other industries. To simply get an insurance company off the ground, it requires a colossal amount of cash to cover any potential claims. Additionally, regulation is tough, with good reason. The European Commission’s Solvency II Directive sets a high standard for the capital requirements for insurers to hit to be classed as an eligible provider.

This type of money is hard for a start-up to find. Having said this, very similar challenges are being overcome in retail banking, with challenger banks such as Metro and Atom obtaining banking licenses and putting regulatory capital in place. The successes that many have encountered in FinTech should buoy potential InsurTech entrepreneurs, as should the appetite of venture capitalists to invest in the insurance sector.

I don’t just speak for myself; insurance has excited many colleagues from other funds, especially as the industry is starting to give us some success stories. Slowly but surely, companies such as The Floow, BoughtByMany and QuanTemplate are demonstrating that technology can disrupt the insurance industry. London’s centuries-old legacy in insurance has created a talent pool that is, arguably, the best in the world. Combine this with the strong tech talent in the capital and you can see that the raw ingredients required to build extremely interesting companies are readily available. Additionally, certain large incumbent insurers are beginning to show interest in nurturing the capital’s potential InsurTech community. AXA is a particularly good example, having recently launched Kamet, a €100 million accelerator program aimed specifically at InsurTech entrepreneurs.

The combination of VC appetite, available talent and support from existing players demonstrates that London is a powder keg of untapped potential. The only missing ingredients, at the moment, are the world-beating entrepreneurs willing to put their ideas to the test.

FinTech has shown that London can lead the world in industries that are steeped in tradition and ripe for change. It’s time for InsurTech to step out of the wings.