A recent survey of insurance underwriters found that 40 percent of their time is spent on “tasks that are not core” to underwriting. The top three reasons they cited are:
Redundant inputs/manual processes;
Outdated/inflexible systems; and
Lack of information/analytics at the point of need.
The survey – conducted by The Institutes and Accenture – also found that underwriting quality processes and tools are at their lowest point since the survey was first conducted in 2008. Only 46 percent of the 434 underwriters who responded said they believe their frontline underwriting practices are “superior” – which is down 17 percent from 2013.
“While underwriters believe technology changes have improved underwriting performance, 64 percent said their workload has increased or had no change with technology investments,” Christopher McDaniel, president at The Institutes Catastrophe Resiliency Council, told attendees at Triple-I’s Joint Industry Forum.
The survey’s findings with respect to talent may shed some light on this. The number of organizations viewed as having “superior” talent management capabilities for underwriting fell 50 percent since 2013 across almost every measure of performance evaluated.
“Training, recruiting, and retention planning had some of the biggest drops, particularly for personal lines,” McDaniel said. About a quarter of personal lines underwriters said they view their company’s talent management programs as deficient. That rate rose to 41 percent for talent retention; 37 percent for in succession planning; 33 percent for in training; and 30 percent for recruiting
“While technology investment may have improved underwriting performance” in terms of risk evaluation, quoting, and selling, McDaniel said those improvements “appear to have come at the expense of training and retaining underwriting talent,” McDaniel said.
A McKinsey study that assessed the potential impact of automation on functions like underwriting, actuarial, claims, finance, and operations at U.S and European companies found that as underwriting becomes more technical in nature it also will require more social skills and flexibility. Respondents to the McKinsey survey said automation and analytics-driven processes will produce a greater need for “soft skills” to shape and interpret quantitative outputs. Adaptability will also become more important for underwriters to stay responsive to changing risks and learn new techniques as technology changes.
“Underwriters will not become programmers themselves,” the McKinsey report said, “but they will work extensively with colleagues in newer digital and data-focused roles to develop and manage underwriting solutions.”
Non-fungible tokens (NFTs) are a hot topic, gaining attention from pop culture to the business press. Most of this notoriety has been associated with the buying and selling of digital collectibles, but the underlying blockchain technology and this specific application of it have implications for tangible assets and for insuring both digital and physical properties.
For this reason, the Institutes RiskStream Collaborative – the risk-management and insurance industry’s first enterprise-level blockchain consortium – recently launched a free educational series about NFTs.
What are NFTs?
“Non-fungible” means an object is unique and can’t be replaced with something else. A dollar is fungible – you can trade it for another dollar bill or four quarters or specific numbers of other coins, and you still have exactly one dollar. An individual bitcoin is fungible. A one-of-a-kind trading card isn’t fungible – if you trade it for a different card, you would have a different thing, and you would lose possession of your original card.
NFTs are unique digital markers that can be associated with an asset to identify it as one-of-a-kind.
In the second episode, the RiskStream Collaborative brings in Jakub Krcmar, CEO of Veracity Protocol, to discuss the concepts of computer vision, digital twins, and NFTs of physical products. The ability to create a unique digital twin of exact replicas – like identical baseball cards or identical automobile gears – to create an NFT may have major insurance implications. One example was the potential for NFTs to be associated with high-value physical objects to demonstrate authenticity of ownership and reduce or eliminate fraud opportunities.
Episode three features Natalia Karayaneva, CEO of Propy, who explains the potential for NFTs in real estate transactions. She highlights some of the benefits of the NFT approach, underscoring the efficiencies brought to primarily paper-intensive processes. The potential for insurance also is discussed.
In episode four, Kaleido CEO Steve Cerveny wraps up the series by describing the tokens themselves. He highlights the ability to create NFTs to represent any asset. These tokens are programmable “things” on a blockchain, which can help with business processes. Blockchains are basically ledgers or databases. Like any ledger, they record transactions; unlike traditional ledgers, however, blockchains are distributed across networked computer systems. Anyone with an internet connection and access to the blockchain can view and transact on the chain.
This open, consensus-based nature of blockchain – with everyone on the chain checking the validity of every transaction according to an established set of rules – enables conflicts to be resolved automatically and transparently to all participants. This dispenses with the need for a central authority to enforce trust and allows participants to build in automation through smart contracts.
The Riskstream Collaborative is the largest blockchain consortium in insurance, with over 30 carriers, brokers, and reinsurers as members who lead governance and activity. An “associate member ecosystem” is beginning to be established, and RiskStream is inspecting use cases in personal lines, commercial lines, reinsurance, and life and annuities.
Cybersecurity is no longer an emerging risk but a clear and present one for organizations of all sizes, panelists on a panel at Triple-I’s Joint Industry Forum (JIF) said. This is due in large part to the fact that cybercriminals are increasingly thinking and behaving like businesspeople.
“We’ve seen a large increase in ransomware attacks for the sensible economic reason that they are lucrative,” said Milliman managing director Chris Beck. Cybercriminals also are becoming more sophisticated, adapting their techniques to every move insurers, insureds, and regulators make in response to the latest attack trends. “Because this is a lucrative area for cyber bad actors to be in, specialization is happening. The people behind these attacks are becoming better at their jobs.”
As a result, the challenges facing insurers and the customers are increasing and becoming more complex and costly. Cyber insurance purchase rates reflect the growing awareness of this risk, with one global insurance broker finding that the percentage of its clients who purchased this coverage rose from 26 percent in 2016 to 47 percent in 2020, the U.S. Government Accountability Office (GAO) stated in a May 2021 report.
Panel moderator Dale Porfilio, Triple-I’s chief insurance officer, asked whether cyber is even an insurable risk for the private market. Panelist Paul Miskovich, global business leader for the Pango Group, said cyber insurance has been profitable almost every year for most insurers. Most cyber risk has been managed through more controls in underwriting, changes in cybersecurity tools, and modifications in IT maintenance for employees, he said.
By 2026, projections indicate insurers will be writing $28 billion annually in gross written premium for cyber insurance, according to Miskovich. He said he believes all the pieces are in place for insurers to adapt to the challenges presented by cyber and that part of the industry’s evolution will rely on recruiting new talent.
“I think the first step is bringing more young people into the industry who are more facile with technology,” he said. “Where insurance companies can’t move fast enough, we need partnerships with managing general agents, with technology and data analytics, who are going to bring in data and new information.”
“Reinsurers are in the game,” said Catherine Mulligan, Aon’s global head of cyber, stressing that reinsurers have been doing a lot of work to advance their understanding of cyber issues. “The attack vectors have largely remained unchanged over the last few years, and that’s good news because underwriters can pay more attention to those particular exposures and can close that gap in cybersecurity.”
Mulligan said reinsurers are committed to the cyber insurance space and believe it is insurable. “Let’s just keep refining our understanding of the risk,” she said.
When thinking about the future, Milliman’s Beck stressed the importance of understanding the business-driven logic of the cybercriminals.
If, for example, “insurance contracts will not pay if the insured pays the ransom, the logic for the bad actor is, ‘I need to come up with a ransom schema that I’m still making money’,” but the insured can still pay without using the insurance contract.
This could lead to a scenario in which the ransom demands become smaller, but the frequency of attacks increases. Under such circumstances, insurers might have to respond to demand for a new kind of product.
The global pandemic accelerated many technological advances that were already underway in the insurance industry – changes that are likely to pick up speed as COVID-19 recedes, according to Rohit Verma, CEO, Crawford & Co.
Triple-I CEO Sean Kevelighan recently spoke with Verma about the dramatic changes taking place as virtual interactions became more necessary and expected by consumers – especially in the early stages of the COVID-19 crisis. Crawford is a global provider of claims management solutions.
“We have a self-service app which had probably a seven to 10 percent adoption rate,” Verma said in the conversation, which you can watch in full below. “Within the first three months, that adoption rate went up from seven to 10 percent to about 35 to 40 percent.”
Verma said he expects further acceleration of digitization in insurance, with start-ups partnering with larger, established companies to transform how insurance is done. The biggest obstacle, as he sees it, is the question: “Do we approach problems with a viewpoint of how we do solve them digitally, or do we approach them on how we solve them traditionally?”
So, what better time than now (before it’s too late!) to bust the cliché that insurance is a boring industry.
The cliché might be rooted in the idea that insurance is all about remaining cozily in some imaginary “safety zone”. Or maybe in the fact that the industry’s visual surface tends to be one of dull-looking paperwork full of fine print.
But think about it: the entire industry is rooted in risk!
Automobile accidents and other forms of property damage are only the start of it. There’s liability risk – the risk of being sued: product liability, professional liability, employment practices, directors and officers, errors and omissions, medical malpractice – the list goes on, and insurance professionals have to understand these areas of risk intimately to price policies, set aside appropriate reserves, and pay claims in a timely fashion.
Is climate-related risk keeping you up at night? You’re not alone. Insurers have been working on that one for decades, empowered by sophisticated modeling and analytics capabilities. They aren’t just worrying about extreme weather and climate – they’re partnering with other industries, communities, and governments to do something about it.
And, speaking of sophisticated technology – what about cyber risk? The average cost of a data breach rose year over year in 2021 from $3.86 million to $4.24 million, according to a recent report by IBM and the Ponemon Institute — the highest in the 17 years that this report has been published. These kinds of numbers add up quickly. Unlike flood and fire – perils for which insurers have decades of data to help them accurately measure and price policies – cyber threats are comparatively new and constantly evolving. The presence of malicious intent results in their having more in common with terrorism than with natural catastrophes.
These are just a few of the risks types insurance professionals look in the eye daily, working with a wide range of experts across industries and disciplines to meet them. From the individual and family level to businesses large and small to the global economy, insurers play a critical role as both risk-management partners and financial first responders.
Keep these things in mind next time you catch yourself stifling a yawn at the mention of insurance!
Sean Kevelighan leads Climate Risk and Resilience panel. (Photo/videos by Scott Holeman, Media Relations Director, Triple-I)
By Loretta Worters, Vice President, Media Relations, Triple-I
Insuretech Connect – the world’s largest gathering of insurance leaders and innovators – last week brought together insurance technology stakeholders to network, share insights, and learn about leading-edge technology across all insurance lines.
Conference participants included Pete Miller, president and CEO of The Institutes, who discussed risk mitigation through new technology.
“Capturing data about the things we do and then allowing us to mitigate risk before we even get to the insurance function, that’s really where I think this industry is going,” he said.
One panel, Climate Risk and Resilience, focused on the importance of Insurtech and innovation to the success and sustainability of the industry. Moderated by Triple-I CEO Sean Kevelighan, the panel included Sean Ringsted, chief digital officer at Chubb; Christie McNeill, associate partner with McKinsey & Company and leader of ESG and Climate Change for the Insurance Practice in North America; Alisa Valderrama, CEO and co-founder of FutureProof Technologies, a venture-backed financial analytics software company specializing in climate risk; and Susan Holliday, Triple-I nonresident scholar and senior advisor to the International Finance Corporation (IFC) and the World Bank, where she focuses on insurance and Insuretech.
“Insurers are no stranger to climate and extreme weather,” Kevelighan said. “They have had a financial stake in it for decades.”
He noted that insured losses caused by natural disasters have grown by nearly 700 percent since the 1980s and four of the five costliest natural disasters in U.S. history have occurred over the past decade.
U.S. insurers paid out $67 billion in 2020 due to natural disasters. The insured losses emerged in part as the result of 13 hurricanes, five of the six largest wildfires in California’s history, and a derecho that caused significant damage in Iowa.
This year’s Hurricane Ida is expected to cost insurers at least $31 billion and to push Hurricane Andrew out of the top five damaging storms. 2021 has been another record year for wildfires. January 1 to September 19, 2021 there were 45,118 wildfires, compared with 43,556 in the same period in 2020.
The panelists talked about how insurers have long been aware of climate risk and – to the extent that existing data-gathering and modeling technologies allowed – considered it in risk pricing and reserving. As information storage and processing have vastly improved, the industry has not only gotten better at underwriting and reserving for these risks – it has identified opportunities in areas it once could only view as problems.
Improved modeling, for example, has increased insurers’ comfort with and appetite for writing flood coverage and spurred the development of new products.
“Insurers are and always will be financial first responders, but there’s a growing realization that risk transfer alone isn’t enough,” Kevelighan said. “Insurance is one important step toward resilience. It’s well documented that better-insured communities recover faster from disasters. But more is required to address increasingly complex global risks.”
Videos and voice recordings manipulated with previously unheard-of sophistication – known as “deepfakes“ – have proliferated and pose a growing threat to individuals, businesses, and national security, as Triple-I warned back in 2018.
Deepfake creators use machine-learning technology to manipulate existing images or recordings to make people appear to do and say things they never did. Deepfakes have the potential to disrupt elections and threaten foreign relations. Already, a suspected deepfake may have influenced an attempted coup in Gabon and a failed effort to discredit Malaysia’s economic affairs minister, according to Brookings Institution.
Most deepfakes today are used to degrade, harass, and intimidate women. A recent study determined that up to 95 percent of the thousands of deepfakes on the internet were pornographic and up to 90 percent of those involved nonconsensual use of women’s images.
Businesses also can be harmed by deepfakes. In 2019, an executive at a U.K. energy company was tricked into transferring $243,000 to a secret account by what sounded like his boss’s voice on the phone but was later suspected to be thieves armed with deepfake software.
“The software was able to imitate the voice, and not only the voice: the tonality, the punctuation, the German accent,” said a spokesperson for Euler Hermes SA, the unnamed energy company’s insurer. Security firm Symantec said it is aware of several similar cases of CEO voice spoofing, which cost the victims millions of dollars.
A plausible – but still hypothetical – scenario involves manipulating video of executives to embarrass them or misrepresent market-moving news.
Insurance coverage still a question
Cyber insurance or crime insurance might provide some coverage for damage due to deepfakes, but it depends on whether and how those policies are triggered, according to Insurance Business. While cyber insurance policies might include coverage for financial loss from reputational harm due to a breach, most policies require network penetration or a cyberattack before it will pay a claim. Such a breach isn’t typically present in a deepfake.
The theft of funds by using deepfakes to impersonate a company executive (what happened to the U.K. energy company) would likely be covered by a crime insurance policy.
Little legal recourse
Victims of deepfakes currently have little legal recourse. Kevin Carroll, security expert and Partner in Wiggin and Dana, a Washington D.C. law firm, said in an email: “The key to quickly proving that an image or especially an audio or video clip is a deepfake is having access to supercomputer time. So, you could try to legally prohibit deepfakes, but it would be very hard for an ordinary private litigant (as opposed to the U.S. government) to promptly pursue a successful court action against the maker of a deepfake, unless they could afford to rent that kind of computer horsepower and obtain expert witness testimony.”
An exception might be wealthy celebrities, Carroll said, but they could use existing defamation and intellectual property laws to combat, for example, deepfake pornography that uses their images commercially without the subject’s authorization.
A law banning deepfakes outright would run into First Amendment issues, Carroll said, because not all of them are created for nefarious purposes. Political parodies created by using deepfakes, for example, are First Amendment-protected speech.
It will be hard for private companies to protect themselves from the most sophisticated deepfakes, Carroll said, because “the really good ones will likely be generated by adversary state actors, who are difficult (although not impossible) to sue and recover from.”
Existing defamation and intellectual property laws are probably the best remedies, Carroll said.
Potential for insurance fraud
Insurers need to become better prepared to prevent and mitigate fraud that deepfakes are capable of aiding, as the industry relies heavily on customers submitting photos and video in self-service claims. Only 39 percent of insurers said they are either taking or planning steps to mitigate the risk of deepfakes, according to a survey by Attestiv.
Business owners and risk managers are advised to read and understand their policies and meet with their insurer, agent or broker to review the terms of their coverage.
By Marielle Rodriguez,Social Media and Brand Design Coordinator, Triple-I
Sunil Rawat
Triple-I’s “Insurance Careers Corner” series was created to highlight trailblazers in insurance and to spread awareness of the career opportunities within the industry.
This month we interviewed Sunil Rawat, Co-Founder and CEO of Omniscience, a Silicon Valley-based AI startup that specializes in Computational Insurance. Omniscience uses five “mega-services” that comprise of underwriting automation, customer intelligence, claims optimization, risk optimization, and actuarial guidance to help insurance companies improve their decision-making and achieve greater success.
We spoke with Rawat to discuss his technical background, the role of Omniscience technology in measuring and assessing risk, and the potential flaws in underwriting automation.
Tell me about your interest in building your business. What led you to your current position and what inspired you to found your company?
I’m from the technology industry. I worked for Hewlett Packard for about 11 years, and hp.com grew about 100,000% during my tenure there. Then I helped Nokia build out what is now known as Here Maps, which in turn powers, Bing Maps, Yahoo Maps, Garmin, Mercedes, Land Rover, Amazon, and other mapping systems.
I met my co-founder, Manu Shukla, several years ago. He’s more of the mad scientist, applied mathematician. He wrote the predictive caching engine in the Oracle database, the user profiling system for AOL, and the recommender system for Comcast. For Deloitte Financial Advisory Services, he wrote the text mining system used in the Lehman Brothers probe, the Deepwater Horizon probe and in the recent Volkswagen emissions scandal. He’s the ‘distributed algorithms guy’, and I’m the ‘distributed systems guy’. We’re both deeply technical and we’ve got this ability to do compute at a very high scale.
We see an increasing complexity in the world, whether it’s demographic, social, ecological, political, technological, or geopolitical. Decision-making has become much more complex. Where human lives are at stake, or where large amounts of money are at stake on each individual decision, each individual decision’s accuracy must be extremely high. That’s where we can leverage our compute, taken from our learnings over the last 20 years, and bring it to the insurance domain. That’s why we founded the company — to solve these complex risk management problems. We’re really focused on computational finance, and more specifically, computational insurance.
What is Omniscience’s overall mission?
It’s to become the company that leaders go to when they want to solve complex problems. It’s about empowering leaders in financial services to improve risk selection through hyperscale computation.
What are your main products and services and what role does Omniscience technology play?
One of our core products is underwriting automation. We like to solve intractable problems. When we look at underwriting, we think about facultative underwriting for life insurance where you need human underwriters. The decision-making heuristic is so complex. Consider somebody who’s a 25-year-old nonsmoker asking for a 10-year term policy of $50,000 — it’s kind of a no-brainer and you can give them that policy. On the other hand, if they were asking for $50 million, you’re certainly going to ask for a blood test, a psychological exam, a keratin hair test, and everything in between. You need humans to make these decisions. We managed to take that problem and use our technology to digitize it. If you take a few hundred data fields, and a few 100,000 cases to build an AI model, it quickly becomes completely intractable from a compute standpoint. That’s where we can use our technology to look at all the data in all its facets — we automate and use all of it.
Once you’ve got an AI underwriter’s brain in software, you think from the customer intelligence standpoint. You’ve got all this rich transaction data from your customers to pre-underwrite, qualify, and recommend them for different products. We’ve also built a great capability in the data acquisition area. For workers comp and general liability, we have the data that improves the agent experience. We can also correctly classify any NAICS codes and can help with claims avoidance and finding hidden risk. We’ve also got a great OCR capability. In terms of digitization of text, we can take complex tabular data and digitize it without any human in the loop. We’re able to do this worldwide, even in complex Asian languages. We also do a lot of work in asset and liability management and can do calculations that historically have been done in a very low-powered, inaccurate manner. We can run these calculations daily or weekly, vs annually, which makes a big difference for insurance companies.
We also work in wildfire risk. A lot of wildfire spread models look at a ZIP+4 or a zip code level, and they take about four hours to predict one hour of wildfire spread, so about 96 hours to predict one day of wildfire spread at a zip code level. In California, where I am, we had lots of wildfires last year. When you double the density of the grid, the computation goes up 8x. What we were able to do is improve and look at the grid at 30 meters square, almost at an individual property size. You can individually look at the risk of the houses. At a 30-meter level, we can do one hour of wildfire propagation in 10 seconds, basically one day in about four minutes.
Are there any potential flaws in relying too much on automation technology that omits the human element?
Absolutely. The problem with AI systems is they may generally be only as good as the data that they’re built on. The number one thing is that because we can look at all the data and all its facets, we can get to 90+ percent accuracy on each individual decision. You also need explainability. It’s not like an underwriter decides in a snap and then justifies the decision. What you need from a regulatory or an auditability standpoint is that you must document a decision as you go through the decision-making process.
If you’re building a model off historical data, how do you make sure that certain groups don’t get biased again? You need bias testing. Explainability, transparency, scalability, adjustability — these are all very important. From a change management, risk management standpoint, you have the AI make the decision, and then you’ll have a human review. After you’ve done that process for some months, you can introduce this in a very risk-managed way. Every AI should also state its confidence in its decision. It’s very easy to decide, but you also must be able to state your confidence number and humans must always pay attention to that confidence number.
What is traditional insurance lacking in terms of technology and innovation? How is your technology transforming insurance?
Insurers know their domain better than any insurtech can ever know their domain. In some ways, insurance is the original data science. Insurers are very brilliant people, but they don’t have experience with software engineering and scale computing. The first instinct is to look at open-source tools or buy some tools from vendors to build their own models. That doesn’t work because the methods are so different. It’s kind of like saying, “I’m not going to buy Microsoft Windows, I’m going to write my own Microsoft Windows”, but that’s not their core business. They should use their Microsoft Windows to run Excel to build actuarial models, but you wouldn’t try to write your own programs.
We are good at system programming and scale computing because we’re from a tech background. I wouldn’t be so arrogant to think that we know as much about insurance as any insurance company, but it’s through that marriage of domain expertise in insurance and domain expertise in compute that leaders in the field can leapfrog their competitors.
Are there any current projects you’re currently working on and any trends you see in big data that you’re excited about?
Underwriting and digitization, cat management, and wildfire risk is exciting, and some work that we’re doing in ALM calculations. When regulators are asking you to show that you have enough assets to meet your liabilities for the next 60 years on a nested quarterly basis, that becomes very complex. That’s where our whole mega-services come in — if you can tie all together your underwriting, claims, and capital management, then you can become much better at selection, and you can decide how much risk you want to take in a very dynamic way, as opposed to a very static way.
The other things we’re excited about is asset management. We are doing some interesting work with a very large insurer. What we’ve been able to do is boost returns through various strategies. That’s another area we’re excited about — growing quite rapidly in the next year.
What your goals are for 2021 and beyond?
It’s about helping insurers develop this multi-decade compounding advantage through better selection, and we’re just going to continue to execute. We’ve got a lot of IP and technology developed, and we’ve got pilot customers in various geographies that have used our technology. We’ve got the proof points and the case studies, and now we’re just doubling down on growing our business, whether it’s with the same customers we have or going into more product lines. We are focused on serving those customers and signing on a few more customers in the three areas where we are active, which is Japan, Hong Kong, China, and North America. We are focused on methodically executing on our plan.
With the cyber risk environment worsening significantly, a recent A.M. Best report says, “prospects for the U.S. cyber insurance market are grim.”
The recent proliferation of ransomware attacks leading to business interruption and other related hazards has caused cyber insurance – which began as a diversifying, secondary line – to become a primary component of a corporation’s risk management and insurance purchasing decisions.
Consequently, the A.M. Best report says, insurers urgently need to reassess all aspects of cyber risk, including their appetite, risk controls, modeling, stress testing, and pricing, to remain a viable long-term partner for dealing with cyber risk.
Cyber insurance “take-up” rates (the percentage of eligible customers opting to buy the coverage) are on the rise, according to a recent Government Accountability Office (GAO) report – to 47 percent in 2020 from 26 percent in 2016. This increased demand has been accompanied by higher prices for cyber insurance, as well as reduced coverage limits for some industry sectors, such as healthcare and education. In a recent survey of insurance brokers, the GAO says, more than half of respondents’ clients saw prices rise 10 to 30 percent in late 2020.
“The rate increases for cyber insurance outpaced that of the broader property/casualty industry, but the increase in cyber losses outstripped the rate hikes, which suggests more trouble for 2021 as ransom demands continue to grow,” said Sridhar Manyem, director, industry research and analytics at A.M. Best.
The A.M. Best report says the challenges the cyber insurance market faces include:
Rapid growth in exposure without adequate underwriting controls;
The growing sophistication of cyber criminals that have exploited malware and cyber vulnerabilities faster than companies that may have been late in protecting themselves; and
The far-reaching implications of the cascading effects of cyber risks and the lack of geographic or commercial boundaries.
In April, Federal Reserve Chairman Jerome Powell said cyberattacks are the foremost risk to the global financial system, even more so than the lending and liquidity risks that led to the 2008 financial crisis.
“The world evolves, and the risks change as well and I would say that the risk that we keep our eyes on the most now is cyber risk,” Powell said. “There are scenarios in which a large financial institution would lose the ability to track the payments that it’s making, where you would have a part of the financial system come to a halt, and so we spend so much time, energy and money guarding against these things.”
More recently, FBI Director Christopher Wray compared compared the current spate of cyberattacks with the challenge posed by the Sept. 11, 2001, terrorist attacks. He said the agency was investigating about 100 different types of ransomware, many tracing back to hackers in Russia.
As we’ve written elsewhere with respect to natural catastrophes, it seems the world has entered a phase in which the traditional emphasis on risk transfer through insurance products is no longer sufficient to address today’s complex, interconnected perils. A focus on resilience and pre-emptive mitigation is in order, and insurers are well positioned to serve not only as financial first responders but as partners in managing these evolving hazards.
Ms. Winnie Tsen, Assistant Director, Financial Markets and Community Investment, U.S. Government Accountability Office (GAO), was one of the key contributors to the GAO’s May 2021 report on cyber insurance.
By Marielle Rodriguez, Social Media and Brand Design Coordinator
Janthana Kaenprakhamroy
Triple-I’s “Insurance Careers Corner” series was created to highlight trailblazers in insurance and to spread awareness of the career opportunities within the industry.
May is Asian American and Pacific Islander Heritage Month, and this month we interviewed Janthana Kaenprakhamroy, CEO of London-based insurtech, Tapoly. Although Janthana lives in the UK, we believe that Asian heritage should be celebrated no matter where you live.
Founded in 2016, and backed by Lloyd’s of London, Tapoly is Europe’s first and fastest growing insurtech, providing on-demand flexible commercial insurance products for SMEs, freelancers, the self-employed and the gig economy. Recognized as Insurance Provider of the Year at the British Small Business Awards in 2018, Tapoly’s mission is to make insurance simple, accessible, and flexible.
We spoke with Kaenprakhamroy to discuss the role of AI and technology in her business, the boom of the sharing economy, and what the traditional insurance industry can learn from insurtech.
Tell us about your background and your interest in building a business. What led you to your current position and what inspired you to found your company, Tapoly?
I was born in and come from a small part of Thailand, grew up in Sweden, and have lived in London for the last 20 years. I have roots in different parts of the world, which has shaped my international way of thinking. I feel like I don’t fit a specific stereotype and can blend into different cultures.
I’m an accountant by trade and have worked in investment banking for almost my entire career. In late 2016, I decided to quit my job and build Tapoly. We provide technology solutions and insurance products locally in the UK as well as in Asia.
I was never sure what I wanted to do until I came across a problem in 2016 when I was trying to buy insurance for my short letting over the summer, which you can only do for about 90 days a year. In 2016, no insurance companies were serving the types of products for the short letting space. Ever since then, we’ve been developing technology solutions and products to cover this massively underserved market within the micro, SME, and freelancing space.
What is your organization’s mission? What role does tech and AI play in your platform?
Our mission is very simple – we want to able to provide an insurance solution online that is quick and easy for people, in the most convenient way, which is one thing in the commercial lines space that’s not very well-developed. Most companies are buying insurance through their brokers, rather than online directly. We wanted to make commercial lines products easier and less time-consuming for customers to access, without making them answer several questions that they may or may not know how to answer.
If you offer insurance online directly, then the underwriting decision must be prompt and that can only be achieved when you have data on your customers. There is data that traditional insurance companies aren’t using, for example, social media data, which can be cross-referenced with [the customer’s] profile. It’s all about augmenting data to amplify or make customers profiles more prominent for underwriting decisions – it’s something insurtech is doing well. Insurtech would allow data to flow from the point of the customer buying insurance to the point of the underwriter making the decision – this makes the process more seamless and transparent.
A lot of what we do at Tapoly is data analytics. It’s not only for risk selection and underwriting alone – it’s also for customer acquisition and marketing. Customer segmentation is very important, and you can only do it with a certain level of good-quality data on your customers.
What do you see as the biggest pain points for customers within traditional insurance that insurtech can better solve?
Customers in the market segment that we serve, which is microbusinesses and freelancers, have three main pain points. One is the price, especially for customers who do ad-hoc jobs which are not part of their core competency or core activity. Second is the convenience – the ability to fill in a simple questionnaire and get insurance quickly. Third is the availability – some products are not available for some freelancers. For example, a group of freelancers doing construction work in a certain environment are less likely to get certain insurance products due to their high risk profile.
Within the gig economy, there are job titles that are outside the norm and that don’t fall inside traditional insurance categories. We need to revamp the list of professions. In insurtech, we see gaps in coverage [in certain industries]. For example, marketplaces where the underlying risks may be different depending on what level of services and products the platform is providing. Another example may be the evolution of some professions, e.g. “virtual assistants”, where they may in some cases provide basic accounting services, which would previously be performed by certified professionals, because accounting is also moving online. There’s a lot of mismatch between the way insurers categorize their customers and the profession that customers recognize themselves as, and the ability to buy insurance automatically in the most convenient way.
Do you see innovation and transformation happening in the traditional insurance space?
I think the insurance industry is well-aware of the need for innovation and many companies are at the beginning of innovating, but innovation takes time. While we recognize the need, it will take time to implement. As a startup, we don’t have a hierarchical structure or have as many constraints. We can build anything we want without waiting for the approval of senior management. What insurtech can bring is the speed to market, the ability to adapt, and to implement changes and help insurers prove the concept in the most cost-effective way.
In what ways has COVID-19 impacted the sharing economy and your business? What are your predictions for the growth and trajectory of the sharing economy?
A 2015 PWC report showed that revenue from the sharing economy was $15 billion in 2013 and would reach $335 billion in 2025. That’s a phenomenal increase in the market within 12 years. I think the COVID-19 pandemic really accelerated the sharing economy. There are so many businesses that did fantastically well during the pandemic, including businesses in logistics and delivery, and the insurtechs that are operating in that space. From the product delivery, customer-facing side, we didn’t have a problem because we were already set up to operate online. However, it did impact our customers and some of them didn’t renew their insurance or either postponed or changed their policy.
In terms of opportunities, there are many insurance companies or intermediaries that have started to think about innovation. COVID-19 has really accelerated that thinking because tech has become a big hurdle. There are a lot of operational challenges among larger insurance companies that are not set up to sell insurance digitally. That is something insurtech can take advantage of because we are already set up to do this.
Let’s talk about diversity in VC funding and entrepreneurship. A2019 Diversity VC report showed that ethnic minorities are under-represented in venture capital and women are under-represented in senior roles. Another2020 Extend Ventures report shows that female entrepreneurs receive just a fraction of available funding that male founders do. Were there any initial challenges in founding your company and attaining funding, and how did you overcome these obstacles? Are there any present challenges of being an Asian- and woman-owned business and founder?
In the beginning, not raising enough funding can cause a slowdown in your growth. Even with the best ideas, it’s hard to scale your business without capital. I certainly think that the confidence in a woman in running a business could be improved in the VC space. There are a lot of stereotypes and unconscious biases that people apply to their decisions. The VC space needs to work on being self-aware and educate themselves around these issues especially when judging a first-time entrepreneur. There is also uncertainty and a lack of data on startups that make it difficult for VCs to validate and invest in, on top of gender stereotypes.
My biggest daily challenge is finding enough capital to be able to grow my business. The difficulty for early-stage founders is balancing your own interests with the investor’s interests and figuring out how much you want to raise versus how much you can raise. To overcome this problem, we usually find strategic investors that can add a lot of value.
What are your goals for 2021 and beyond? Where do you see the traditional industry heading in the next few years given the pandemic?
We’re preparing for hockey stick growth in 2021 and want to exponentially grow our company in 2022. My aim is to raise enough money to be a larger team and to have the capacity to manage that level of volume and growth.
I think the traditional insurance industry will evolve slowly in the next couple of years. A lot of insurers have been badly hit due to COVID-19 because of claim costs and loss of investments. It would take a couple of years before we recover fully, and hopefully insurtech will still be relevant within this space. At least if anything, insurance companies will be spending more on innovation to reduce their claims and operating costs.
