06.10.21
Jonathan Sherling

Why technology is about to revolutionize the specialty commercial insurance market

It’s impossible to ignore how software has changed our world in the past decade — we now use ride-hailing apps for transportation, turn to streaming services for limitless entertainment, and track our food deliveries through third-party apps. Companies are pioneering new and evolving technologies as well as infrastructure to remain competitive. If they don’t, they fall behind — Blockbuster and cab companies can attest to the struggles of staying afloat once they’re competing against software-focused, industry disruptors. The marketplace envisioned by Marc Andreesen when he wrote that “software is eating the world” back in 2011 is becoming evident in every part of our working and personal lives. 

There are exceptions, however. Notably reluctant to evolve, most commercial insurers have shrugged off technological disruption, and remain behind the curve of incumbent businesses in other industries who are in some cases already several years into wholesale digital transformations. 

The lagging pace in our industry is not for a lack of inspiration from closely-related fields. The past decade has seen the explosive growth of “Fintech”, with enormous investments in the banking and finance sectors. And within insurance there’s been significant tech investment in personal lines: despite recent fluctuations in stock price, Lemonade has a greater market cap than The Hanover, Kemper, and other household names. Hippo, Metromile and Root are notable additions to the insurtech push in this market. These success stories in banking, finance, and personal lines insurance have proven overwhelmingly that venture-backed, technology-driven businesses can penetrate highly regulated industries. 

So why did commercial insurance get left behind? Let’s explore what has happened in other industries as a lens to see where opportunities lay ahead. 

When Insurance and Finance Parted Ways 

While the majority of the insurance industry remained stagnant from a technology perspective in the 1990s, we saw a dramatic shift in the functionality of tools employed in the banking sector during that time. Banks capitalized on software to enhance efficiency, while markets progressed to fully electronic trading. With the digitalization of portfolio management, as well as software simulations of trading positions and adverse events, the financial industry was able to redefine how it worked. The birth of “fintech” shortly followed, particularly in consumer-facing markets. We are now starting to see the marriage of fintech and traditional models as recently evidenced by companies like SoFi.

It’s notable that within fintech the businesses that have seen the most success are those that have acknowledged and embraced regulation. While there is some history of those within the fintech industry to be blind to regulation — with a mantra of “we are not financial institutions” — those that have instead blurred the lines and coordinated with banks and regulators have been able to work collaboratively to create regulations specific to their offerings. It was long believed, both in finance and insurance, that if something was complicated enough, it was immune from the disruptions of the tech world. We can see that is no longer the case, especially if the tech is making complex processes easier. 

Meanwhile, insurers in specialty commercial did little to invest in new technology to aid better risk analysis, risk selection, mitigation, modeling, stress testing and event simulation. Today, many insurers are not capitalizing on technology for underwriting, and some lines in specialty insurance continue to utilize processes that are completely manual. Looking at the success of Lemonade and others, we can assume that software and the use of data science for analytics and decision making will not be long in coming for specialty insurance. 

One notable exception to this long-brewing dynamic is worth mentioning. Cyber-focused insurtechs have pioneered the use of public-facing security information about insureds to inform underwriting, risk selection and pricing while also providing security recommendations to aid with risk mitigation. As models like those used by tech-enabled MGA’s continue to build sophistication by leveraging an increasing number of data sources, the marginal benefit to the combined ratio via lower loss and expense ratios will become increasingly evident. Traditional insurers will be hard-pressed to ignore these advancements when their businesses are held up to the light against the competition. 

Tech, Meet Insurance 

Insurtechs have seen success with new underwriting models and techniques driven by predictive modelling and harnessing real-time data. This allows them to view risk in an entirely new way, often more effectively. There’s no reason this approach must remain limited to lines like Cyber Liability.

D&O, for example, has decades of actuarial data and experience. Underwriters are drawn to measuring company solvency, sector exposure, the competitive landscape and so on. The underwriting information available to measure those metrics (in the case of private companies) is sometimes one or two years old, and may not be reflective of the current risk that company carries. Insurtechs are establishing new underwriting models and techniques that can harness real-time data, apply predictive modelling to that data and view the risk in a new paradigm.

Skeptics will assert that using different models to assess risk outside the existing framework is only worthwhile if it outperforms the existing framework it seeks to replace. That is a fair position; but we are well past the point in technological progress where the ability to harness data to better predict underwriting losses over time is in question. If such models haven’t been successfully demonstrated in real-world underwriting for a particular product, the question now is not if, but when, they will. Fintechs and insurtechs may have taken on simpler or more data-rich targets first, but with the concept now proven, there’s a playbook for more ambitious applications. 

Even if one remains doubtful that technology will overhaul existing underwriting frameworks, there are a number of ways to harness data science while working within them. For example, insurers can use machine learning to digest material, such as the priorities document and subsequent updates or trends in SEC enforcement, as they are released, and automatically apply that logic to their underwriting model. A product manager now has more time to spend elsewhere: educating, drafting language, reviewing referrals and simulating the impact of hypothetical adjustments to underwriting appetite on the current or historical portfolio. 

Although the technology described would surely allow overwhelmed underwriters and product managers to shift their focus beyond data gathering, data entry, and basic analysis to the more technical aspects of their roles — negotiating and executing complex transactions — the benefits extend beyond time efficiency. As the algorithms become more sophisticated, underwriting managers are able to better position their portfolios and aid product development. The utilization of data can help identify products, coverage sectors, attachment strategies and pricing elasticity — all of which can be simulated to establish the optimums in a predictive manner. 

D&O, Ready for Tech

Traditional carriers risk being left behind as startups in specialty commercial insurance enhance the use of AI and data-science based tech to overhaul the underwriting process. At Corvus, we’ve seen how specialty insurance and technology work collaboratively and cohesively to provide brokers with actionable information that assist with risk management. We use data to provide our distribution partners and clients feedback on their risk, exposures and transparency into our underwriting assumptions.

In other industries, we’ve witnessed how working with the rise of technology and software has enabled companies to innovate and succeed. We’ve also seen how a resistance to our evolving insurance marketplace has been commonplace (and still is) for many carriers. But if we look back at the evolution of fintech — where many startups are now collaborating with the banks themselves — we can see how the integration of technology and intricate processes is the future.

Corvus vCISO is here: meet your clients’ new (virtual) cybersecurity pro

  Corvus was founded on the idea of building a safer world. While we’ve pursued a number of initiatives to further our mission over time, the heart of our efforts remains the education and personalized data we provide brokers and policyholders to reduce cyber risk.  

(Re) Building a Ransomware Risk Score for the Future

  As ransomware rose to become the single biggest driver of cyber insurance claims in 2020, we felt that this aspect of cyber risk deserved more detailed reporting for brokers and policyholders. So we got to work. We decided to re-create one aspect of our overall cyber risk score, adding more detail and providing a separate report page in Smart Cyber quotes. You can read about the specifics of the score here.