Transforming the art of underwriting

Delving into the details has always been a central part of underwriting, but there is a delicate balance to be struck. It’s all too easy to get stuck in the weeds of a submission, to focus on the day-to-day process and lose sight of the bigger picture. However, being able to take a wider view is often what is needed to push the insurer into new areas of growth and profitability.

During their presentation at Underwriting Innovation USA on November 10, Jeff Tyler, head of product, data science and engineering, and Jay Nichols, strategic advisor, of Two Sigma IQ, will demonstrate how the twin opportunities of technology and data science can help elevate the underwriter’s skill and expertise.

They will reveal where to glean new insights and how to manage the underwriting process so it becomes a faster, sharper, leaner engine that can drive the business forward, even in the most pressurised of markets. Tyler and Nichols spoke to Intelligent Insurer ahead of the event.

Can you outline event-based underwriting as it stands today?

Jay Nichols: Event-based underwriting is founded on three questions: what events could happen? Given those events, what could the damage be? Given that damage, what is the cost to the insurer? It’s essentially looking at the price of risk on a probabilistic basis.

Event-based underwriting has been used in property cat for a long time and transformed it when it was introduced. The time has come for the industry to migrate it to other lines.

Jeff Tyler: The reason it hasn’t migrated to other lines is because only now do we have the technological efficacy, the availability of computing power, and the data resources to allow it. The advancement of artificial intelligence (AI) and data science techniques puts the industry in a good position to take advantage of event-based underwriting techniques.

Nichols: Data science is where the big change is now, particularly the ability to convert a claims database into an event database. In property cat, the computing power was limited so underwriters had to take shortcuts to explode out the tail. As technology has improved and become more accessible, the underwriting process has improved with it.

Tyler: Investing in data science was not something everyone was doing in the past but now people have realised they should be investing time and resources in it. It’s cost effective, so insurers should be thinking about how they put tools in the hands of the underwriters, enable them to use data science techniques and give them a head start.

How is this going to upgrade the underwriter’s role?

Nichols: It elevates the art of underwriting by allowing underwriters to have more information available without having to create it themselves. It means the underwriter becomes more of a high-level evaluator of analysis and less of a processor of data.

Tyler: The system lets underwriters do the things they’re good at better, faster, and at greater scale. It takes them out of the trenches, where they are looking at submissions risk by risk, and allows them to look across their entire portfolio of risk and understand how they want to optimise it without dealing with a constant inflow of data.

We see a world where the machine does that for them at the submission level and sets them free to spend more time on the big picture, which is where their insights are most valuable.

What new insights should carriers be looking for in the richer datasets they can access?

Tyler: One of the most important things will be understanding what has happened in a business historically—and especially the trends and business decisions that have helped them to mitigate losses. It’s very difficult to do that when you’re looking at submissions on a case-by-case basis.

Now, it’s possible to understand how certain technological advances have impacted the client’s ability to run a safer business programme, for example.

What opportunities are carriers currently missing out on that could be resolved here?

Tyler: This is going to be a natural process. Making money on current strategies in the long run isn’t inevitable, so if you’re not planning for the next step, you’re already behind.

Insurers need to be asking themselves: “how can I keep my edge?” and “how do I apply these advancements today so I can sustain my advantage?”.

Nichols: It’s not a question of “if it ain’t broke, don’t fix it”. Insurers that have the databases and data-processing advantages, and choose to move forward and innovate, will inevitably pick out the better risks. Those who don’t will end up with adverse selection.

What does this mean for the next generation of underwriters?

Nichols: A lot of underwriters straight out of college are doing factor-based underwriting. That’s just how the training process works. But with access to better technology, they can gain a deeper understanding of the risk, and understand the effectiveness of mitigation and events that could adjust the ultimate price of the policy.

Fundamentally, it’s also a better, more interesting job—it gives frontline underwriters a more impactful role to play, along with their deeper understanding of the risks and better options for communicating around them.

Why is now the time to be talking about transforming the art of underwriting?

Tyler: This technology certainly isn’t brand new, but the industry is focused on being more efficient and it is attacking the process, trying to make it smoother and remove obstacles to the current way of thinking about risk.

We want to address the job of the underwriter, and the thought process behind risk management. Our focus is not necessarily on making a step easier but eliminating it altogether (if that’s appropriate) or replacing it with something more powerful.

We want to rethink the process holistically—things such as loss and exposure analysis should happen immediately. It shouldn’t have to be a 35-step process; leaving it as a 35-step process doesn’t serve the underwriters.

Nichols: It can be daunting. It’s not simple to make a transition like this, but you have to start by making some simplifying assumptions on the path. Apply it to lines where it can make a real difference. From there, you can iterate, learn and start to improve holistically and, at the portfolio level, not just improve efficiency.

Jeff Tyler, head of product, data science and engineering, and Jay Nichols, strategic advisor, of Two Sigma IQ, will be demonstrating how the audience can elevate the art of underwriting at Underwriting Innovation USA on November 10, 2021, at 10:50am EST.

This is the biggest online event tailored specifically to underwriting—don’t miss out. Register now!