How Does AI Help Underwriters?

Today’s underwriters are dealt a raw hand. In an increasingly volatile risk environment, they’re expected to be thorough in their analysis but are measured on their throughput. They’re asked to take the portfolio view, but a large loss on a single account can mean days of retrospective deep dives. Technology has long promised to help, but underwriters have ended up with a mess of disconnected tools and siloed data sources that take up even more time. Can AI change that?

The short answer is yes - the right AI can actually help underwriters quite a bit. While not all “insurance AI” tools are equally capable, the best AI helps underwriters focus on the right deals, support their decisionmaking with the right information, and respond to their organization’s constantly evolving portfolio balance in real time.

AI in Underwriting: Empowering Humans, Not Replacing Them

Let’s get one thing out of the way right now: AI is not here to replace human underwriters.

Insurance is an industry that’s built on trust and relationships. No matter how many technologies, guidelines, or playbooks an underwriter has to work with, the individual underwriter still plays a key role in identifying opportunities, evaluating risk, and maintaining adequate pricing in a competitive environment. Their judgment is crucial to winning the right deals.

What AI can do, extremely well, is make it easier for human underwriters to get what they actually need to identify the highest-appetite, most-winnable risks. This is more than just going through the same process in less time - while increased efficiency is one benefit of a good insurance AI, it’s not the most important benefit.

The game-changing benefit of AI is that it can provide the underwriter with the insights that they want in order to evaluate and price risk, but have never before been able to have. In this way, AI doesn’t just “save time” for the underwriter - it creates time, by helping them focus on the best deals from the very beginning.

AI Helps Underwriters Identify the Best Opportunities

Many underwriters are overwhelmed by a high number of submissions, and limited time to evaluate them. While some opportunities are better than others, the sheer volume of submissions flooding an underwriter’s inbox makes it hard to pull out the best deals.

Given enough time, an underwriter would read all their submissions. They’d evaluate each risk both independently and in the context of the portfolio, they’d identify the right price, they’d evaluate what they felt they could win, and they’d quote only the business on which they felt they could be competitive. They’d give every broker or agent that “quick no” on the risks that didn’t make the cut.

But since most underwriters don’t have enough time to do that, instead the default is often a FIFO process - the first submissions in are the first submissions out. This means sometimes submissions that are a better fit for the portfolio can end up behind a less-promising submission in the underwriter’s queue, simply because of the order they came in.

This is a prime area where AI can help. By ingesting an organization’s goals, guidelines, appetite, and historical quote-bind data, the AI can form an initial assessment of each submission, and provide the underwriter with recommendations on which submissions merit the most attention. The underwriter then applies their judgment on which deals to work, quote, and hopefully bind - but without having to wade through pages of irrelevant details first.

While the AI will never be perfect, a really good AI can also learn as it goes along. The AI can collect feedback on how the underwriter’s judgment differs from its recommendation, and update its suggestions accordingly.  The more an organization (or even a specific underwriter) uses it, the more effective it becomes at surfacing deals the underwriter will most want to see, and at making helpful suggestions. 

This helps both individual underwriters and the larger organization: experienced underwriters are able to work more efficiently, while junior underwriters can benefit from the institutional knowledge baked into how the AI has learned to respond. This is especially vital as more senior underwriters approach retirement.

AI Helps Underwriters Track Portfolio Appetite in Real Time

New deal opportunities often present underwriters with an excess of external data to sort through, but internal data is rarely so readily available. One of the biggest obstacles for underwriters trying to meet goals is how long it takes for their own organization’s performance data to become available. With data weeks or months out of date, evaluating progress towards the organization’s goals is almost impossible.

Underwriters typically only gain access to performance data in a monthly or quarterly review. By then, it’s too late to correct any issues that emerged over that period, or track the effects of any attempted course changes. From underwriting leadership to individual underwriters, everyone is flying blind.

With AI, underwriters can get real-time course corrections and tracking. It’s not feasible for an underwriter to generate a report on portfolio progress in the context of each account that they evaluate - and even if they could, they wouldn’t have time to actually read all those reports. 

AI can analyze every action within a risk as it happens, and flag problems that might otherwise not pop up for weeks. For example, if an individual underwriter picks up an otherwise-promising submission, the AI could flag immediately that that risk is no longer in appetite - something the underwriter might not otherwise find out until they’ve invested time in the deal (or even bound the risk). The instant tracking enabled by AI, with the right information surfaced at the right time, helps underwriting organizations stay on top of shifting portfolio goals in a way that simply hasn’t been possible for most organizations in the past.

Modern AI for underwriters can dramatically improve efficiency and performance - not by replacing them, but by empowering them to focus on the most high-value aspects of their role. AI can help underwriters find the right deals, provide the insights they need to evaluate and price risks, and enable them to stay current on appetite and goals progress. With the right insurance AI solution, underwriters get the support they need to do their best work - and underwriting organizations get more optimized portfolios, in less time.

Federato’s RiskOps platform delivers a sleek, modern underwriting experience combining a unified workflow with real-time risk data and bleeding-edge AI to proactively balance a portfolio. To learn more, get a demo today.