With events going virtual in 2020, we’ve had the opportunity to attend and participate in conferences across the globe at the touch of a button – hearing from colleagues from various international markets about challenges they face in today’s world.
We’re excited to do just that at this year’s Underwriting Innovation Europe conference, taking place in June, where senior underwriters will come together to discuss how to accelerate underwriting profitability in a world of changing risks.
This is such an important topic for insurers across the globe in today’s hardening market – and it’s something we previously discussed on a panel at Underwriting Innovation USA, alongside experts from Prudential International and Liberty Mutual Insurance.
Here, we share key takeaways from that panel, with insights across large commercial, mid-market and life/health insurance.
We are facing a huge productivity challenge in insurance, and in commercial underwriting there are two main challenges to consider. We kicked off the panel delving into these in detail.
Firstly, there’s the macro challenge of ensuring the right items of work are allocated to the right underwriter. That’s particularly challenging when thinking about new business, and the value of opportunities through the door vary widely. Success here is all about orchestrating work across the business in the right way, allocating the most valuable work to the right underwriters and eliminating the need for them to work on out of appetite submissions.
Then there’s the micro challenge: When a risk lands on an underwriter’s desk, how do they most efficiently and effectively write that piece of business?
Historically insurers have focused on addressing the micro challenge, making risk analysis more effective, but still within an inefficient end-to-end process. Without addressing the macro challenge it is like having a sprinter run the middle 100m of a marathon. The overall impact is not worthwhile. This is one of the main reasons many digital transformation initiatives in insurance have failed. Now, insurers are realising that unless they address the macro challenge, they cannot drive productivity-led growth.
Delving specifically into how these challenges affect the commercial mid-market, where business is heavily broker intermediated, the biggest issue in the macro challenge is to make automated decisions on a risk profile that typically comes in an email or as an attachment. In today’s hardening market, underwriters have been flooded with out-of-appetite submissions – up to 60% in some cases – so this is more important than ever.
In the absence of a simple way to do this today, you frequently see underwriters working on a ‘first in first out’ approach, going through broker emails one after another. Given the wide ranging value of the risks coming in, that’s not the most effective approach.
Another ramification of this ‘triage’ challenge is that a submission often bounces through a number of different teams before it finds the right one.
So where does the opportunity lie here?
Well, it’s about building a digital risk profile that enables automated decision making as soon as possible in the process. But so far, most organisations have tried to automatically extract every detail from a submission, which has proved problematic. Instead, the opportunity lies in extracting key indicators of risk – like company name – then using external data to create a profile of the risk itself. This helps you understand the value of the risk and who should be dealing with it, without the complexity of extracting every detail from any number of submission formats.
This is actually one of the key problems we solve at Cytora. We help insurers to route attractive submissions to the most appropriate underwriter, in real time, first time. By digitally streaming risks across the business, insurers can see a positive impact on broker response times, quote to bind ratio, and operational costs.
Sandeep Haridas, VP & Manager, Underwriting Strategy & Excellence, Liberty Mutual Insurance, echoed this for the large commercial market. He told us that the team still receives a surprising amount of unsolicited opportunities, so it’s vital to cull things quickly that aren’t within appetite.
Echoing the issues around triage, Sandeep explained that getting a risk to the right underwriter is challenging – but then the question arises as to where it should sit on the pile. Should this submission be top of the pile, or perhaps somewhere in the middle?
To date, some organisations have benchmarked priority on likelihood of winning the business. But more and more, insurers are looking at the quality of the opportunity itself. Then when it comes to the triage process, he believes there are three models to consider.
While all three models have their merit, getting the right opportunity to the right underwriter means everyone has a much better chance of winning – the insured, the broker and the carrier.
John Di Federico, VP Underwriting, Prudential International, took a step back to explain the incremental steps in digitising life/health over the past decade. As paper applications went digital, insurers were able to collect data and digest it – gleaning far more value than ever.
The impact on straight through processing (STP) came as reflexive questions came into play, moving from static applications and increasing STP by 10 or 20 percent as a result. Once insurers threw big data, predictive analytics and machine learning into the mix, John notes that they’ve seen STP at 60 or 70 percent.
This applies similarly in mid-market commercial, but we’re still seeing a high rate of cases that need to go to an underwriter. And for these underwriters, the moment they start working on a submission they have to go to twenty or more data sources to characterise the risk.
This is the case for new business, and we can tell the same story for renewals too. Underwriters just have a snapshot of the risk which might be a year old or more. They need to start building an up to date risk profile, going to those 20 websites again to see if exposure has changed.
Nowadays, insurers can easily pull in external data automatically, building connectors so that when a risk lands on an underwriter’s desk or comes up for renewal, all of the necessary information is available to them digitally.
According to Sandeep, there is a misconception that in large commercial deals, underwriters have a lot of time to figure things out, do a good job of risk assessment and pricing for a complex piece of business. But it doesn’t always work out that way.
Imagine you are underwriting three or four lines of a conglomerate, operating in 19 countries. Where do you begin? Well, if you start with what the broker sent you, you could only be 40 percent of the way there with the detail required to make the next set of decisions.
Sandeep outlined three key areas of automation that can help here, and how they’re helping his team in large, complex risks.
Firstly is extracting data from a submission, and there are lots of solutions to support with that today. Secondly, the insights from that information are really important, having AI to help with the interpretation of the data.
Thirdly, you need to understand what you can do once you have the information and the interpretation. It’s not just pricing – that comes last. It’s also about matching those requirements to the right products. At Liberty Mutual, there are over 400 products just in the Global Risk Solutions space in North America, for example, and these insights can help greatly in aligning a piece of business with the right product.
For Sandeep, the last aspect of this is the intelligence gleaned by the underwriter from conversations with the broker. The tone, the voice, how excited the broker is about the account, how it’s been presented to the carrier to work on, etc. All of that is key to the underwriter role.
Ideally, underwriters should be focused at this “level four” space, but Sandeep notes that they’re usually still playing at level one. If you can automate level one, you can remove the need for underwriters to get bogged down with that. Then automate level two, and take them out of that too. Then they can focus their attention on level three and level four – i.e matching requirements to products, interpreting intelligence from broker conversations, and underwriting effectively – which is where they should be.
We wrapped up the discussion with a moment on insurtech partnerships. I’ve been on both sides of the fence; as former COO at Hiscox leading an innovation team I spent time working with plenty of insurtechs.
In my view, a partnership works well in two ways. Either, when an insurer wants to solve a very specific problem, the technology company must show that they have the solution to that well-defined problem. But more often we see a second model, which is a more strategic insurer and insurtech partnership, with both parties working together to solve a broader more strategic challenge.
What was clear from our discussion was that technology is having a tangible impact today. Gone are the days of innovation theatre and promises of digital transformation by short-lived insurtechs – in the here and now, technology is helping insurers to differentiate, to develop the best solutions and offer the best customer service for brokers and the insured alike.Many thanks to all of the participants in this session, along with our moderator Paul Carroll. To listen to the talk in full, check out the Underwriting Innovation USA website here.
