Juan de Castro: Welcome all to the last episode of Season 3 of Making Risk Flow. In this season I had the pleasure of talking to 15 incredible executives from around the insurance industry; from brokers, to insurers, to advisors. And they work on very different segments of the market, from SMEs all the way through to a large commercial. And we’ve touched on a very wide variety of topics, from how to drive profitable growth, how to deliver better broker service, how to drive superior risk selection, or how to think about underwriting talent. But there are three common challenges across the industry that are constant across all of these broad ranges of discussions. The first one is around efficiency and how manual processes result in inefficient workflows impacting productivity and broker service. The second one is about effectiveness and how poor underwriting data impacts the ability to drive consistent risk selection. And the third one is about continuous performance improvements and the fact that the lack of visibility over the frontline activity hinders their ability to identify improvement opportunities. And every guest agreed that these challenges are preventing the industry from being as efficient as it should be. To make insurance relevant again, we need to rethink how carriers can onboard risks at close to zero marginal cost, control the target portfolio shape, and provide lightning-fast service to brokers. Thankfully, in Season 3, guests have also shared their views on how to address these challenges, and they can be boiled down to four categories of intervention. The first one is about removing unnecessary work to drive productivity. The second one is how to reduce the effort required to underwrite those risks that they want to hold. The third one is about how to maximise conversion for those risks they want to hold. And the last one is about how to do all this, ensuring that you’re picking the right risks. I have compiled a series of snippets from different episodes to bring all of this to life. Hope you enjoy it. The first category of intervention I mentioned was removing unnecessary work and focusing underwriters on the most attractive risks. In Episode 10 of this season, Neil Peters from Arch and Arvind Drubhra from HDI talk about how to ensure underwriting capacity is deployed on the most valuable risks. In the following snippet, they discuss how to prioritise risks to identify the best risks to underwrite, and how to balance risk quality and propensity to bind considerations.
Arvind Drubhra: I fully agree, because when you look at the prioritisation there’s going to be various criteria and every company is going to have their own criteria around what would be considered as part of that prioritisation rule set. So things like treaty exclusions, for example, right? You’ve got certain CAT appetites, so every company is going to have their own rule set, and the power comes from using the correct tooling to actually automatically filter out things that you know are not really applicable in your business, then start focusing on the ones that are relevant. So that to me is what the power comes from, because otherwise, we have underwriters today who say, I’ve got things coming in, but I can’t quote that because that automatically goes against what my treaty allows.
Juan de Castro: Any thoughts on that, Neil?
Neil Peters: Amongst those multi-site brokers you’ll have different quality relationships, inevitably, because, despite all the talk of technology, this is still a relationship-based business. And we might have a fantastic relationship and be able to get rate conversion with one set of people, poorer conversion and less likelihood to win from another set of people who work for the same organisation, and that’s not always clear. Whereas if you get your data analytics right and if you get that, how the submission is absorbed and chunked and then put in front of the underwriter, you can warn them. Now it’s quite interesting because underwriters are very good at convincing you that they are going to pay something with you because they want a quote. So we’ve had various conversations where we’ve gone back to a component of the data and said, well actually you’re not winning from this guy, or this girl. You think you are, but you’re not because they’re really good at making you feel good about quoting to them but you never actually win anything. So it starts to challenge some of the norms and some of the perceptions of what is good, what is not, who is good, who is less supportive, and it really refines your thinking and clarifies it as well. There have genuinely been some surprises that people find, I thought our conversion would be really good with it. No, it’s not. And you are kissing a lot of frogs, not to find many fruits.
Juan de Castro: Also, in the first episode of the season, Philippe Lutgen from Howden talked about the challenges with the back and forth between brokers and insurers and the challenges it poses.
Philippe Lutgen: Absolutely. The cleaner the upfront data is on the risks, the less back and forth you’re going to have. And that brings me back to my days in AXA XL where we had a big global program business, we used to underwrite global programs with policies issued in multiple territories. So when you write on the incoming side of those policies, we had a risk in Bhutan for a very large client, it was a $2500 local policy which cost $15,000 just to actually put in place because the data wasn’t clean, the instruction to the local fronting company wasn’t clear, so there was a constant back and forth. Which currency do we have to do this in? Is it in Indian Rupee? Because Bhutan uses Indian rupees. Was it in US dollars? And you spend a huge amount of time and money to see something which in itself doesn’t bring you that revenue. So if you have the data clean up front, if the producing office, broker, underwriter have very clear instructions, it’s a data set that goes to the incoming fronting companies, then it’s easier to issue a policy. But if you don’t get it right, it’s going to be a lot of back-and-forth emails and very inefficient.
Juan de Castro: The second category of intervention was reducing the effort required to underwrite a given risk. In the second episode, Paolo Cuomo from Gallagher Re talked about how to optimise the sharing of data across the value chain to drive efficiency.
Paolo Cuomo: Yeah, I almost go back even a stage further in the value chain to answer your question, and that is, how does one make sure the primary insurer has the optimal data? And there was a great little Insurtech in Lloyd’s Lab a few years back called Layr, who I think were based out of Atlanta. And what Layr were doing is they were working with small companies to actually link into their HR system, their finance system, their procurement systems, to understand what was going on in the company and therefore to make sure the right coverage was in place. And this, to my mind, was a great example of where you can ensure that the underwriter knows everything they need to know about the company they’re underwriting. Now, as you get to larger organisations and more complicated covers, you find that the data that the underwriter would like to have from their client isn’t always available, maybe in the format they want or in a timely manner, and so you’ve already got a challenge at that point. And then as you move further up the value chain towards the reinsurer, if the primary carrier is struggling to have the data he or she may want, then clearly there are going to be gaps as you go further up the value chain.
Juan de Castro: But there are always new angles of risk analysis and how insurers incorporate new data in the risk selection process. And the best example is ESG. In the fifth episode of this series, Paul McCarney from Moody’s and Simon Tighe from Chaucer explain the process they are making in this regard.
Paul McCarney: At the end of the day, a lot of the data, even the data we’ve got, is still maturing. There’s still more disclosures needed to improve on this. So being able to engage their clients, explain how they’re being assessed, and then see how that can encourage more disclosures I think is something that the wider market seems to be quite bought into. So I think clients of ours at the moment, and ones we’re talking to, really see this as going way beyond the box ticking. This is about getting the data and getting the workflows such so that that data is turning into the analytics that people need to kind of consider ESG as part of the decision making. That I think, over the last twelve months, is really something that’s come through in the marketplace.
Simon Tighe: The point Paul made there about the data maturing is very important. I think we’re very keen to point out that this is not perfect, right? What we’ve done is not the final answer. This is not the end game, this is not the end result. We want the market to come together to keep building this to get to the end game. This is our starter for ten, right? And a bit of a shameless plug here, we’ve just updated our sustainability report which is on our website, and in there we actually disclose every single data point that we think is important. We want this to be open to everybody. We want people to understand what it is we’re trying to do and why. And we want people to join us on it. Because without standardisation, this thing will die, right? So without participation across the full value chain of insurance, right, we’re talking about clients, we’re talking about insurers, we’re talking about reinsurers, brokers, service providers, everybody, without their buy-in, this thing dies. And we all know ESG is a problem that we have to work towards and we all need to work together to do it.
Juan de Castro: Often we think that the London market is the last one to adopt new ways of transacting risk. So it was particularly interesting in the eighth episode of the season to hear from Sheila Cameron on the progress the London Market Association is making.
Sheila Cameron: So we have just launched CDR and MRC. So the things that I tell people, what can you be doing now? As for brokers, brokers are the ones who create the contracts. So one of the things is, very often today, those are just created in Word. Okay, here’s your new contract, here’s your new Word template. Adopt your template, put the template into your systems and start using it. So we have set a target of that, by the end of September this year, all brokers need to start producing client documentation in this standard. So typically in the London Market there’s about a three-month run-up phase, so we want to ensure, keeping in mind the 80/20 rule, that the vast majority of contracts created with a 1/1 renewal date next year are created in this template. So number one, brokers please get the MRC template into your systems and start creating contracts in that way. Number two, adopt the GRLC standard, make sure your data is in this standard. And number three, start working out what your API strategy is going to be. Let’s start thinking about where the majority of your business comes from. Are you going to build separate individual APIs into every broker that you deal with? Are you going to push everybody through your third party trading platform of choice? For example, White Space or PPL? How are you going to do this? Who are you going to connect with in order to make this work?
Juan de Castro: The third category mentioned of intervention is maximising the effectiveness for the risks you want to bind. In the third episode of this season, Jonathon Gray from Allianz talked about how quote turnaround time is a key lever for quote conversion and how Allianz is using submission prioritisation to optimise the turnaround time for the highest quality risks.
Jonathon Gray: To a certain extent, yeah, I think it’s difficult, and you’ve got to be careful around just throwing loads of risks at an underwriter within 30 minutes of it coming, underwriters just won’t be able to cope. And I think it’s key that you prioritise and help an underwriter as much as possible. So one thing we focus on here is making sure that we do an element of prioritisation so when it lands in an underwriter’s workflow, they’ve got a good sense around what’s a good risk? Is it a trade we like? Is it a broker we do well with? What kind of locations is it based in? So I think it would be very unfair of us just to throw hundreds of cases at our underwriters very quickly. You’ve got to give them the tools and the ability to take those prioritised risks, further add their knowledge, and then be able to trade on the front foot, use their experience really to make sure that the business is brought home.
Juan de Castro: The last category of interventions I mentioned is about driving consistent and granular risk selection. In Episode 7 of this season Mandy Hunt from RSA gave some brilliant examples about this.
Mandy Hunt: So I guess in the worst case scenario, you’ve got somebody that says you can write offices, and I mean concrete or brick built buildings that are very purpose built versus writing an office above a chip shop. And of course they present very different risks, not necessarily because the office work is any more hazardous, but the processes that are going on around it. And that is going to be true across every trade that you can think of. There will be some risks that are acceptable and there’ll be some that are not for any insurer. And what we want to avoid are the cases that could hurt us, that we’ve taken on by mistake, or we didn’t understand, or there was a bit of extra information that if we’d known we wouldn’t have done. So, for us, I would like our underwriters to not have so much responsibility to make sure they’ve covered every point. Are there some data points that go, if these things are true, then this is a risk we can quote, and it not be so reliant on trawling through Google, trying to find pictures, sending surveyors out. Because ultimately when you define, as an insurer, your risk appetite, you want the business to sit within it. And my guess is occasionally some of the losses that impact insurers are those that are not quite within the risk appetite, or they’ve moved outside of the risk appetite because something has changed in the risk and we need ways of being able to spot those things too. If RSA suddenly decided tomorrow to sell insurance but also make cars, we would understand that would be a different risk profile. However, a small SME who currently makes curtains, who then realises they’re quite good at making furniture and suddenly does the two together changes the risk dynamic from something we’re comfortable with maybe to something we’re not because of the process and the fire hazard, but probably isn’t thinking an insurer is going to be worried by those things, just thinks that’s just how businesses are. So where we can have tools that enable us to see and spot those things, we bring far more consistency to the decisions we make. That means that on a personal level, an underwriter is not struggling with some of those things where maybe there’s a loss and everyone’s saying, well, why did we write that? How come we ended up with that in our books? The rules would help us avoid those kinds of situations.
Juan de Castro: So these were some of the snippets from different episodes around those four areas of intervention. But in this season of Making Risk Flow, we also talked about the role of technology and underwriters. Is technology replacing underwriters? What is the role of each? We touched on both of these in two different episodes, in the fourth episode with Matthew Grant from InsTech, and the twelfth episode with Nathália Bellizia from BCG.
Matthew Grant: I mean, in theory, you could have a fully AI enabled underwriting operation. But the reality is, unless the data itself is completely reliable and integrated into your clients business, then you’re going to get big gaps and big holes in what you’re trying to analyse. It’s that comprehensive way to be able to collect data that’s actually quite difficult to get in a commercial setting. Buildings are complicated, activities are complicated. So I think, certainly in my lifetime, I wouldn’t worry if I was at this stage of my life as an underwriter that I was going to be displaced by some technology.
Nathália Bellizia: Yeah, I know, I like your second school of thought. I should also say that I do think in the short term, it’s not about the technology replacing the individual, I think it’s the individual using the technology will be so much more productive than the individual not using the technology. So that will be the power as opposed to replacing them completely. And really maybe because the parts of the job that are less enjoyable will be potentially automated or made more efficient, what if we actually make the industry attract a lot more talent? Overall, it can be great, right? And so I like to believe in the glass half full perspective more than the other one.
Juan de Castro: But it’s not all about technology. In the ninth episode, Paul Brand from Convex gave us a brilliant summary of the importance of culture in driving superior performance in the market.
Paul Brand: Insurance, it’s about having bumps, isn’t it? That’s what our clients are paying us for. They give us money to transfer risks on the world balance sheets and then bad things happen in the world and we go, right, we’ll pay for that. Well, if every time that happens, yeah, leadership runs around going, I didn’t know we were gonna have losses, it gets a bit nuts, doesn’t it? There’s then a really interesting choice that companies make as to whether they’re fundamentally going to be driven by permissions, so before you do anything, you have to ask permission to do it, or whether you’re gonna be run by constraints, which is, you don’t have to ask anything unless you’ve been explicitly told there’s a constraint on it. So as I think about how we’ve set up our underwriting units, they’re very driven with that constraint model. So people have got the right to essentially drive a lot of the outcomes for themselves and I just think that gives a real sense of belonging to the work that you’re doing.
Juan de Castro: And last but not least, on the eleventh episode, Paul Mang from Guidewire brought it all together, explaining how only through technology, data, and analytics, the insurance industry can maintain its relevance and play a pivotal role in the advancement of society as a whole.
Paul Mang: I think about it in two, kind of, general categories. One is around efficiency. The protection gap largely has to do with the price of covering exposure. The biggest competition any of us face in this industry, really, is not necessarily incumbents competing with other incumbents. I think the biggest competitive issue facing anyone who participates in this industry is non-consumption. In fact, there’s more business not being written. And so it’s very hard to take away business from a competitor. If you think about the alternative, which is your key competitor is that potential insurers are self-insuring, they’re either retaining it because of higher retention, or in fact, they are becoming their own insurer by applying their own balance sheet against volatility. So that’s one thing, analytics could help improve efficiency. Efficiency, well, it should drive down costs.
Juan de Castro: Well that is all. Hope you have enjoyed this overview of Season 3 of Making Risk Flow. I hope you have a fantastic summer and join me in September for Season 4 of the podcast.
