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Graham Ross on Outstanding Claims with the Price Writer Ep 11
30 Plays1 year ago
In this podcast episode, Jeremy interviews Graham Ross. Graham shares his journey from graduating in statistics to becoming a pricing expert and consultant. He discusses the challenges and evolution of pricing in the insurance industry, emphasizing the importance of data, analytics, and adapting to changing customer behaviours. Graham also touches on the impact of inflation, customer fairness regulations, and the need to understand customer psychology.
Don't miss this insightful discussion with a veteran in the field of insurance pricing. Tune in to gain valuable perspectives on the past, present, and future of this crucial aspect of the insurance industry.
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Transcript
Introduction of Graham Roth
00:00:00
Speaker
The next one of pricing is just your entry chips to the game. Welcome back to Outstanding Claims with The Price Writer. Today we have Graham Roth of 12 Squared fame with us. You'll tell from my big grin throughout how pleased I am to interview Graham. He is one of the greats of GI pricing who is at the vanguard of pricing analysis before most people even knew what that is. Let's hear from Graham.
00:00:28
Speaker
Hello Graham and welcome to the show. Hi Jeremy, good to see you again. It's good to see you as well, I'm so pleased to have you on. The first thing I'd like to ask you is, how did you get where you are today? Can we go back a long time Jeremy? I graduated in statistics from University College and was looking for jobs and one of my lecturers approached me as a former student from the same university. He's an actor, he's looking to recruit a statistician, so I went and talked to him and...
00:00:58
Speaker
So I ended up joining the poem Assurance, which doesn't exist anymore. But anyway, it has a sort of statistical analysis to help them with their processing and motion insurance book. I keep it short. There for about 10 years, the last three or four was heading up acting. One at the time was probably a few actuarial students, another statistician, and a couple of clerical staff.
00:01:27
Speaker
we were still in the days of a lot of manual work. I think we still are sometimes. So all that 10 years of being on-price in predominantly motion insurance, but also involved into home insurance. Because again, at that time, home insurance had been flat priced. It was just the early days of introducing some differential rating, predominantly based on geography.
Career Path and Professional Transition
00:01:51
Speaker
I then joined KPMG, you're a referral practice, initially recruited with a view to helping them create presence in postal lines pricing. But the timing didn't quite work out, because end of the 80s, early 90s, we had major storms in the UK. The Royal Sea Oil Platform Piper output blew up.
00:02:15
Speaker
There was the explosion of US liability claims around pollution, asbestos, all those things. So I found myself doing far more clean, preserving work and reinsurance type work than I'd anticipated, but still got help with experience and exposure to things I hadn't been exposed to in my personal life and career up until that point. And then,
00:02:44
Speaker
After about four years there, I was fortunate. My career has consisted of lots of fortunate things. A former colleague of mine from the Pearl Assurance was working a direct line. He rang me one evening and said, we're looking to expand. He'd recruit someone. You're just enjoying it as well. We'd done a crewing, met some of the senior people.
00:03:06
Speaker
And they offered me a job and I was keen to join them. So that was the start of 13 years there. So I was recruited to head up the statistics team. I think one of the things that
00:03:18
Speaker
perhaps talk about as we go on, is the role of statistics and analysis and insurance is broader than just pricing. Pricing's a key part of that. That's probably one of those crimes of recruiting analytical people, but certainly in a direct-to-permission, like a direct line, there was a need for
00:03:36
Speaker
desire and it's a management team to use statistics to drive the business and use data to drive the business. So all those are things that are highly organized and operate a call center efficiently or what is your client's performance was part of what I dealt with in that period. And must've been reasonably successful because management. So I was in senior management positions for the last five or six years. And then
00:04:03
Speaker
I set up on my own some time ago now, 17, 18 years ago as a freelance consultant. I felt a point where I had enough experience to do that and it gave me a bit more flexibility about my time and I know it's a cliche about work and life dance and all those things.
00:04:25
Speaker
at that time. That was working because by that time it was into my fifties. So I've had, what, 60, 70 years working as a freelance consultant. And I worked with you when I was doing an interim role at AXA. I had a few interim roles as underwriting directors or pricing directors for large and small insurers and pricing projects.
00:04:49
Speaker
And now I'm on the gradual decline. Should go into full-time retirement. It's coming soon, but it's not quite sure when. I've still got one or two clients. I do a little bit of work. So I think Nutshell was coming 45 years, which we can talk more about.
00:05:10
Speaker
What did you find the biggest challenge about going and being a consultant, so being your own boss and your own leader?
Data vs. Traditional Expertise in Underwriting
00:05:20
Speaker
I'm not sure. I felt at the time that clearly having that CV of having worked at the Red Line would be attractive to those other people.
00:05:32
Speaker
And it was also fortunate that a lot of seeing a big block from direct limer myself had moved on and I was still in touch with it. So I had a strong network. So it was really confident I could get some work. And I also was parking back a phone. I had four years of KPMG. So I knew what being a consultant was like and what it entailed as opposed to being an employee. So I think the biggest challenge was what decided
00:06:03
Speaker
what sort of work I'd do and how I would do it. Because I think it's clear if you're like I was intending to be, just for one person enterprise, there's no way you could compete with big players. I'm in the big consulting at KPMG and I don't know about the actual specialists.
00:06:24
Speaker
You must have encountered resistance to the sort of statistical root of setting crises, and I think a lot of people still encounter that now. What would you say was the kind of biggest challenges there? I think there's this tension between, and again, apologies for any underwriters I offend in the next few minutes, but I think I love you all, but
00:06:50
Speaker
Whereas this viewer denies to Ann and Coramene, which is fact-based, look at the data and decide what's going on. It gets you into a tension with people who believe and are experts and believe in things. There's almost one extreme, there's me who says, I know nothing apart from what the data tells me. You've got other guys, I'll characterize as under-artist. You think, I could be using experience as a consequence that I know these things.
00:07:21
Speaker
I think the end of the day is more about trying to get to the point where you understand their expertise and their points at you. I'll give you an example. I wasn't that close to you, but it's not that confidential. But way back in the early 90s, car manufacturers started to introduce things which we call pop-out specs, and they appealed to young drivers. This is the box that was in the Volkswagen Golf GTI.
00:07:50
Speaker
And my sister had a two litre black one actually, it went like a rough catch. So that's the classic old patch, small car and powerful. It put that together with a young person.
00:08:04
Speaker
You can imagine there's a significant risk in the insurance company there. The underwriters, from their experience, put two and two together. I said, that's an issue we need to address it before people like myself who are relying on statistics and data would have realized that. So in that story, you're alerted to that. So you start maybe based on their expertise, you do things and then you might track it and adjust for it.
00:08:35
Speaker
Whereas if you're waiting for the data, it can be too late. Yeah, absolutely. Yeah. That's why I said there's that ability to do that. The frustration is when, if you haven't done that, you start to get data and it's maybe not as bad as they thought it was going to be. It's that sort of trying to convince people to look at the data rather than rely on their judgment. Yeah.
00:09:02
Speaker
So hopefully that sort of, I haven't got an answer, there's no magic. Well, regardless of the results, there's this difference of opinion between future experts and analysts. No, that's right. There is a balance and I'm not really sure anyone's quite got that balance right. Yeah. I felt rather stuck in the middle at times, funnily enough, because I've been, I like the expert analysis and I like the knowledge and I think that's important, but I am a statistician.
00:09:32
Speaker
But sometimes I feel like the statisticians think I'm too close to the expert judgment side and the underwriters think I'm too close to the statistical side stuck in between. I think in my brief recap of my career, I've had analysts and underwriters report to me and at various times being reported to them as part of a management team.
Key Factors in Direct Line's Success
00:09:56
Speaker
And what would be kind of most interesting thing about being at direct line during its real scale up phase when it was taking over? That was the early 90s. I think there's a bit which probably reflects my bias is that what impressively when I arrived, having come from KPMG and had lots of companies who I consulted, is there was a management team. I was very clear about what they were trying to do.
00:10:28
Speaker
And back to my role and one of the reasons they recruited me, they recognize the importance of data and analysis and understanding performance of the account. Put those together. I think the other thing that helped them enormously is
00:10:49
Speaker
I think too many of the established insurers dismiss them as being, oh, there are some flashing a pan, or they're lonely, ever direct insurers, lonely, ever appeal to one small specialist niche.
00:11:07
Speaker
Also, what was going on in the pricing in that time helped to complete direct line a lot. Yeah. Because it was a time I was told a while ago about my time at KPMG was saw by the industry responding to all sorts of catastrophes without natural weather.
00:11:22
Speaker
So there was a lot of pressure in the early 90s for the big players to rebuild their profitability, restore their balance sheet. So they were looking to make progress, which created the gap and allowed DirectLine to grow and be profitable.
00:11:44
Speaker
I'll just admit, the Redline was an excellent company. That's not together. And that's probably still is, although I don't think it's a while since I worked. But at the time I worked there, it was an excellent company. I'm not going to just do that. But equally, its ability to be as successful as it was, was in the context in which it was operating in the early 90s, through to the start of this millennium, when a lot of the competition for various reasons was slow out of blocks, and then probably didn't.
00:12:14
Speaker
realize there's more to it than just like a few ads on TV. Yeah. Yeah. So it's the combination. So they did have a good environment that actually they were very good at what they did as well. It was a big, Martin Byrne was. Yeah. We closed part of the team at that point, got our act together and exploited that opportunity. Yeah. And what would you say Graham is your mission for general insurance pricing?
Mission and Vision for Pricing Strategies
00:12:45
Speaker
I'll turn that around because I'm at the end of my career. So I'll answer it as what was my mission when I joined as a young adult, rather to be young. I think that the point you'll get from some of the answers already is I was driven by a fact. This should be a sort of fact-based approach. That was always there. Use the data to understand the risks and therefore how you price.
00:13:11
Speaker
As I got more experience, I think I then realized it had to be a process, not a sort of a little one-off project to build in some fancy model. It's about process. I think that came more and more apparent when I was at some direct line, because there I inherited things when I joined, but part of where myself and the team I'd there tucked in was getting a process that worked.
00:13:44
Speaker
So is that I'll give us a process not a project.
00:13:49
Speaker
Okay. Fact-based driven by data. At the point I made a while ago, sometimes you recognize the expertise of underwriters or claims managers who can point you in the direction of what to look for in the data or things that might not be apparent in the data that you might want to take a judgment of and then respond to as you can.
00:14:10
Speaker
I think the other thing I, for me personally, is it has to be a replicable process. And I think where that got me into discussions with Operation Star is around that replicable thing meant
00:14:25
Speaker
I was always saying, let's drive out referrals. For some reason, you can't provide a query of the system. However, it's implemented and you have to have somebody come in and make a judgment because everything I've seen is that judgment adds more variability.
00:14:45
Speaker
Yeah, because I'm, again, coming back to my statistical training, one of the things that comes to me is the post degrees, and that is around the whole thing around quality management, top quality management, which is quite trendy in the 90s, much still in the labour.
00:15:03
Speaker
And that was at the heart of the hydrogen money idea in the controller process by driving our ability. So that got me a lot in terms of how I thought about pricing as a process. And sources of variability are things like referrals where you got each underwriter and may come up with a different decision. I was always very resistant to the idea that you could call center agents or other people the ability to negotiate the customers.
00:15:30
Speaker
Yeah. Again, it introduces additional variability. I mean, operational people and market people had a different view. It's been one of the discussions we had that informed my, if you looked at what my mission was, it was to drive variability out of the pricing decision. Yeah. That is excellent. In terms of different risks justify a different price. It's more for this customer, they will get that price.
00:15:59
Speaker
Yeah, I understand. So it's understanding the customer's attributes and getting a consistent price and a consistent decision when that happens. The other thing in terms of admission or other is that we're the better's process, but it's not a static process. We're effectively in an arms race.
00:16:21
Speaker
Yeah, when I was, again, I don't want to go into the whole story, but when I started, I said, we sell some extra horseshoes. We're actually no-cacuted power, so lots of clerical manual stuff and desk calculus. A handful of raising factors, and we never made any money, okay? We tried as a couple of things we'll talk about. Today, huge amount of cacuted power,
00:16:48
Speaker
I know insurers employ huge numbers of analysts, actuaries, all sorts of things. And they have much larger and more complicated data structures and pricing models, external data coming in to support. They still don't make any money. So that's- No, it's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true. It's true.
00:17:16
Speaker
So now I think being excellent at pricing is just your entry chips to the game. If you can't do that, then don't enter the game. I think then that's what you like.
00:17:31
Speaker
What my experience always is talking with, that's just a necessary, but not sufficient route to profitability. You still have to have some point of difference, some competitive voltage to achieve a chance to return better than market average. That's right. You need something that customers care about. He can't do it in isolation. You've got to try and understand your competitors and the market, especially which you're operating.
00:18:02
Speaker
And lead to that, you get into questions like balance of power. If you think it would, again, you probably expect, as given my pedigree is very much direct insurance, because most of the clients I've worked with as a consultant in the last 15 or so years of being in the direct space, is of the balance of the talent, that's between the underwriter, and whether it's Brokaw or the intermediary, between the customer, or how much power it's company got.
00:18:34
Speaker
My view at the moment is in the last 10 or so years, the balance of power has shifted to four or five big aggregators. Graham, what would you see as your vision for the future of insurance pricing?
Future Challenges in Insurance Pricing
00:18:51
Speaker
I said I'm on my way out, so that's not really something I've thought a great deal about.
00:18:58
Speaker
What I think I will do is turn it round and say, yeah, I'm coming to the end of my career, but I hope there's people listening to them at the start of their career. And they're probably saying, what's the whole plan on that? In terms of the challenges that can have been met over the next few years for people involved in pricing and journalists. When we talk about it, we tend to think about it because that's where the other two most of the effort is because that's the most competitive, the most complex in terms of understanding risks in personal life states.
00:19:28
Speaker
I think there's one immediate thing, which comes back to when I started my career, is how do you price in a period of high and uncertain inflection? Now, if anyone's evolved right now, it can take years for personal injury claims to be resolved. And I'll say, they're settled at the, if you like, the prevailing cost of living, or they're planning to price it. So how do you set a price today for when a margin of £10 up is $7.4 billion?
00:19:58
Speaker
And that, I think, can make a big difference. How do you set about solving that? I'm not sure you can solve it. You can just come up with your best judgment. That's probably, it doesn't much impact, probably more impact on the prices you set. And then those last few tweaks, as you look at the sort of three way direction between something at the corner of your pricing table. Yeah, definitely. And so that sort of, how do you do that?
00:20:24
Speaker
get plugged into the data that's available to help you understand how inflation might unfold in the coming years and what that could mean to you in terms of price.
00:20:35
Speaker
I suppose on the other side of it, and there's always the argument that you've got a bit of hedging to do with your investment portfolio. It's a business. All the planes reserve your hold. It should give you some hedging calculation, but it's not perfect. That issue is immediate. I think this point I made about the arms race, that's going to carry on.
00:21:00
Speaker
I'll admit, ignorance of the analytical methods underlying artificial intelligence and the shoot of landing, but it feels like they, if they haven't already, they're coming into the way people try not build price and orders. That was recent career. Being a bit of a traditional tool, this takes a long time. I do get concerned.
00:21:26
Speaker
At the end of the day, I want some of these models you'll probably just, if you like, wobbly, random noise. With me, in terms of all this sophistication and pricing while you can build and the huge number of factors you've got available to understand the risks, I'd still haven't resolved it. How and where do you draw a line between
00:21:51
Speaker
get me into more and more detail and then recognize. And actually a lot of that detail is, as I'll describe it, just your modeling noise. Yeah. There's a lot of evidence too. And at that hotel, if you look at the huge differences in prices and Shorra's chart, and it's not consistent. It's not as if wine shoes consistently wore a stood system. It suggests that there's some of that already there. Noise in the models they're going to reflect. So I think there's a challenge there of
00:22:20
Speaker
how to use all this technology, but ready to stop. I think the other thing that I'm thinking through, this sort of customer duty has just been introduced, hasn't it?
Transparency and Equitable Pricing
00:22:32
Speaker
Yes. The role was old from treating customer fairies. You'd go back a few years, you'd got the gender directive, some layers, you'd best restricted your ability to differentiate by gender. You got the stuff that's coming recently around new business and real pricing.
00:22:50
Speaker
So I suspect pricing in the future, in total lines, will face more of those sorts of pressures. I don't think so, Ting. Well, the society government, these sort of transparent and equitable. That's built into the customer duty thing, isn't it, about, you know, prove you're producing good value or fair value? You need to prove a link between the price and the cost to the manufacturer.
00:23:20
Speaker
How do you reconcile all that? Because in terms of when I involved in more detail practice in that wasn't the constraint. They were constraints on pricing, but not to the extent you have today. External agencies limiting what we can't do or insisting on the degree of transparency. That was a challenge. I think the other point, because this was a big burn stop to me during my career.
Customer Psychology in Pricing
00:23:46
Speaker
Okay, you'll gather this stats and maths. I'm probably very rational. This I've never really understood until recently, this sort of customer behavior, getting to the psychology of it, how they respond to the different ways you present privacy, product features to them.
00:24:12
Speaker
No, this feels like from pricing analysts, this Hollywood mistake of as well as analyzing all of the risk data to understand the relative performance claims. Have you invested enough time in understanding
00:24:27
Speaker
our customers react to different ways we position the proposition in front of them. And I know people explore whether you include this add-on or prices set for the default, things like that, and how you pitch successes. But it feels like this, if you looked at the balance of effort, huge amount of effort into understanding risk prices doesn't seem to be the same or proportional.
00:24:55
Speaker
effort, suddenly, in my experience, now I'm a little bit out of date into this sort of using the same ideas to understand customer behavior and psychology and dynamics of it, having the best properties for your price in front of it. I think that's right. I think there is a lot more to do there. Because I think by then, if you don't want to reference a bit of the story about that, which is probably more about if you change the proposition, you change customer's behavior.
00:25:23
Speaker
Yeah, no, no clothes owners protections now well established, but way back in the early eighties, when it was first introduced project, I worked on was trying to work out, we can mark it's moving that way. We've got to introduce it had we promised it. So I approached it and reported here. The customer's got five years, no clones. Yeah. Look at the kind of different parts. They could take the next five, six years, next year, they may or may not have a claim to like a random walk.
00:25:53
Speaker
Yeah, that's right. And you can look at whether or not it's five years. This is roughly the average price we collect. So we need to work back and say, if we can protect the no claims, we need to collect the same average price. All right, brilliant piece of analysis. You didn't realize, you should have done, perhaps, if you change the rules, companies took it out. Yeah. I think the industry learned that if you now pretend there are no claims, companies are more likely to put in smaller claims.
00:26:23
Speaker
Yeah. Yeah. That's right. I've never, I think excess is an area where we rather struggle. If we move the compulsory excesses, the customers tend to then behave differently. Isn't that an interesting one? Again, I only recently thought about, Bob, this is more about voluntary excesses.
00:26:53
Speaker
And again, it's probably dominated by my thinking on mobile, but it applies to other products as well. If you put a voluntary accessory, it probably becomes like, well, the price associated with the case.
00:27:06
Speaker
Whether they accept the price or not tells you something about their attitude to risk, their view of how likely they are to claim it. And you end up, again, this was something in my early career, and I'm looking at introducing higher accesses or changing discounts. And it was a good approach for quite a bit of the distribution of plans. If you chop it off here, you've lost this much. You think that was saying it was 3% of the claims. It inevitably seemed to save you more.
00:27:36
Speaker
Yeah, because the people who took that offer were so selecting to be the ones who felt they were safe. Yeah, that's right. That's right. Yeah. So if I don't even know I'm driven by analytics, I'd say I'd like to start off that place. The one that I particularly appreciate enough about the onion career is if you change the rules, customers change their behavior. Yeah. And it's difficult tomorrow sometimes.
00:28:04
Speaker
Yeah, definitely. Yeah. The very fact that somebody is changing their access shows they're a certain type of person who already knows probably more about insurance than the average. Or view of their risk or their own risk. Yeah. Yeah. Anything else? What was the question again? So how about a condition for the future, which I'm denying I've got one, which has some challenges and things that I think will be, well, I think we ticked them off really.
00:28:33
Speaker
Is there anything you'd like to add? I suppose, I started off by saying I stumbled into this, effectively got a message through my former lecturer saying, Ken, tell us from this guy, I could see to look into the criminal statistician. And I chose to go there because in Gene Central London, Haven is not waging arrest. But I have enjoyed my careers, you know, sort of pricing analysts and
00:29:02
Speaker
spent a few time, a few years in big and bold as a more of a general manager and director. It has been fun. It's been challenging. And I still think it's released things on challenge. I think still for people who are interested in statistics and analysis, I'm actually translating that into action. This is a space to be.
00:29:29
Speaker
But that's an interesting point.
Advice for Aspiring Analysts
00:29:31
Speaker
What would you say is the thing that people should be learning? If they wanted a career that's fulfilling like yours that reached a senior level, gave them a lot of fulfillment, what should they be learning and doing? You do ask some difficult questions. Good. You ask my own experience and my own character. I think
00:29:56
Speaker
Well, if you're an analyst, whatever you call yourself, post-naturally, that's an analyst. I was called a statistician and that seems to fall out. But I'm sorry, back to the point is you've got to try and understand probably your clients' interests, whether you're a client manager or senior manager or you're a consultant. And as one of those listeners to what they are cheap to do,
00:30:25
Speaker
Think about the problem they're trying to solve. And maybe you've got, think about how you can help them address that beyond perhaps the narrow limit you're giving them. Again, it's a bit caricature. Often as a, Dickie is a junior price analyst, she'll get asked by somebody, kind of gives me a table or a graph that shows me how conversion rate varies by age of customers.
00:30:51
Speaker
If you understand business and that thematic, why is he asking you that, or she's asking you that, what they, and you can anticipate that and not do the bits of analysis, get you beyond it, fixing a table incident. Okay. It's pretty clear that this statement has been, and therefore I think we should tune it to a bit more. So it's almost, yeah.
00:31:16
Speaker
Just try and understand the real question you've been asked, which means that I don't understand the business in the context. Come back to the sort of things I talked about in one equation. You understand how you've come to your point of view trying to be successful. Market context, it's easier to answer those questions. So maybe, yeah. So I don't want to stand up.
00:31:38
Speaker
But there's a bit when you've got an analyst, take your blinkers off and then stop looking at what's next and just try and understand the environment in which your business is operating. Yeah, not just the focus, not just in the detail, but actually thinking about the bigger picture as well. And how, I think one of those things I've felt when I was working, and this is a challenge I had when I was a thousand clients working
00:32:07
Speaker
people younger is, I often had this point saying, we were conformed from the call center tomorrow morning. What prices are we going to charge? So, the same as we did today, we're at a better weekend.
00:32:25
Speaker
Yeah, that was the kind of mindset I got to it. So, well, back to again, sort of, some of the next few people. Telling me you're going to run a six month project to collect all this data and analyze it is fine, but is there something I could do better tomorrow prior to going to the Oakland shop?
00:32:46
Speaker
Yeah. I'm, I'm going to borrow that actually. That's very good. Cause I think this is again, I'm not claiming any great insights here cause it's a bit of a cliche, but too often the pick brawl or so, what's the expression? But basically it's good is the enemy of perfect. I think that's, yeah. Yeah. We can't do that. Cause it's not perfect, but I would say no, it's better than what we're doing today. Yeah.
00:33:16
Speaker
And that's a way to try and think. Maybe a challenge again for analysts, for people. There's a danger you can stop into trying to come up with a kind of big privacy structure, which I doubt exists. But you're trying, you're trying to get close to it. And if you can come up with structures that you see and get you closer, how do you implement that learn from it? It's all right. So again, get yourself into a mindset. This is an intricate process. Yeah.
00:33:45
Speaker
That's it. What effect today won't be perfect tomorrow anyway. So it's always got to be. As you prove it back into this art choice mentality. Absolutely. Absolutely. I need to prove when you try something. Gran, thank you ever so much for your time today. It's been absolutely brilliant hearing from you. Thank you, Jeremy. Thank you very much. You have a good rest of your day. Thank you. Thank you. Bye. Bye bye.