Couldn’t find a thread on this specifically. I recently attended ICA 2023 and there were a few presentations on Insurtech. Apparently some traditional insurers are funding some of the new companies.
It’s not something I know a lot about, but certainly something to keep an eye on. I received a news release today that Trupanion and Lemonade are some of the most shorted stocks in the finance sector. Trupanion has dropped 50% this year but interestingly, Lemonade has gained 40%.
Boss sent me this just yesterday:
Technology Was Supposed to Transform Insurance Pricing. It Hasn’t. - WSJ.pdf (140.3 KB)
Insuretech is mostly around:
Using less people (labour costs) combined with technology (AI) and automation to achieve better operational efficiency.
Thats kind of what it boils down to.
Eh, I find insurtech seems to be people thinking:
And I say that as someone who would likely be characterized as working in insurtech.
I used to think that but they listed a number of examples of well-known traditional insurers that started their own or acquired Insurtech companies.
Swiss Re → IptiQ
Parent guarantee covers reserve volatility, capital requirements (doesn’t have to be conservative so leaner coverage), and reinsurance (no extra premium given away).
So this allows the smaller insuretech to be much smaller and automated, which is then used via digital sales channels (B2B or B2C).
I see it mostly as a way to reduce operational costs while maintaining premiums.
Yeah, its soooo hot right now. But nobodys really hitting it.
Munich re was doing something all hot and bothered in insuretech on the life side recently. I went and had a look recently, and they shut down everything before they even launched.
Not saying its not possible or we wont get there but generally im sceptical still.
I’m not up on the P&C filing world, but would there really be a reason the Insurtechs could file rate changes faster? Don’t they have to go through the same process as the carriers?
100%
The problem with insurtech is they see lots of cool ways to better predict risk, but the reason the incumbents aren’t doing that on PL is because of regulatory restrictions.
Come challenge us on the commercial side, but sadly you can’t just brute force your way to a pricing model because the risks are far more heterogeneous.
Yeah that’s just consulting speak.
As far as I’ve heard, the process of rate setting (for some companies) takes like 6 months just to re-code the models or whatever. Insurtechs do that faster.
Also sceptical.
Consumers: We want to buy online!
Also consumer: won’t actually buy online.
I think most people would find it unbelievable how few consumers are willing to buy insurance 100% online without speaking to someone. I think it’s a lot in P&C, and it’s at almost 100% on the life side - no exaggeration. I’ve seen this repeatedly, again and again, from a variety of different viewpoints (like, insurtech’s saying stuff like ‘gee, we’re suprised about how high touch everything is’).
And on the life side, you can maybe push some 30yo’s to buy online, but the business is low premium and really really bad news in terms of policy’s taken and retention. I’ve heard numbers like only 40% of applicants take life insurance policies bought online, and I’ve no idea how many of those cancel in the first couple of years but I bet it’s a lot. And life companies do NOT like those numbers. Add in the fact that those 40% that take the policies are like $150/year premiums and…again, I’m sceptical.
And I say that as someone who’s had reasonable success in this area (online retail of life insurance).
And on the life side, you know how many companies have gone bust who tried to go online? A: Almost all of them. Really, pretty much all of them.
That probably should read “the reason the incumbents aren’t doing that on PL in the US is because of regulatory restrictions.”
Spend time lurking in the /r/insurance subreddit and it becomes clear that some portion of those who only shop online probably shouldn’t.
People just have nagging reservations about life insurance. They still research online, and look for sites that allow them to buy online, then still want a phone call. Like, everyone. it’s bizarre.
But I suppose understandable, given the amount of crap information that’s out there. I was looking at a site last week in Canada, where they claim that Equitable Life is now owned by AXA, and that people shouldn’t buy whole life and instead they should invest in RRSP’s at an average rate of return of 19%.
For those unaware, AXA->SSQ->Beneva in Canada, and Equitable Life is a small mutual life insurance company with no relation to ‘AXA-Equitable’. Equitable Life was founded in Waterloo Ontario by CW Tweed in 1942 on King Street in Waterloo with one secretary and a rented typewriter. Lol, how do I even know that.
My other favourite is UL being described using US style UL attributes. No, Canadian UL doesn’t work like US UL.
But that’s what’s out there.
The main difference on the life side is pricing based on genetic information.
With the advent of AI, we now have enough computing power to be able to crack that problem.
For example, you can use anonymised NHS information (hundreds of millions of records) with genetic information to calibrate pricing for life insurance.
You can achieve better granularity for mortality and morbidity, which gives scope for better pricing on an individual level i.e having a mutation for a breast cancer gene can increase mortality by 50% (this is not captured by traditional pricing methods).
On the GI front, it is less clear. Other than cyber or catastrophe modelling, standard GI techniques have not changed much in many years, primarily because there is little need to reinvent the wheel.
Although in that case, it’s really advances in the science of genetics (which have been made possible by more computing power) rather than AI, isn’t it?
I’d also be curious how pricing evaluates according to the minimax criteria. What I mean by this:
I’d think that life insurance pricing using that generic information would have an improved sum-of-squared-error.
But what about the worse-case scenario for an individual person? Genetics are not destiny. And for those people with bad genes, but who don’t actually get sick, or who do not even have a propensity to eat sick, they would be over charged far more than under current programs.
It’s similar to credit models. They improve average income for companies. But they make the situation worse for the individual who gets their identity stolen, and then their credit ruined.
It’s a question of what should be optimized? Companies want the average, but most consumers want the minimax.
Is that really different than the smokers that were overcharged when they didn’t get sick from smoking?
Who are all these people who want to talk to an actual person before buying insurance?! I won’t even talk to the person delivering my food anymore, I rarely pick up the phone because it means I have to speak with a live person, and the idea fills me with such dread.
Maybe not, mathematically. Or maybe so. I’m not sure how the numbers would work out for some of these genes.
But morally it is different, since we usually consider ourselves to have chosen to smoke.
And it might affect more people.
Interesting thought. But then we don’t choose our gender or age either and we’ve generally accepted those distinctions as moral enough to differentiate pricing on. Just mulling out loud now.
Technically, we’ve been made to backtrack a little on the gender one last I was involved in pricing there was a unisex table available which, if everybody chose it, would bring you right back to no differentiation.