NICC - National Insurance Conference of Canada’s Post

Transcript

Hey, this is our final interview today, at NICC 2024 on day one. And we had the pleasure of having Michelle Dogan, who is the head of auto insurance supervision for FSRA and she's just come from a panel. It's the end of the day and she's going to crush it with us today and finish up strong. So Michelle, thanks for jumping on with us. Everyone loves talking about insurance regulation, but. No, except us, but let's let's look. Obviously there's a lot going on when it comes to auto insurance Ontario and what's happening there. What are you seeing through your lens of pizza right now that you know you want to share with them? The industry, yeah, so much is changing in auto insurance supervision right now. So we've just released some some new guidance on a new supervisory model that we're developing and we're trying to give the industry a little bit more flexibility while also introducing some new principals and targeted consumer outcomes. To achieve more fairness in the industry, fairness and pricing and underwriting get more accurate pricing addressing any potential areas of unfair bias or discrimination. So that's really where our efforts are focused right now and and the industry is also working on building up some of those capabilities too. So are you hearing this from consumers to drive change or is this more of a collaborative approach with industry? It's a combination of the two. So you know, the, the fairness discussion is really advanced in the US right now. And I think, you know, Canadian insurers are starting to think about fairness and they've been having discussions internally and starting to build up some of their capabilities and raising that awareness. And we're having the same conversations as as a regulator and starting to think about, you know, where, where and how to address some of these issues. So it's, it's kind of from both sides. And you were on a. Anel just now that's Pete mentioned Speaking of how data is applied, you know, bringing in 3rd party data and all the various analytics that are coming into our industries. Can you tell us a little bit how the panel went at NYCC this year and what did you get from that as much as you were part of the discussion, what did you get from it by being up there with with the others? I think our team, one of our key messages today was just that there's so much more complexity. So there's way more data available than there ever was before. Like usage, basic insurance is a great example of that, where now we have all this data, much more detail than we ever had before around when people drive, how people drive, how much they drive, all of that. And that just wouldn't have been available to us before. Umm, and models are more complex than they ever have beans. So when we talk about issues of fairness. And there's greater risk than there has been before because everything, we just have more of everything and more complexity within the way that pricing models and underrating models are are built. And there's potential for, you know, unintended consequences. So on our regular show, we've done a lot of interviews with people doing some new technology when it comes to auto insurance and preventative and predictive technologies, some named NATO and other one called driver technologies. Are these things as a regulator? They're trying to be aware of and health insurance companies implement. So it actually helps benefit the driver and the underwriter. Or are are you even able to get that far given all the other changes going on? Are you referring to automobile safety, like new technology, technologies that would help vehicles, help driver tech and help them to accident avoidance and different sort of options like that as opposed to just recording behavior and then realizing it after the fact? Yeah, I mean, we're certainly watching the trends and I think insurers. We're watching the trends as well and trying to understand, you know, how that could potentially, you know, reduce the number of accidents, reduce the severity of accidents or reduce injuries and things like that. But at the end of the day, the pricing is really based on what we see in the data. So if we see, you know, real improvements in terms of of frequency of accidents or if we see real improvements in terms of, you know, lower cost of accidents because safety is, you know, you know, protecting the safety technology is protecting. People better in vehicles and they're less likely to be severely injured. Those are the things that are ultimately going to reduce the cost of insurance. So there's a bit of a lag between when those enhancements are made and when we actually see it in the data. Promise. Like do you guys dive into that at all? Is that part of your file as well? I mean, Pete and I were just down in LA before coming here and and we were passed by one of the new autonomous taxis, right where you know that someone's riding in a car and there's no driver. So how do you guys feel about that as it relates to Canadians? Well, I mean. I, I think, I personally think it's fascinating right now what we're looking at is connected car data, so similar to usage based insurance, which is like collecting data on an app on your phone while you're driving and that would be delivered through the insurance company. You know, auto manufacturers have so much data, the car is collecting data all the time. And so there's so much more information that's available to us than than ever was before. So when we talk about things like like pricing accuracy, for example, or, you know, stripping out unfair bias and discrimination, there's nothing more. Objective, then there's nothing more objective than that connected car data or BI data, autonomous vehicles. I mean, it's coming, but it's still kind of a ways away. So we're again, it's sort of like this situation where we're, we're watching, listening, thinking about what it's going to mean for the future of the industry. But it's, it's not kind of the near or, or medium term, you know, issue that we're managing right now. Michelle, what about the ownership of data? There's a person driving a vehicle who's generating all this data. Do they have an in your views at Fizzer? Do they have power to control their data and own it? And should they have access to it? Yeah, I don't have the answer to that question. That's gonna put you on the spot, I think. I think depending on, yeah, I think depending on who you ask, and then you might get a different answer. If you talk to the auto manufacturers, they would probably say that they own the data. But if you own the vehicle, should they, should that data not be available to you or should you not, you know, have the right to consent? With the use of that data or the viewing of that data, that kind of thing, I don't think that those questions have really been answered. But it's sort of percolated in the US market more recently because some of that connected car data had been sold to a third party, which was resold to some insurers. And since that's been pulled back. So they're really important considerations around ownership of data and privacy of data and whether the owner of the vehicle should be able to decide. Where their data goes and how it's used. O let's put you on the spot. What's been your favorite session at NYCC today? I. I really enjoyed the discussion that we just had with the group, and I was moderating the panel, so I was not answering the question. Like us. Yeah, you gotta listen really attentively. Yeah, exactly. But these are the issues that are kind of near and dear to my heart, for sure. And what we do at Fisera. The other one is, is fraud. So many people in the industry would be aware that we're building a new fraud reporting service for the industry. So for the first time ever, we're going to have this. Kind of global view of fraud in Ontario specific to automobiles, specific to automobile insurance, but the types of fraud that are that are occurring and for the first time ever being able to quantify the impact of, of fraud on the industry. Like we know it's a really big number, but we don't know exactly what that number is, right? So now we're going to be able to describe it and quantify it. And then once we're able to do that, then we'll be able to look into the data and identify, you know. Patterns, networks, things like that. And think about, you know, what's an appropriate way to leverage that data to to mitigate fraud or avoid fraud in in the industry. And that will help, you know, reduce auto insurance premiums over time or at least mitigate the effects of cost inflation over time, if that makes sense. Well, Michelle, thank you so much. It's been a long day for you. It's always tough being the last one bat and clean up, but you hit it out of the park and we really appreciate you stopping by and enjoy the rest of your time at ICC. Thank you so much. That was an awesome interview, Pete, and we're rolling. We've got way more coming on. Yeah, great guests. And thanks to Accenture for having us out here. And remember, check us out on the Insurance Podcast wherever you download your podcast.