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There are quite a few discussions around
insurance these days. One that's been talked about but maybe not
enough and is getting more and more
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focused now is how credit
scores can have an impact on how much you pay
for homeowners insurance.
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Pleasure to be joined
by Ben Keys, Professor of Real Estate here at
the Wharton School.
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Ben, great to catch up again.
How are you, sir? I'm doing well.
Thanks so much for having me, Dan.
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Yes, absolutely.
All right. So the bigger question I think I have
right at the top is do people realize the
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level of impact that a credit score can
play on your homeowners insurance rates?
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Yeah, I don't think they do. I was certainly surprised by our findings
in this study looking at households with a
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very rich data set to see
just how much their credit score impacts the cost
of homeowners insurance.
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And it turns out it's quite a lot. We've had many discussions over the last
few years about climate risk and some of
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the rising costs there in terms of where
you live. But they're not just pricing on place.
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They're also pricing on people. Right. And so there's a couple of components to
discuss here.
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Speaking about the people, is there a
significant difference when you're talking
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about credit score with lower and higher
income families? Yeah, I mean, so certainly there's a
strong relationship that people with
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higher incomes have
higher credit scores, but it's certainly not a
one-to-one relationship.
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One of the things that we're struck by in
this analysis is thinking about what
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credit scores are proxying for when
insurers use this in their pricing. And so they're not allowed to use credit
scores in all states.
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And we'll talk more about some of the
variation across the country in this. But when you're looking at this,
one of the challenges is, well,
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credit score is correlated with a lot of
other things and a lot of other attributes.
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And so from a research standpoint,
we wanted to try to find a setting where we could isolate just a change in the
ability of insurers to use credit scores,
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rather than all of the other things that
credit score might be correlated with. Now, the other component which you and I
have talked about is climate risk.
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And your research talks about the fact
that credit score, in many cases, is an even bigger burden at times than the
climate risk component.
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Yeah, we were very struck by this,
that if you look across much of the country— so not in the most risky parts of
the country, but if you look at the rest
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of the country, you know, the vast
majority of the distribution of households in the US, your credit score is actually a
bigger determinant than your climate risk.
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If you were to just improve your credit
score a little bit, that's going to have a
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bigger impact on your
cost of insurance relative to just doing a small reduction
in your climate exposure.
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And so if you could think about the kind
of the gradient between your expected losses or the gradient
between your credit score, it's
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that credit score relationship
that's actually steeper. And that might undermine sort of some of
the incentives to reduce your risk or to
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mitigate some of the hazards when you
might be better off paying down some of your credit card debt and improving your
credit score.
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That might be a quicker way to lower your
insurance bills. Do we know how much we're talking about
here differential, whether it be
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percentage or actually dollars wise,
of the type of difference we're seeing with people that are paying
more on their homeowners
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insurance than people
that are paying less? Yeah, so in our study we find that, all
else equal, households in the top quartile
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of credit scores pay
about $550 a year less for insurance than
those in the bottom 20%.
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And that's the average. That varies quite a bit across the
country. And it's quite a bit larger difference in
the highest risk areas.
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So there's kind of a double whammy for
living in risky areas, that if you have a
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riskier location and also
a lower credit score, you're going to pay substantially
more for homeowners insurance.
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Now, I'm sure there are going to be people
out there that are going to say that
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laying this out the way you have,
it's a bit of an unfair process for those at the lower end of the spectrum.
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What do you say to them
about how to kind of deal with this and mitigate it
the best way that they can?
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Well, this is the tension in setting
risk-based pricing. And three states have banned the use of
credit scores in setting homeowners
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insurance rates, California, Maryland and
Massachusetts. And the view in those states is that it
isn't a fair practice to use credit
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information to set your homeowners
insurance. In the other 47 states in
the country, you are allowed
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to use credit scores,
although to varying extents. And I think what that suggests is that
there's a variety of opinions on whether
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this is fair from a sort of policy
standpoint. I think actuarially, the insurance industry
says, "Well, there's predictive power in
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the credit score. It's proxying for a bunch of things. And if we try to unpack what some of those
things are that it's proxying for,
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you know, one might be that people with
lower credit scores live in riskier areas.
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That's something that
we can account for very well in our rich data from
McDash and CoreLogic.
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Some of it might be that they live in
older homes. And so there may be a difference there in
terms of the potential risks.
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That's another thing that we can account
for. But I think there's a couple of kind of
remaining concerns that are out there.
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One is related to household liquidity,
just the likelihood of filing a claim after an event rather than using your
savings to cover it and sort of
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recognizing that multiple
filings has a negative impact on the cost of
insurance going forward.
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So that dynamic story. Or it might be kind
of a proxy for conscientiousness, that the people who, you know,
miss a credit card payment are the same
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people who might not be maintaining their
homes at the same quality level. You know, the insurance industry doesn't
necessarily unpack those different drivers.
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They don't have the data to do so. And so they use this catchall of a credit
score as a proxy for these things.
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And you can see in their models,
they argue that it's a strong predictor of ultimately the losses on a given property.
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So that's the trade off is, you know,
this idea of fairness is from actuarial
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standpoint, is this seen as fair, versus
politically, or socially, do we think that this is fair?
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And, you know, when you see examples of
next door neighbors paying, you know, 2x what the other one is
paying, you start to think,
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well, that doesn't— doesn't
feel like a very fair system. What do you think, then, are some of the
solutions?
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And is there a potential federal solution? Because obviously, most of this work is
being done at the state level.
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You know, for the federal
government to try and help address some of these
challenges in the insurance market.
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Yeah, the tension is that the states
really, you know, are the ones who regulate homeowners insurance,
and the federal government
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only plays a very small
role, if at all at the moment. And so this is a state-by-state process to
determine, you know, what is the— what is
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the ability of the insurers to use
additional information? And what is this actually proxying for?
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What is it capturing? I think we need better data from the
industry to connect this to claims data
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and to understand what some of the
underlying drivers are of the pricing relationship that they see that they're
then passing on to the homeowners in
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the form of higher premiums. What about the federal reinsurance market? So the federal market doesn't—
you know, there isn't really a federal
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reinsurance market when it comes to
homeowners insurance. There's a federal flood
program, and they don't
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price credit scores in
this same way. So you don't see the same relationship in
the national flood insurance program.
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But I think, you know, in terms of
addressing sort of credit-score-related issues, it really does become a state by
state story.
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And in our paper, we dig into a policy
change that happened in Washington state where they essentially flipped the switch
and said you can't use credit scores and
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then flipped the switch back after intense
lobbying from the industry. And there, we could kind of hold a lot of
the other characteristics constant.
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These were the same
homeowners in the same houses with the same insurance
carriers in most cases.
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And we can see exactly
what the effects of taking credit scores out of the pricing model
did to the cost of insurance.
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But the challenge for the consumer
continues to be one where there's not a lot, it seems like, that they can do on
their end to be able to have a significant
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impact to make this system work better
down the road, it feels like. These are challenging times in the
homeowners insurance market.
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We are seeing some softening in a few of
the most expensive spots in the country.
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But in general, insurance prices are up
quite a bit. The McDash data suggests
that they're up almost 7%
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over the last year, which
is far faster than inflation. And that's after multiple years of double
digit growth.
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And ultimately, what our study is pointing
to is that this insurance burden falls
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most heavily on the lowest credit score
households. And so those are the
households that have the least
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cash on hand and that
need insurance the most. They're the ones who are
going to benefit the most from
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having this protection in
place in the event of a disaster. And they're the ones who can afford it the
least.
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And so that's really the tension in this
market right now. Ben, great to talk to you again,
as always.
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Thanks very much. Yeah, thanks so much for having me,
Dan. Thank you. Ben Keys, Professor of Real Estate here at
the Wharton School.