
A simulation of the insurance industry: The problem of risk model homogeneity - hhs
https://arxiv.org/abs/1907.05954
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mikaeluman
Having worked in the finance industry developing risk models for clearing
houses, I can safely say that the problem is a lot worse than the authors make
it out to be.

Regulators across the globe, practically all of whom are wholly ignorant of
what they regulate, demand implementations of their tabular formulas which are
often highly specific rather than generalized and so become obsolete as
quickly as people find gray spots in the formulations and ways to circumvent
the intentions of the regulation. Basic it reads more like law than math and
it doesn’t work.

That means all costs go to implementing these sub-par models leaving no room
for innovation.

In the end, common people will have to foot the bill and regulations will get
even worse. Vicious cycle.

~~~
floki999
Agree about the regulators’ (lack of) abilities.

Catastrophe risk models, however, shouldn’t be be lumped together with the
types of financial engineering/quant models used in capital markets. The
latter are generally very theoretical, based on pretty shallow theory and
little data. Academia has been spewing out a lot of quant finance models which
have little bearing on real market dynamics.

Cat risk models, however, are generally more data-driven and rich in terms of
science and engineering I.e. understanding of underlying hazard mechanisms.
But, like any model, they still are only approximations of reality.

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rdtwo
If the entire industry is exposed to the same risk and all get blown out then
everyone gets a bailout or a pass on paying. That’s a feature not a bug

~~~
kurthr
Exactly, these are companies in business to make a profit not to provide a
societal benefit. They all benefit from regulation of margins and common
model/pricing, "everybody wins" except the customers.

~~~
floki999
Without the insurance and reinsurance industry, we’d be a lot worse off.

~~~
kurthr
Most of the world doesn't have a Health Insurance industry (of US size and
cost) and they have better outcomes with lower pricing. That doesn't mean
there isn't an insurance industry in those places, it's just smaller, more
properly regulated, and less profitable.

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floki999
Havn’t read the paper in detail yet, but the authors’ understanding of the
property catastrophe market is rather simplistic. I’ve traded this risk as an
investor for fifteen years and have used the risk models that are used by all
firms in the market. Yes, there are a handful of cat risk model vendors, but
their numbers are not constrained by the need for certification.

The fact is these risk models are quite sophisticated and all make use of
pretty much all the science, engineering and data available with respect to
the hazards in question. They still are limited in their ability to accurately
estimate risk and this is taken into account when pricing transactions.

Furthermore, while all firms have access to the same models, many (who employ
scientists and engineers) will apply tweaks based on their evaluation of model
weaknesses/limitations. Hence, there is an inherent level of diversification
in terms of how the models are used to price risk. This is what makes a
market.

The objective of catastrophe risk modeling is to estimate, long-term risk as
accurately as possible, while knowing full well that there remains a lot of
uncertainty.

The regulators, rating agencies and other market watchers are actually ill-
equipped to assess catastrophe model risk.

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jacques_chester
Speaking of model risk: the model code for this paper has no tests that I
could identify.

[https://github.com/INET-Complexity/isle](https://github.com/INET-
Complexity/isle)

~~~
xtracto
It is not uncommon for agent based models to lack on the side of good
engineering practices. Given that the majority of these softwares are
programmed to use and throw.

I did research in that field for about 7 years and at that time the focus was
mainly on the paper that was to be published.. it is even a win to have the
source available nowadays.

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vikramkr
Why is too few models the issue? Wouldn't the problem be that the existing
models arent good enough? Its not clear to me how an increased diversity in
models addresses the problem - at the end if the day a form has to pick one to
make any particular decision. If each firm is using a different model in the
name of diversity, then while the few firms with more accurate models
potentially do well the subpar models will underperform in general and
probably increase the overall risk level of the industry. Is there something
I'm overlooking from my skin through the article here?

~~~
byefruit
No model is going to be perfect and given that, you want errors that models
make to be as uncorrelated as possible.

In the extreme case, if all firms use a single model that underestimates the
risk of an event then that event occurring poses a threat to the entire
industry.

With more models, each making different errors, only parts of the industry are
exposed to each error. The more models, the smaller the number of affected
firms and with reinsurance between firms the risk to the whole industry is
much smaller.

~~~
throwawayjava
The basic question is whether the reinsurance companies are properly
capitalized given the homogeneity of risk taken on by the insurance companies
they cover.

There can be a lot of modeling homogeneity without lots of unanticipated risk
(e.g., natural disasters in disparate geographic regions).

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theincredulousk
This entire paper and no reference to Nassim Taleb? They even use his
language.

Any fans of Fooled by Randomness, Black Swan, etc.?

One of his main ideas, that he has followed up with Mathematics, is fragility
to model error in the presence of fat-tails.

If you’re interested in this kind of stuff I’d highly recommend his books.

Anyone with math chops beyond mine checked out his papers? I don’t understand
enough of them to endorse or critique.

~~~
short_sells_poo
That's possibly because Taleb does not have a good reputation among most
experienced professionals (in my circle in the hedge fund industry). He talked
a lot of sense, but then failed to put most of it into practice. In other
words, he isn't earning money from what he preaches, he earns money from the
preaching.

It's all nice and dandy to say "you have to be anti-fragile, expect the
unexpected, yadda yadda yadda...", but putting it into practice is extremely
difficult. I don't know of a single institution who did so with an audited
track record. Sure, there are (were) many tail event specialized funds, but
these will not be providing regular income as one would expect from most
funds. Rather, they'll tend to constantly bleed money (basically an insurance
premium), and then pay out larger sums when the "midden hits the windmill".

Even looking at something like 2008, it is often cheaper to just accept the
occasional drawdown and weather the storm rather than buy protection against
it, because of the amount of headwind your investment will face in terms of
the insurance premiums.

~~~
johnrgrace
Taleb one day got into an all out drop down twitter war with my friend Andrew
Shaffer, author of books like "50 shames of earl grey" "how to survive a
sharknado" etc. His personal unhinged behavior makes everyone suspect of his
professional work.

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jmpman
I’ve wanted to see similar simulations but for the housing market.
Historically housing rental prices didn’t exceed renters income and yet times
of rapid housing inflation (2006-2008) outpaced any income gains. Of course
those reasons are known, and the subsequent housing price fall set off a
cascading effect. Recent housing increases outside of the bay seem eerily
similar to the previous bubble, but I haven’t seen any good analytical
framework to determine if it’s sustainable.

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asdfasgasdgasdg
Should the insurance just find a way to exclude massive, correlated events?
That might give buyers a more reasonable expectation of covered losses, given
that coverage in such an event is smoke and mirrors anyway. It's all well and
good to have liability insurance, since presumably one's own liability is
fairly uncorrelated with other people's liability. Flood insurance, financial
instrument insurance, etc. is more questionable to me.

~~~
cortesoft
That is what the reinsurance market is for. Natural disasters are when
insurance is most needed, to rebuild a whole community. Disasters are locally
correlated, but generally not globally correlated. The global insurance market
can handle them just fine, and in fact are a great example of a place where
insurance is needed - large, unpredictable, rare, and too expensive to handle
by yourself. That is just the same as individual insurance, just at a larger
scale.

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bfirsh
If you're on a phone, here's an HTML version of the paper: [https://www.arxiv-
vanity.com/papers/1907.05954/](https://www.arxiv-
vanity.com/papers/1907.05954/)

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cosmodisk
I'd love to see simulations for Lloyds of London,where underwriters often
insure each other or the the entire trail of who's responsible for what gets
very tricky.

~~~
floki999
Check out the ‘LMX spiral’ ..

~~~
cosmodisk
This is what I was thinking about but didn't it even had a name..

