> gender cannot be used while calculating car insurance premiums. But sadly they can still ask for your profession, marital status, etc.
How is that bad? An insurance works by collecting slightly higher premiums than the expected insurance payout. The more acurately the insurance can predict risk, the better. And if they calulate that some profession/gender/lifestyle/whatever carries a higher risk, it's only fair that those people have to pay more, after all they also cost the insurance more.
Having people pay for their risk is also a net-positive force for society. If some profession causes people to be sleep-deprived and have more car accidents, their premiums go up, producing pressure to either reduce the risks or choose other professions. If you don't let insurances factor this in, you are just subsidizing those with riskier lifes.
If you hyper-specialize the risk pools it effectively prices lots of people out of the market, causing their risk pools to collapse. Insurance also loves to write exclusions if they aren’t prohibited. By your logic health insurance should exclude sickle-cell anemia coverage for black customers.
For insurance to work as intended, it has to be spread across a large population and it needs to cover a wide variety of perils.
Where insurance can be a force for societal good it should be allowed to discriminate. For example, insisting on better fire safety. Or basing your car insurance rate on your car’s safety rating.
P.S. Insurance works by making money off the float, not by collecting more in premiums than they pay out. The expected payout is around 100% over the long run, but the payout happens over time. Until it does, the insurance company holds the money and uses it to make money. (Granted, in this low-interest-rate environment insurance companies may set the payout ratio a bit more favorably since the float makes them less money, but competition effectively helps keep a cap on that).
Mutual insurance companies (owned by their policy holders) are different. Any profit of a returned to the policy holders, so there’s no incentive to set rates higher than required. However the tragedy of the commons kicks in: if they offer lower rates to high-risk groups, they tend to attract the worst of those groups, causing higher losses - especially with health insurance. That’s part of the reason government regulation of insurance is the way it is, the other being gross mis-management causing insurance companies to go bankrupt and be unable to pay out during times when people need it the most.
The variance you see in car crash risk among groups of people is far smaller than the risk of health problems. No drivers have a 100x genetic risk of crashing. The worst case of "new young driver" is already discriminated against, after all, but they can still afford insurance.
> P.S. Insurance works by making money off the float, not by collecting more in premiums than they pay out.
This really doesn't matter. Float happens to be of similar magnitude to profits. It could be significantly more or less. I'd say it's more of a coincidence than anything whenever the two align.
The more acurately the insurance can predict risk, the better. And if they calulate that some profession/gender/lifestyle/whatever carries a higher risk, it's only fair that those people have to pay more, after all they also cost the insurance more.
This is the classic correlation/causation fallacy that is why sadly we have needed explicit anti-discrimination laws in other contexts.
When I added my partner to my car insurance policy, at a time before prohibiting the use of gender to determine premiums, our payments went down quite significantly despite now covering two drivers. When I asked why, they told me that statistically women are safer drivers than men, and since my wife had a good track record with no accidents, that meant our risk together was now lower.
The thing is, at that point I had been driving regularly for many years, while my partner had also passed a test many years earlier but had hardly driven since. We both had clean sheets, but as you'd expect given our vastly different levels of experience, she was not as safe a driver as I was and would have been the first to admit it. However, the insurer's questions hadn't identified any of this, and had reached an obviously absurd conclusion.
Even after the policy change, in practice I was almost always still driving anyway, so clearly whatever my level of risk was before, our combined level of risk was still similar afterwards. But again, nothing asked when we adjusted the cover or since would have picked that up.
This is the trouble with almost any profiling based on personal data, from insurance calculations to targeted police actions to screening job applicants: in principle, it might be a reasonable thing to do, but if your model doesn't properly incorporate all relevant facts, it can actually be worse than nothing because not only does it give an incorrect assessment, it also instils false confidence in that assessment.
You are missing out on the additional information about you that they got when you added your partner, i.e. that you are in a long-term relationship. Married men are well-known to be lower-risk drivers than single men, presumably the insurer also knows that men in a relationship significant enough to buy insurance together are also lower risk.
Also, someone who hardly ever drives is very safe from the insurer's perspective. They may not be very skilled, but they also don't have many opportunities to get in accidents.
Even if that first part were true, we'd been together for a considerable time before she was interested enough in driving the car that we changed the insurance, so their risk analysis would still have been miles off for years.
But they can't base insurance premiums off of information that they don't know. They can't just take your word for it that you are in a relationship, because that is too easy to lie about. Buying insurance together is a clear indicator that would take significant effort to game.
But they can't base insurance premiums off of information that they don't know.
Of course. But as long as they can't form a sufficiently complete picture to make fair decisions -- that is, pricing based on actual risk -- discriminating on easier grounds that are correlated with risk but also happen to be incorrect in many cases isn't fair, so we make laws that stop them doing that.
"...it's only fair that those people have to pay more, after all they also cost the insurance more."
Insurance is supposed to spread risk. If your logic were taken to its limit, everyone would pay in the same amount that they were expected to cost - with an added amount to line the pockets of the insurance companies. Then why bother with insurance at all?
it's only fair that those people have to pay more, after all they also cost the insurance more
What a curious thing to say in 2018. Would you also argue that women take more time off to have babies so it’s only fair on employers not to hire them?
> Would you also argue that women take more time off to have babies so it’s only fair on employers not to hire them?
No, hiring no women simply because they get babies would be silly.
How long the person will likely stay with the company and which extended leaves they will be taking is of course a factor in the hiring decision. Both of those events incur a real and measurable cost to the company. But there are many reasons why males and females leave or take time off, babies are only one of them. And it is only one factor among many. Expected job performance, personality, the effects of certain team compositions, customer perception, etc all have a bigger effect on the company than the baby factor and thus should be weighed accordingly.
How is that bad? An insurance works by collecting slightly higher premiums than the expected insurance payout. The more acurately the insurance can predict risk, the better. And if they calulate that some profession/gender/lifestyle/whatever carries a higher risk, it's only fair that those people have to pay more, after all they also cost the insurance more.
Having people pay for their risk is also a net-positive force for society. If some profession causes people to be sleep-deprived and have more car accidents, their premiums go up, producing pressure to either reduce the risks or choose other professions. If you don't let insurances factor this in, you are just subsidizing those with riskier lifes.