Companies use many forms of data to change premiums, many you don't have much control over (e.g. what area of the country you live in). Why is that wrong?
If insurance companies are setting premiums based on personally collected data from random apps, the thing to do isn't to advise people to avoid them, the thing to do is to figure out how to feed the random apps data that looks healthy.
Of course health insurance isn't allowed to consider such data, and it's unlikely to be of much value to life insurance (because it has no provenance).
I thought geography factored into deciding premiums since different areas had different risks of specific events that would lead to an insurance payout. Does what you all are doing simply not need that? Or are you saying that analysis can be left off if they desire for privacy?
They change a lot in the US, too, and different companies have different methods of spreading risk across geographical areas, which can lead to shockingly different prices from different insurers depending on your location.
I don't know what it's like in USA, but where I'm from insurance premiums change a lot from location to location, so much that some people change their residence to a cheaper city.
2. It's a wealth of data that can be used to generate other things about you. It's also data that's traditionally very hard for other parties to get a hold of - your car's make, model and your address is typically not secret information, but for the most part nobody but you knows everything about how you spend your time.
And once your insurance company has this information, you lose control over it. They can share it with other companies, with law enforcement, with parties that may not be relied on to keep the information secure.
Wrong inferences can be made about you, can be shared out.
Remember, this isn't a court where you get to argue your individual case. If data mining starts affecting insurance premiums, you probably aren't going to notice. The insurance company is not going to say "because of your daily McDonald's purchases...". They're just going to say, "effective 6/6/2020, your rate is $x".
People that do "unusual and unpredictable things all the time" are so rare that they don't matter at the scale of data mining. Most people do usual and predicable things, and that assumption is probably worth money.
However, a number of factors have to come together for this to work. First, the insurance companies need to correlate purchases and insurance claim rate. Then insurance companies need to secretly implement this plan. Then when you get the letter that says your premiums are being raised, they need you to not switch to a competitor that is undercutting their new rate. And finally, they'll have to avoid the rage of citizens and legislators. With their upcoming special status in 2014, it's unlikely that lawmakers are going to let insurance companies do whatever they want.
So ultimately, being different isn't going to protect you from data mining, but I think the market will. Do you want to be the first company to announce they're spying on your purchases? Do you want to own the grocery chain that's known as the spying one?
I don't understand what's so hard about the data here. You raised concerns about tax credits, employee share, and subsidies. But none of these have anything to do with the raw insurance premiums charged by insurers.
If you've found that there was a year in which premiums grew by 30+%, say so. I'm not saying I think the data will say things; I'm saying: the data says things.
There's no guarantee that anyone's premiums would actually go down. Instead, you might find people that thought their premiums would go down actually go up because of this. After all, we're talking about insurance companies who are the poster child for fucking over their customers. Giving someone this much visibility surely means they could find something to justify a premium increase.
I would never voluntarily submit data to insurance like this. It's a suckers bet.
Maybe - insurance companies could start using your shopping habits to inform your risk group and therefore premiums. I could see other nefarious uses like tracking when female customers get pregnant for purposes of enforcing abortion bans or targeting of individuals by anti-abortion groups.
I think it's a mistake to underestimate the imagination of insurance adjusters and bureaucrats when it comes to how personal data could be used.
It's really not. Think about what this information is used for: It's probably pulled by your insurance whenever you take out a new policy. There's 40 million people in California. If 5% of them change insurance each year (2 million), and that report costs $25 (A reasonable filing fee for a sensitive government document), there's your $50 million right there.
Right, but I'm talking about the novel ways companies try to optimize premiums. Car insurance is already doing it with some companies wanting you to install an application on your phone to track your driving habits in hopes of maybe lowering your premium. Disgusting shit.
That article says nothing about "using online browsing data to set insurance rates and policies."
To start with, every insurance company develops a statistical model of each and every customer. Non-smokers get lower rates than smokers. Life insurance depends on age. That's how insurance companies must work.
That article says that some insurance companies use more than just risk factors in order to determine the price, but also information like market power (or lack thereof) for your market segment. For example, poor or immigrant people may not have the time or knowledge to look for alternative companies, so an insurance company may offer an initially low price to get lock-in, then raise it after a few years to be above the price needed for actuarial reasons.
It doesn't talk about online browsing data, and it doesn't talk about personalized factors other than the expected aggregate demographic modeling.
I wonder if one way to make better use of this data is to restrict what detail the insurance company can see. For example, you could imagine an arrangement where a third party vendor subject to strict controls gets the raw data and produces summarized scores, for example the frequency of hard brakes. Insurance companies would then only see these summaries, which could be challenged by customers, and can only vary premiums based on the summaries.
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