As you head into the new year, you may be looking to renew your insurance and here is something you should watch for: the schmo tax!
That’s what people are calling insurers’ practice of using price optimization. Which sounds consumer-friendly, but isn’t.
It’s a practice whereby insurers try to maximize your premium based on what they can dig up about your online shopping behaviour. Translation: “schmo” comes from the concept of “Joe Schmo,” the ordinary, not-so-brilliant human being.
Consumer Reports Online Magazine reports:
“[Insurers] mine data about your shopping behaviour to uncover trends, such as how many iPhones you’ve bought, whether you remain a loyal customer of one telecom company when another is offering cheaper service, and how much of an increase you accepted when your car insurance policy was renewed in the past. Then your insurer applies its trade-secret algorithms to predict how much of a price increase you’ll tolerate without quitting the company and shopping for a better deal elsewhere.”
Actuarial data gives way to big data
In other words, you may be paying more for your car insurance if you’re not an online price-shopper (and far more than that). It means that your insurance premium may not be determined from actuarial data (risk-based), but instead determined by big data.
If a price optimization analysis indicated that a consumer in one location was less likely to comparison shop than a consumer in another location, the insurer would charge the first consumer more for an identical policy – even if the two consumers had identical risk profiles.
Umbrage in the USA, calm in Canada
While this practice has caused considerable outrage in the United States, it’s virtually off the radar in Canada. Pennsylvania, Maine, D.C., California, Florida, Indiana, Maryland, Ohio, Vermont, and Washington have all taken action to ban or restrict. Yet, try an online search and you’ll find very little Canadian-focused discussion.
But, it would be surprising if this is happening south of the border and it isn’t happening here. The Toronto May 2015 conference, Analytics for Insurance Canada, had this as one of the highlights:
“This isn’t another conference – it’s a high-level niche conference showing insurers how they can use the vast amount of customer data they have. It’s about strategy and business rather than IT, so you won’t be bored with technical jargon”
What about the regulation?
Insurance companies are heavily regulated. In California, the law states that insurers must base insurance premiums on risk-based factors. Therefore, pricing premiums based on what the consumer will pay is banned.
The California government sent a notice out to 250 insurance companies in the state of California that price optimization does not seek to arrive at an actuarially sound estimate of the risk of loss and other future costs of a risk transfer. Therefore, any use of price optimization in the ratemaking/pricing process or in a rating plan is unfairly discriminatory in violation of California law.
In Ontario, we also have a similar regulation under the Insurance Act of Ontario Regulation 7/00, called the Unfair or Deceptive Acts Practice. Section 1 paragraph 1 and 2 prohibit:
- Any unfair discrimination between individuals of the same class and of the same expectation of life, in the amount or payment or return of premiums, or rates charged for contracts of life insurance or annuity contracts, or in the dividends or other benefits payable on such contracts or in the terms and conditions of such contracts.
- Any unfair discrimination in any rate or schedule of rates between risks in Ontario of essentially the same physical hazards in the same territorial classification.
It would be useful if the province of Ontario could confirm whether these practices occur here and what steps they have taken to ensure the insurance companies are warned off from engaging in such practices. In any event, we can all help ourselves from being “schmos” by questioning premium increases and shopping around online.
