Creepy Insurers? - by Matthew E. Kahn
Environmental and Urban Economics
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Creepy Insurers?<br>DNA, Drones, and the Adult in the Room
Matthew E. Kahn<br>Aug 16, 2026
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Dora and I buy insurance for our car, home, lifespan, health, disability and travel. For profit firms are willing to bet that we won’t crash our car, drop dead, experience a wildfire, become disabled, or have some catastrophe on a trip abroad.<br>These firms hire smart actuaries who do the best they can to predict what is our conditional probability of suffering one of these bad events.<br>Thanks for reading Environmental and Urban Economics! Subscribe for free to receive new posts and support my work.
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For example, I am a 60 year white man who lives in West Los Angeles and has never filed a car insurance claim in 44 years and I own a 2020 Tesla with 35,000 miles on the odometer. Conditional on this information, a car insurance company quotes me a premium price for the next year. The insurer gets paid my premium and makes profit if I don’t file a claim.<br>Some Insurance Econ 101<br>Suppose the actuaries predict that I have 1% chance of being in a car accident that causes $75,000 in total damage during the next year. They would love to charge me $5000 for car insurance but competition will drive down the price of my premium to roughly .01*75000 = $750. Even if there was no law requiring that I have car insurance, a risk neutral person would pay this amount. The insurer would be foolish to charge me $545 because it would expect to lose profit under this contract.<br>The “Creepy Insurer”?<br>Let’s focus on health insurance and residential property insurance. Suppose I receive a letter from my insurer;<br>Dear Matthew,<br>Thank you for your trust in giving “AllFeet” the opportunity to be your insurance carrier for the last 17 years. To better serve you, we would like to ask you to submit a genetic sample of your DNA and allow a drone to fly over your home and to allow a Google Street view Car to photograph your home.<br>If you opt in and provide us with these data, we will provide you with a payment of $X. These data will allow us to provide tailored insurance products that are likely to save you money and improve your quality of life in the years ahead.<br>If you have any comments or concerns, please visit this website to watch our information video.<br>Sincerely,<br>ZZZ
How do you predict that Matthew will respond to this letter? To keep this Substack short, let me tell the optimistic case and make my main points;<br>#1 Matthew knows that his grandfather lived to age 96 while his other grandfather died young from smoking too much. His parents are still alive. The family health history is actually quite favorable. Matthew anticipates that his DNA sample will distinguish himself from other 60 year old white men in his nice zip code and he will be charged lower rates. He opts in.<br>#2 Matthew and Dora have been investing effort in clearing vegetation from around their property. The home is tidy and the recent Los Angeles Wildfire has motivated them to be proactive about mitigating property risks. They have been talking to their neighbors about their actions to reduce block level risk. They welcome the drone flyover.<br>My Point? If insurance buyers can opt in to participating in these two data sharing opportunities then advantageous selection will occur. Those who know that they are above average will provide their data because we are tired of being pooled with higher risk individuals.<br>The insurers are NOT dummies —- Those who do not reveal their private information about the genetics and property preparedness are “hiding something”. Do they have a private property right to hide that information? The Insurer’s letter “outs them” and causes a separating equilibrium. In English, Santa knows who is “naughty and nice”. Now, the insurer knows new information about who is “high risk and low risk”.<br>The insurer will start to charge higher prices to higher risk individuals and properties.<br>Before you get upset about this inequality caused by “greedy capitalist firms”, permit me to make a new point.<br>Suppose that Matthew has a genetic score that places him at risk of Diabetes and suppose that the drone sees that Matthew’s home in Westwood is at wildfire risk because of wild vegetation.<br>Suppose Matthew receives the following new letter from the insurer;<br>“Dear Matthew,<br>Your personalized risk score data indicates that both you and your home are at higher than average risk to experience health and property losses. We have a fiduciary responsibility to our shareholders to charge you more for insurance.<br>But, we also have a responsibility to you to offer you an opportunity to enjoy cheaper insurance.<br>Given your diabetes risk, we ask that you take an A1C blood test every 6 months and if your score is lower than 5.9, we will offer you a 32% discount on your insurance.<br>Given your home’s wildfire risk, if you take these 4 certifiable precautions , we will reduce your property...