self-driving

INSURANCE: Porsche and Mile Auto to cut premiums 40% using AI for pay-per-mile insurance.

Insurance is the holy grail for Artificial Intelligence and the Internet of Things in finance, because it requires a messy interaction with the physical world, rather than living merely in a spreadsheet, database, or blockchain. To this end, we like the news of Porsche partnering with Mile Auto on pay-per-mile insurance. There is a reasonable demand-side argument: owners of Porsches don't drive the car as a primary automobile, and would prefer to only pay insurance for the time they are actually on the road. The second argument is even more fun -- owners of Porsches don't want to be tracked via GPS or a black-box by something like Cambridge Mobile Telematics ($500MM from Softbank) or Metromile ($90MM from VCs) because they are fancy and private people. No tracking please!

How does the thing work? You pay a cheap base rate to Mile Auto, and once in a while take a picture of the speedometer's reading in the app. The picture is translated to numbers via a machine vision algorithm, and your per-mile variable insurance rate is calculated on the spot. The company claims this will lead to a 40% reduction in premiums for the average user. For what it's worth, we hear that the growth of renter's insurer Lemonade is similarly fueled by people who are forced to get coverage (e.g., by the landlord) but are looking for the most discounted, easy to manage product. What does that mean? It means that the low risks self-select out of the insurance pool, driving up the price for unsophisticated non-techies that don't drive a Porsche.

Let's take the argument to an absurd extreme. On the developer website Programmable Web, there are 59 separate APIs that developers can use to build insurance apps and connect into underwriting engines and carrier capital. From Clearcover (affordable car insurance in your app!) to Haven Life (term life insurance on any website or application!) to Lemonade, OCBC Materntity, Qover and a plethora of others, developers have real choice in how to weave these more digital insurance products into the attention black holes in your phone. What happens when the tech-forward customer considers only these options, and the conservative customer considers only insurance sold by agents and direct mailing? Could there be a bifurcation of risk profiles that fundamentally injures the risk-pooling function of the industry? Perfect information about risk collapses the value of hedging. Half of us will know and live in a predicted future, while the other half will pay for the ignorance.

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Source: PR Newswire (Porsche), Company websites, Programmable Web (Insurance)

INSURTECH: Rage Against the Machine and $500MM telematics Softbank investment

Let's start off with the ridiculous, and get more ridiculous. SoftBank has a lot of money to invest in category killing fintech businesses, and one of the latest such players is Cambridge Mobile Telematics, which just received $500 million from the investor. What is it? A widget attached to a car windshield, and then used to collect data about the quality of a particular driver -- from speeding to breaking. This data is then tied to the purchasing of insurance, where "good" drivers have access to lower cost financial products. This is an interesting, and pioneeing, example of how edge computing will create orders of magnitudes more digital data that then feeds the manufacturing of finance. 

A sneaking suspicion in the back of our minds is that driving data is really good for training robots how to drive. Meaning, Google and the rest of the big tech companies are all running experiments with self-driving cars on the road to collect driving data. Something simple from a telematics device certainly is not equivalent to major machine vision and radar data. But it does paint a straight line towards how self-driving car insurance should be priced. Let's repeat that. If a widget in a car tells you insurance prices based on driving performance and you combine that with an AI car, you could compare humans and machines on an apples to apples basis.

The ridiculous part is the human response to tech-first transportation companies. In London, Chinese bike-sharing company Ofo is pulling out of the city because people steal and destroy their untethered bikes. In California, aspiring freedom fighters keep throwing scooters from Bird and Lime into oceans, lakes and rivers. Public service employees are straining to fish out these venture capital funded wonders out of the water. In Phoenix, self-driving Waymo cars are getting their tires slashed and assaulted by gun-wielding road-ragers (Mad Max style, we assume). All that to say that the human element in this story is allergic to being entirely prodded, measured, and automated away. Can politics catch up with SoftBank's Vision Fund, which could build Trump's wall 20 times over? We hope so.

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Source: DigIn (Softbank), Gizmodo (Ofo), Slate (Bird), Business Insider (Waymo)

ARTIFICIAL INTELLIGENCE: Self-driving cars and self-speaking news anchors inch us closer to dystopia.

Financial services regulators have been so hard on crypto currencies, roboadvisors, digital lenders and payments companies. It's as if that money is a life or death situation! But getting a permit to drive a robot car on a public road without a human being holding the wheel -- not a problem in California. Waymo, which is the Google car spinout, has been given the green light to put 40 autonomous cars on the road. This is already happening in Arizona, with 400 users that can get into a robot car via an app around Phoenix.

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We don't want to be alarmist, of course. Statistically, these machines are likely much better than humans at driving -- they are just more likely to make mistakes that humans would think are preventable. The same process took place in regards to machine vision, with early prototypes making classification mistakes between cats and dogs; now, such algorithms can tell apart the difference between hundreds of breeds. So we hope to see similar progress as driving and visual data is incorporated into autonomous car systems. We'd be remiss not to mention our white paper on the topic, which models out how the insurance industry may lose its lunch when cars don't crash. On the other hand, we note that the DMV required a $5 million bond to put a self-driving car on the road, so the risk is still wildly unknown.

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In a more sinister move, China's state-owned news agency recently launched "composite anchors", which is a machine vision version of a news anchor that can be manipulated with text. Here's how it works. You shoot dozens of hours of video of a person speaking, and then spin up neural networks that can (1) manufacture sounds similar to the target's speech and (2) manufacture video resembling the human making that speech. Presto -- just type in whatever into a command box, and your generated anchor will say it, in any language you would like. Given the recent video editing experiments that the White House supported in relation to denouncing a journalist, we are acutely terrified of how this can impact the attention economy. Not to mention the implications for selling a human likeness for endless manipulation. 

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Source: SF Chronical (Waymo), South China Morning Post (AI Anchor)