Will be interesting to see if they can apply this to other markets. You'd think if they could quantify the risk for flying robots then they'd be able to do it for anything.
First off, a disclaimer. I am Abe, and I lead the engineering team at Flock.
With that out of the way, yes, our algorithmic risk assessments leverage real-time data to identify real time, geospatial risk. It is absolutely our long term vision to use this to make insurance generally more fair, easy to use, and, yes, cost effective to both the insurers and the insured. In pursuit of this goal, we are currently working with other insurers to identify whether our core technology can be used in other industries.
Interesting. Just learned recently that the biggest insurance risk with drones is fires from the batteries, during flight and during storage.[1] Not sure how on-demand would help with the latter.
Care does need to be taken with LiPo batteries , ideally charging them with a compatible balance charger. If they are to be stored for a prolonged period, often the batteries can be discharged to a “storage” capacity. It is good practice to always charge and store your lipo batteries in a lipo safe bag (available from most hobby stores). Always follow the LiPo battery manufacturer guidelines!
With that out of the way:
A subscription product is something that we're currently working on which will offer you out of flight cover. It's still in the early stages at the moment but if you sign up to our newsletter on our website you'll be the first to know when it rolls out.
i know this is a bad question but the TAM for this is... not inspiring. this would be a nice small biz but i dont know how this is a venture scale biz. maybe they have plans to expand beyond drones.
What is the societal value of adding more (and real-time) data to insurance?
In general, insurance helps spread risk. This means that if something drastically bad happens we distribute the impact over a larger population reducing the individual impact.
In the extreme if you perfectly assess risk insurance ceases to have any value. The insurance costs would perfectly reflect the risk and there would be no benefit to owning insurance.
My hunch is that this kind of data driven insurance could help people avoid risky situations. But I’m not sure that’s a given and it seems like there are many downsides (particularly if the risk is unavoidable).
"My hunch is that this kind of data driven insurance could help people avoid risky situations."
That's the ideal. The cheapest accident to pay for is the one that doesn't happen.
It's all about aligning incentives. The win-win dynamic is that the insurer can certify training courses, licensing, product design, etc. Customers can get discounts for making safer choices.
Selection effects can be more adversarial. e.g. You get dropped after the first incident. The people who would benefit the most from coverage can't get it. People with poor credit scores get discriminated against even in the absence of activity specific bad history.
Obviously as you mentioned perfect discrimination causes the system to break down. Risky customers can't get covered while safe customers don't buy because their risk is infinitesimal.
That is the dream - be a risk management and insurance company, rather than just the latter. We do reward people for safe flying and provide them with data in order make the best choices. This is why we are fairly transparent about where the price comes from (even if we do not necessarily tell people exactly how we calculated a price from the data).
If a customer knows that their price is high because, for instance, there are 2 schools within a 300 yard radius, chances are they can move their flight, thus endangering less people and saving themselves insurance premiums.
>In the extreme if you perfectly assess risk insurance ceases to have any value.
For low probability high impact risks insurance is very useful even if perfectly assessed. For example you might determine the risk of my house flooding in any given year to be exactly 0.1%, and the expected damage $100000. Having to pay $100k would be a disaster for me, but paying $110/year to an insurance company is small cost I might not even notice.
With perfect risk evaluation insurance is mathematically a bad idea, but unless you have limitless access to capital at market rates it's hard to get an advantage from not talking that insurance
13 comments
[ 3.4 ms ] story [ 50.9 ms ] threadWith that out of the way, yes, our algorithmic risk assessments leverage real-time data to identify real time, geospatial risk. It is absolutely our long term vision to use this to make insurance generally more fair, easy to use, and, yes, cost effective to both the insurers and the insured. In pursuit of this goal, we are currently working with other insurers to identify whether our core technology can be used in other industries.
[1] https://jrupprechtlaw.com/drone-insurance
With that out of the way: A subscription product is something that we're currently working on which will offer you out of flight cover. It's still in the early stages at the moment but if you sign up to our newsletter on our website you'll be the first to know when it rolls out.
In general, insurance helps spread risk. This means that if something drastically bad happens we distribute the impact over a larger population reducing the individual impact.
In the extreme if you perfectly assess risk insurance ceases to have any value. The insurance costs would perfectly reflect the risk and there would be no benefit to owning insurance.
My hunch is that this kind of data driven insurance could help people avoid risky situations. But I’m not sure that’s a given and it seems like there are many downsides (particularly if the risk is unavoidable).
I’d be interested in perspectives on this.
It's all about aligning incentives. The win-win dynamic is that the insurer can certify training courses, licensing, product design, etc. Customers can get discounts for making safer choices.
Selection effects can be more adversarial. e.g. You get dropped after the first incident. The people who would benefit the most from coverage can't get it. People with poor credit scores get discriminated against even in the absence of activity specific bad history.
Obviously as you mentioned perfect discrimination causes the system to break down. Risky customers can't get covered while safe customers don't buy because their risk is infinitesimal.
If a customer knows that their price is high because, for instance, there are 2 schools within a 300 yard radius, chances are they can move their flight, thus endangering less people and saving themselves insurance premiums.
For low probability high impact risks insurance is very useful even if perfectly assessed. For example you might determine the risk of my house flooding in any given year to be exactly 0.1%, and the expected damage $100000. Having to pay $100k would be a disaster for me, but paying $110/year to an insurance company is small cost I might not even notice.
With perfect risk evaluation insurance is mathematically a bad idea, but unless you have limitless access to capital at market rates it's hard to get an advantage from not talking that insurance