You only make insurance cheaper by charging risky people more. Right now it is mostly laws that protect categories of people that keep insurance companies from charging people more. What’s the plan here, use machine learning in a “hands off” way with a black box algorithm to apply pricing discrimination in a way that a human could not because of regulation?
- Processing claims with humans is expensive; every step that can be accomplished by a computer will probably be cheaper.
- A claim processed via ML will probably be handled fast. A fast response = happy customer, which helps with retention. This is a big one.
- A claim that is processed and closed quickly is harder to amend. Some customers slowly realize that adding items to a claim is free money. Others (legitimately) forgot items and want to add them. A quick claim is usually cheaper than one that might take a few days (or weeks) to process.
- Younger generations are more used to working with a web pages and will likely look at humans (e.g. agents) as old-fashioned.
The big carriers are both scared and dubious of Lemonade. If Lemonade can somehow make it work they could do serious damage to the carriers. But it's hard to see how they'll make the numbers work, as their current losses show. Most of the carriers are trying to implement something similar (which is where I'm slightly involved).