[deeg]

I'm tangentially involved in the insurance space and I believe Lemonade is trying to use machine learning to process claims because:

- 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).

[gen220]

Depending on your perspective of "ML", the insurance industry already uses "ML" (i.e. very complicated decision trees) to process claims. Very few large insurance companies are non-automated in claims processing.

The places where the money hides, so to speak, include (1) handling complex cases [customers] (2) scaling a human's ability to process non-automatable settlements. (3) scaling internal support interactions with customers (4) introspection to claims data and support data. (5) graceful handling of prior authorizations.

These problems are not as attractive, but they are where insurance companies spend most of their money. It's still a tech problem, but it's not super fancy.

Existing carriers struggle to solve these problems, because they have historically grown by acquisition, and as such do not have the kinds of unified data systems required for the rapid development of applications that perform the required kinds of introspection. It's a space that's ripe for disrupting.

[zerni]

Working in “InsurTech” myself...

I’d say customer acquisition is the biggest cost and insurance companies are terrible at it because differentiation is almost impossible in a price driven by extreme price war.

It’s not uncommon that 30-50% of your travel insurance premiums are going to a broker or price comparison website. Talking about great value.

It’s not as sexy as ML in claims but one of the big innovations Lemonade has developed is looking like the anti-insurer and creating a huge PR machine around that. True or not, it worked.

[gen220]

I’ve observed this, but I don’t think that any carrier has successfully figured out a way to grow that doesn’t involve brokers (digital or physical). They have a death grip on the market, with a very high percentage of potential members held behind their gate.

Like you, I’m not convinced that the value they add to the chain justifies their expense, but they’re legally and economically entrenched.

My only hypothesis for their eventual dissolution is that unit commissions will get smaller and smaller over time, as more brokers use tech to manage bigger books of business with lower employee headcount requirements, and brokers become more indistinguishable from carriers.

Or maybe some consortium of carriers will get together to build THE comparison shopping site, like healthcare.gov, and offer some ridiculous bonus payment to you the member for shopping there.

[Phillipharryt]

Decision trees are a type of Machine Learning, no need for the quotation marks.

[junipertea]

Maybe they meant chaining if statements

[gen220]

Yep, this is what I meant. The "first generation" of these engines were written in COBOL, and are quite nasty by modern standards.

Most people in the tech industry don't apply the ML label to these kinds of software. However, there is a ton of knowledge invested in these systems: certainly more than any one currently-living human has in their head.

A more apt, though out-of-fashion label might be "expert system": https://en.wikipedia.org/wiki/Expert_system

[HenryBemis]

I've been contracting with a mega-big insurance company for a few years. From discussions with fellow contractors in siimlar-sized insurance companie, we all tend to reach the same conclusion..

Ιmagine a spaghetti code. Now think of an IT eco-system that has grown with half-baked interfaces, patches, MANY MANY MANY MANY spreadsheets, legacy systems (and I mean having MS Server versions 10+ years old), and nobody dares to change passwords because there will be pain.

Now imagine that a mega-big insurance is growing by M&A, and it becomes mega-big by absorbing other companies, (speghetti-zed) IT eco-systems, and they try to absorb processes and data with even more spaghetti-ish manners. One sneeze and the world is coming down...

Now consider a new, modern company that has the talent, and none of the inheret problems/risks. They may not be mega-big (yet), but they got the potential to slowly steal chunks of the market, only if/the grow clean, fresh, and organically.

In the UK it's a (growing?) trend to have your app on someone's phone, tracking motion from the phone's sensors (accelerometer, GPS/speed, etc.) and they can give you lower premiums. The possibilities are endless... as long as they are modern enough.

[pionar]

I'm not sure what's in it for me as a consumer. I did a quote with them a couple weeks ago, and even with all the "discounts", it came in at almost double the premium with worse coverage.

[0xffff2]

I just checked, and for my apartment they come in at about half of my current renter's insurance for similar coverage. Maybe it's highly dependent on location, or maybe I'm just way overpaying for renter's insurance. Unfortunately for them, switching away from the bank that already handles 95% of my finances isn't worth saving $100/year.

[deeg]

(Keep in mind that I am just an engineer and don't deal directly with policies.)

My understanding is that it is generally considered that renter's insurance is too high at most large carriers. There are historical reasons for this which I won't go into (and I don't understand all of them anyway). The carriers don't change this because:

1) Lowering renter's insurance premiums would require raising premiums elsewhere (e.g. homeowners). Raising rates causes customers to leave.

2) Renter's insurance is fairly cheap as it is and people don't price-shop all that much.

3) Shifting premiums brings regulatory scrutiny and you have to do it right (and legally). It's not worth the hassle.

I think Lemonade started largely with renter's insurance to take advantage of that gap. It's one of the things that put fear into the major carriers.

Before I started working in the business space I knew almost nothing about insurance (and didn't care). It's been fairly interesting and I have more empathy for the carriers than I used to; they aren't quite the blood-sucking maggots that some maintain.

[itsoktocry]

>Maybe it's highly dependent on location, or maybe I'm just way overpaying for renter's insurance.

Or maybe Lemonade is like many other "tech" companies, and is selling their product below costs in the hopes of growing into profits. From a consumer standpoint, gambling with your insurance in such a manner is scary.

[tharne]

> Or maybe Lemonade is like many other "tech" companies, and is selling their product below costs in the hopes of growing into profits.

This is exactly what they're doing. Take a look at their losses from claims. Brilliant marketing though, especially for an insurance company.

[zerni]

Given the relatively small size of their book, a few outlier claims can destroy all their economics. It should regulate over time.

[1123581321]

It’s unlikely the estimate varied much from what other insurers would offer you, assuming you were comparing the same building materials and coverage. If Lemonade were so expensive, their loss ratio from the S-1 would be much better and they’d have fewer customers.

(Anecdotally, they are offering me about 95% of what I pay Geico for similar coverage, and without the auto insurance discount.)

[phonon]

Renter's insurance doesn't cover the building.

[1123581321]

Right, which means I was quoting homeowner’s insurance. Renter’s insurance is priced closer to the possessions replacement portion of homeowner’s.

[petra]

So from your insider vantage point, how will the insurance job market look in 5-10 years ? What jobs, if any, would be left ?

[deeg]

I don't work directly for insurance companies so I am not a good judge of what jobs will be around. I would expect that any job that deals manually with claims--line entry, price evaluation, even fraud detection--will decline, maybe a lot. However, I don't see them going away entirely--there are just too many anomalies and the data you're dealing with is too dirty. That's not sticking my neck out too much; you can say pretty much the same thing for any broad industry. :)

I assume that Lemonade is banking on doing away with almost all manual processing so they're ideas are different from mine.

[gen220]

I think we’ll see the insurance market transform in a similar way that we’ve seen the financial services market transform. Although, it will go in slow motion, since the gains in insurance aren’t as immediately-accruing as they were in equity and credit trading.

You’ll see the same kind of jobs that exist today, but they will be smaller in number, and way less paper-oriented.

[grvdrm]

Many. Insurance is hardly one type of job and many lines of insurance (e.g. for larger multi-national corps, for certain types of property, and etc.) aren't automated anywhere near the level of what you see in Lemonade's marketing/website/systems.

[ianai]

It also seems they may see this filing as a way to reinforce their marketing as a “good” company that directs funds where they say they do. I could imagine them telling their customers to buy their stock as a way to be involved with how they operate.

[toomuchtodo]

What happens when regulators require disclosure of claim handling ML models, as they already regulate insurance rates?

[watchyourML]

Regulators are starting to lean in on ML rules and requirements. They can't hire data science experts to keep up with competitive demand and salaries, so they are going to require companies to make their ML-based outcomes accessible/auditable. Claims, pricing, risk modeling, underwriting - we're in the early days of companies using ML for these tasks.

[phonon]

They've been doing it a long time... https://consumerfed.org/reports/low-ball-an-insiders-look-at...