<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>deeg</author><text>I&amp;#x27;m tangentially involved in the insurance space and I believe Lemonade is trying to use machine learning to process claims because:&lt;p&gt;- Processing claims with humans is expensive; every step that can be accomplished by a computer will probably be cheaper.&lt;p&gt;- A claim processed via ML will probably be handled fast.  A fast response = happy customer, which helps with retention.  This is a big one.&lt;p&gt;- 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.&lt;p&gt;- Younger generations are more used to working with a web pages and will likely look at humans (e.g. agents) as old-fashioned.&lt;p&gt;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&amp;#x27;s hard to see how they&amp;#x27;ll make the numbers work, as their current losses show.  Most of the carriers are trying to implement something similar (which is where I&amp;#x27;m slightly involved).</text><parent_chain><item><author>afwaller</author><text>You only make insurance cheaper by charging risky people more.&lt;p&gt;Right now it is mostly laws that protect categories of people that keep insurance companies from charging people more.&lt;p&gt;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?</text></item></parent_chain></comment><story><title>Lemonade files S1</title><url>https://www.sec.gov/Archives/edgar/data/1691421/000104746920003416/a2241721zs-1.htm#bg40510a_main_toc</url></story>
<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>gen220</author><text>At most big old and public insurance companies, claims payable represents a significant chunk of expenses, but not even close to 100% (it&amp;#x27;s closer to 60-70%). The rest is, generally, &amp;quot;administration&amp;quot; (humans processing papers, and managing humans processing papers, in cushy offices).&lt;p&gt;This is where better technology can result in lower costs. It&amp;#x27;s a volume&amp;#x2F;unit-cost game. Their unit cost per person is maybe a few cents or a few dollars cheaper, but at huge volumes it makes a big difference.</text><parent_chain><item><author>afwaller</author><text>You only make insurance cheaper by charging risky people more.&lt;p&gt;Right now it is mostly laws that protect categories of people that keep insurance companies from charging people more.&lt;p&gt;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?</text></item></parent_chain></comment><story><title>Lemonade files S1</title><url>https://www.sec.gov/Archives/edgar/data/1691421/000104746920003416/a2241721zs-1.htm#bg40510a_main_toc</url></story>