How three years at McKinsey shaped my second startup

> Our vision at Meanwhile is to build the world's largest life insurer as measured by customer count, annual premiums sold, and total assets under management.

We think we can be bigger (more customers, more sales, more money) than all existing players.

> We aim to serve a billion people, using digital money to reach policyholders and automation/AI to serve them profitably.

We're looking to eclipse the population of any one country and we're going to use something like Bitcoin to side-step national currencies (and maybe also to avoid existing regulatory structure, not clear from the ambiguous language).

> We plan to do with 100 people what Allianz and others do with 100,000.

We believe we can automate or use AI to eliminate the need for people to actually support these billion customers.

All three of those are very bold statements/goals.

My understanding of this reputation is: This often happens at the detriment of either product quality or employee satisfaction. It's debatable if they actually have a reputation of providing value. I think short term? Maybe, albeit expensive. Long term? I'd say no.

Allianz has ~150k employees but certainly they don't all work on the term life business in the USA, they do all kinds of other insurance stuff all over the world and have hundreds of different products.

For term life specifically, there still are some pretty significant back office teams that a customer probably never interacts with directly, though. A few that come to mind:

- underwriters: you wont be able to make a decision for all of your applicants based on the info they provide you and the info you can pull from automated sources, so some number of humans are on the phone with your applicants asking clarifying questions, doing additional research, and making risk decisions. They're also routinely doing retrospective analysis that looks back on claims paid out to make sure the claims are reasonable and there's not some sort of gap in the underwriting approach thats leaving unknown risk on the table, and audits of automated underwriting decisions to make sure the rules engines are correctly categorizing risks

- actuaries: every company has varying risk tolerance for both the policies they issue and the cash they hold/invest. These people are advising on how to take risks and working with underwriters and finance people to try and figure out the financial impact of various underwriting decisions: can a product remain viable if it is purchased by a heavier balance of smokers vs nonsmokers, etc

- accountants and finance: its a capital-intensive business that requires large cash reserves and sane investment strategy for that cash, often subject to tests by regulators or industry associations and all sorts of lengthy audits

- compliance: in the US, life insurance is individually regulated by each state. Many states join the ICC Compact and agree to all follow the same rules and have a single set of regulatory filings, but you still have plenty of other states to do filings with, analyze changing requirements from, maintain relationships with regulators, respond to regulatory complaints or investigations, etc

- industry reporting: most insurance carriers participate in information-sharing programs like the MIB (Medical Information Bureau) and these memberships come with various reporting and code-back obligations. The goal is to prevent you from getting declined at one life insurer because you say you have some sort of uninsurable illness and then turning around and lying about not having that illness to another life insurer the next day. These sort of conflicting answers get flagged for manual review, someone will need to talk to the applicant and figure out why they gave conflicting info to multiple insurers and what the truth really is.

- claims and fraud investigations: many, many people lie to try and get insurance they aren't qualified for or to take out insurance on someone they aren't supposed to. Claims investigations start by asking "is the insured really dead" but then try to answer the questions like "did the insured know this policy was taken out on them", "were the responses the insured gave during underwriting truthful", etc. These investigations are extremely time consuming and often involve combing public records, calling doctors, interviewing family, and more. You'd probably be shocked how common it is for former-spouses to try and take out insurance policies without the other knowing during divorces. Some level of this investigation is happening in the first couple of years a policy is in force, too, as insurers can rescind the policy and refund the premiums if they determine it was obtained under false pretenses

- reinsurance: even the biggest insurers typically pool and share some amount of risk so that a bad claims year can't take down an entire carrier. reinsurance treaties are complex things to negotiate and maintain, and have lots of reporting obligations and collaboration between the reinsurer and the actuaries to validate the risks are what everyone thinks they are

The customer-facing part of a term life company is really just the tip of the iceberg. Small companies are certainly better at doing this with tech than bigger incumbents (thats a big part of the reason we exist at Wysh), and a narrow product focus really helps, but there's still some pretty significant levels of human expertise involved to keep it all running.

They essentially lied about any anticipated KPI potentials and let their "tech" people put together a 15k EUR/month (before public release) platform on AWS which was such a pile of mess, it made the second year's CTO start from scratch. After some heavy arguments because of their poor performance, McKinsey agreed to let some "non-technical" people work there for a couple of months for free. All arguments you'd had with the McKinsey "Engineers" felt like talking to AWS Sales, they had barely any technical insights but a catalog of "pre-made solutions" to choose from.