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Another obvious example is actuaries and any number of other analysts in the insurance industry. According to Google[1], actuaries earn an average of just over $97k/year. While this may not strictly be an "investing area," it's a clear target for automation.

1. https://www.google.com/search?q=actuaries




Part of the reason actuaries make so much is that they are certified and legally required to sign off on analysis, similar to the way civil engineers put their signature (and reputation) on their work. But you would be surprised how many decisions come down to "actuarial judgement", having good business sense, intimate knowledge of insurance rules and regulations...and not doing anything special with the data. Hell, some actuarial methods are the same as they were in the 70s. Data science is slowly eating their lunch in predictive modeling areas, but I wouldn't be surprised if they're still around after data science itself has been automated.

I work on a team of actuaries in a more data science-y role. Believe me, I had the same impression initially: "Can't we automate some of this stuff?". But I've since come to see their value.


It's not that actuaries will be eliminated. It's that 2 actuaries and 2 data scientists will do the work of 20 actuaries.

How many actuaries does a major insurer employ? Would they like to halve that number?


I don't know about actuaries, but I do remember there was an article lately about an insurance company in Japan that replaced hundreds of workers with IBM's Watson.

https://www.theguardian.com/technology/2017/jan/05/japanese-...


That's really interesting. In my circle of friends, most of us can't point to a single success of Watson, despite it's very publicized capabilities. This may only be a small company, but almost certainly larger insurance agencies & medical foundations must be on to this.


Actuaries have quite a high regulatory wall protecting them from other human competitors. But probably not from computers.

(I don't know about the legalities, but the laws requiring companies to have a actuary sign off on stuff probably can be satisfied by having on part time actuary shared between multiple companies sign off on computer generated analysis.)


I know in banking, regulators are satisfied with ML models making decisions about bank capitalisation, so long as the models are annually audited by an external auditor (eg. KPMG, EY)


I assume they will need to sign off on the model... I expect to see a lot of this in the future.


It's not so much the actuaries but the claims adjusters whose jobs will be automated:

http://www.inc.com/kevin-j-ryan/artificial-intelligence-repl...




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