Wall Street has a history of people doing sketchy things through email before they up and quit. Several software engineers have been busted for taking proprietary code from one financial firm to another. And then there’s Morgan Stanley’s Galen Marsh, who was fired in January for pinching data from as many as 350,000 wealth-management clients before the firm got wise. Actions like this won’t ever occur again if a few security startups have their way.
The idea is built on predictive analytics: software that reads your email and identifies which sites you visit, and then develops a baseline user profile to detect when you stray away from the norm, like downloading documents from a database that you rarely use, according to a new report by Bloomberg.
One company installed their software within an unnamed financial exchange and identified six people who were preparing to leave with sensitive data in just the first 30 days. Those six people changed their email habits in one way or another.
Then there are other, much creepier ways to analyze employees that aren’t necessarily always designed to predict crime. Rather, they simply identify the fact that someone may be prepping to quit. Another firm, which is “careful when discussing the software,” provided a scenario where a star trader is disappointed with their bonus and aims to leave, possibly with the intent to take other staffers with them, for example.
The software can “identify discontent” through behavioral and linguistic analysis, according to Bloomberg, which sounds an awful lot like reading your emails, only it’s a piece of software not someone in HR. The algorithm can even look for specific red flags related to financial stress, like “late rent” and “medical bills.”
While none of the companies that currently utilize this brand of software were identified, nearly every example involved the financial services world. The chief scientist at one of the firms was a former security executive at Bank of America.
So, if you are about to quit your job, don’t change your behavior. Or better yet, act completely random from the start, emailing yourself in different languages and downloading e-books on ancient farming techniques. Keep the algorithm on its heels.
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