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"The professor said that, while tech firms started distributing data and crowdsourcing the jobs of data analysts through special tournaments, any investment challenge could be solved by an army of data scientists without financial background. 
Thus “the highest paying jobs in finance” could be put at risk, he noted, adding that asset managers could crowdsource their entire research function, while insurance companies could do the same with their actuarial models.
“Financial ML [machine learning] creates a number of challenges for the 6.14 million people employed in the finance and insurance industry, many of whom will lose their jobs - not necessarily because they are replaced by machines, but because they are not trained to work alongside algorithms,” Lopez de Prado told the сommittee".
Thus “the highest paying jobs in finance” could be put at risk, he noted, adding that asset managers could crowdsource their entire research function, while insurance companies could do the same with their actuarial models.
“Financial ML [machine learning] creates a number of challenges for the 6.14 million people employed in the finance and insurance industry, many of whom will lose their jobs - not necessarily because they are replaced by machines, but because they are not trained to work alongside algorithms,” Lopez de Prado told the сommittee".
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