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So you thought you'd walk into a machine learning job? Bad luck.

Banks say there's no shortage of machine learning talent

Everyone's getting into machine learning but it's a busy field already

If you thought taking a few machine learning courses on Udemy might be enough to inure you against future unemployment then yesterday's report on machine learning in financial services from the Bank of England and Financial Conduct Authority (FCA) will come as a bit of a shock.

The report is based on a survey of 106 banks and finance firms in London. It turns out that, yes, machine learning is being used in banks. But, no, it's not hard to find anyone to fill the roles and that this is the least of the worries as machine learning is rolled out across the finance sector.

Machine learning is coming for jobs in risk and compliance 

The charts below, from the report, show where machine learning (ML) is already most in use in the banking sector (defined as building societies, international banks, retail banks, UK deposit takers, and wholesale banks) and in the investments and capital markets sector (defined as alternatives, corporate finance firms, fund managers, principal trading firms, wealth managers and stockbrokers, and wholesale brokers.)

They suggest that if you work in risk and compliance, your days may be numbered. Everywhere else, machine learning is still at a nascent phase. The report notes too that machine learning itself is making risk and compliance more complex - large, non-linear and non-parametric machine learning models are hard to understand and monitor, and firms are increasingly using unstructured alternative data sets to make decisions, the effects of which can also be difficult to fathom.

Machine learning talent shortages are not the issue

The Bank of England and FCA also asked survey respondents what their problems were in implementing machine learning solutions. As the chart below shows, a shortage of machine learning talent was not top of the list.

Instead, banks ranked machine learning talent shortages as a negligible constraint alongside the horror of legacy systems. Even 'investment and capital markets firms', which saw talent as more of an issue, said it was less of a problem than lack of explainability and insufficient data. 

The report's findings follow an article last month on Cathy Bessant, chief operations and technology officer at Bank of America. Bessant said there's no shortage of machine learning expertise in banks - she said it's simply a question of retraining all the brilliant technologists banks employ already....

 

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Photo by Christopher Burns on Unsplash

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AUTHORSarah Butcher Global Editor
  • Jo
    John Michael
    21 October 2019

    Most banks aren't exactly working on cutting edge projects, they're implementing other peoples' code/research. Finding someone off the street that took a couple udemy courses is easy, but finding ML engineers who can think on their feet is tough.

  • Mo
    Mohd Naved
    20 October 2019

    I agree that there is no shortage of ML/AI professionals because i can see institutes & online courses like mushrooms everywhere offering short term courses on ML/AI.
    But I believe that there will always be shortage of talented and innovative professionals in AI because at PhD level only few good researches are coming out.
    Note : I am an Assistant professor in same field.

  • Ab
    Abhilash
    19 October 2019

    The material for this article is restricted to only banking and there's no data to show how many respondents feel this way. The only data presented is related to the maturity of ML and is not related to this article. This makes the article subjective and pointless.

  • To
    Tom Z
    18 October 2019

    I work in Risk Management and I can say that we use machine learning in our work, not that machine learning is replacing us.

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