Banks, asset managers weigh trade-offs in third-party tools for machine learning
Although many banks and asset managers still prefer to build models in-house, off-the-shelf products are maturing.
“Build versus buy” is an age-old conundrum in most aspects of financial services enterprise technology. That is no less true for emerging technologies like machine learning than it has been in other, more traditional parts of firms’ tech estates. While off-the-shelf products have improved hugely, and no- and low-code platforms promise to make building models a breeze, many organizations still prefer to build their own algorithms and models.
Andy McMahon, machine-learning engineering lead at
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