How Bloomberg got liquidity seekers to trust its machine learning models

Recent liquidity squeezes have proved the worth of advanced models, argues the tech giant. Now the task is to explain their inner workings to machine learning sceptics

Being able to explain how machine learning models work has been a point of contention since the technology’s inception. Bloomberg is set to release further empirical metrics, at the end of this year, to bolster its liquidity models’ explainability. The metrics will initially be available via Bloomberg data feeds and featured more prominently on the Bloomberg Terminal liquidity screens later in 2024.

This is the most recent step in a long-running effort to get clients to trust so-called ‘black

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