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Machine Learning in Financial Services

Refinitiv’s inaugural Machine Learning Survey of nearly 450 financial-institution leaders and data scientists reveals the degree to which machine learning is a key part of business strategy.

The survey shows that the devil is in the data: data quality is the biggest barrier to the adoption and deployment of machine learning. Unstructured data, as well as data from alternative sources, offers context and depth to analysis, but needs considerable work before it can be used for reliable insights. The adage ‘garbage in, garbage out’ has never been more pertinent. Overview

  • We predict that AI will be the single greatest enabler of competitive advantage in the financial services sector

  • No one is more aware of the issue of data than the data scientists tasked with creating the models and algorithms. But there is a mismatch between the vision in the boardroom and the reality on the ground.

  • There is disparity in how technologies are being adopted and used around the world. Financial institutions in the United States and Canada are the front-runners; Asian institutions are more advanced than Europe in some areas, while Europe leads Asia in others.

  • Similarly, the buy side organizations in this sample are ahead of the sell side, but what is interesting is the degree to which the sell side is advancing.


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