With the hiring of data scientists, advances in cloud computing, and access to open source frameworks for training machine learning models, AI is transforming the trading desk. Already the largest banks have rolled out self-learning algorithms for equities trading.
Given the market’s resiliency and traders working from home during the COVID-19-fueled volatility, some market observers have questioned the centralized trading desk mentality that has been pervasive on Wall Street.
Increasingly banks are turning to the field of natural language processing (NLP) and machine learning to extract valuable information from voice, documents, and audio to boost productivity on trading desks. It’s all part of a broader push to gain efficiencies by training machines and bots to analyze language, capture insights, and replace manual tasks and drive workflows further downstream.
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