As the buy-side grapples with higher costs, fee compression and ever-increasing regulation, TORA’s Software Director Pascal Kuyten looks at why many industry participants are turning to Artificial Intelligence (AI) and machine learning technology to imbed further efficiencies in their trading processes.
AI and machine learning have been used by the sell-side for a long time to automate menial tasks performed by sales traders. Buy side participants are now starting to use these technologies in a variety of additional ways, such as creating new processes for price, liquidity discovery and execution algos. More recently, AI and machine learning technologies have been used to improve transaction cost analysis (TCA) at a time when asset managers are legally obliged to show regulators that “all sufficient steps” have been taken to achieve best execution.
The Markets in Financial Instruments Directive (MiFID) II which went live across the Europe Union at the beginning of 2018, has further spurred on firms to explore different solutions for performing TCA as a means to improve the execution decision making process, and meet their legal requirements at the same time. Coupled with TCA becoming more deeply entrenched in the trading process, a 2018 report from consultancy Aite Group entitiled ‘MiFID II Best Execution: Multi-Asset-Class TCA Goes Mainstream’, revealed that AI and machine learning technologies are
emerging trends that will continue to galvanize the investment sector.
“The use of AI will continue to influence the TCA space. Firms with the budget, staff, and technological resources to make the investment into AI will automate the aggregation, cleaning, and analysis of more and more data for the purpose of research cost analysis,” said Aite’s senior research analyst Audrey Blater in the report.
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