How AI is Being Used at Investment Banks – Trade Processing

As part of our coverage on the use of AI in finance, CFTE takes a look and examines the impact of implementing such disruptive technology on various industry verticals. 

Some firms have made full use of artificial intelligence (AI) and machine learning to optimise the trade processing part of investment banking. AI provides banks with the ability to process huge swathes of data rapidly and accurately, allowing human managers to make data-driven decisions without having to manually sift through it.

Currently electronic routing algorithms are used to match buy and sell orders from traders to various stockbrokers, exchanges or trading systems to fulfil these orders. However, this can potentially limit liquidity for the trader, or even increase their costs. Some companies have begun using machine learning to optimise these routes using historical data as well as the opportunity cost for each execution route – for example, how much commission was paid out on a certain route. In this way, the probability of success is mapped out for each possible execution route.

One such example is Smart Chaser, a tool implemented by BNP Paribas Securities Services that utilises predictive analysis to automate trade processing. It claims 98% accuracy for its predictions, trades monitored in real-time. Users also receive a notification when a trade is likely to be rejected, suggesting alternate trading channels for speedier execution. 

With the technology learning how to improve itself, human resources can be fully dedicated to strategise instead of poring over data or other manual tasks. This allows effective decisions to be made with much more accuracy given the larger amounts of data processed to draw patterns and conclusions.

As Jean-Philippe Desbiolles of IBM Watson says in the CFTE AI in Finance course, “We are moving from a programming world to a learning one”. In the past, rules and parameters were set by programmers with software unable to distinguish changing scenarios, with new updates constantly required to keep up. With AI and machine learning, the technology improves itself with more and more data to process.

The rise of AI and machine learning does mean that job scopes will change – humans will need to upskill themselves to work side-by-side with AI in order to utilise the technology effectively. Instead of the misconception of AI rendering people jobless playing out, it will become one of the most important tools at their disposal.

The CFTE AI in Finance course has been developed in partnership with Ngee Ann Polytechnic, a leading institute of higher learning in Singapore and features high-quality content taught by five senior lecturers and 18 industry experts.

With an easy to follow format, the course is perfect for busy professionals to understand the technologies behind AI and machine learning that are disrupting finance.

Click here to learn more about the CFTE AI in Finance course.


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