Wall Street is looking towards Silicon Valley for a more automated environment and a tech-driven approach.
A July 2016 report by CB Insights showed that 41 startups may be introducing AI to fintech. Of the many big names, Goldman Sachs remained dominant in backing as many as four companies that use AI in financial technology. As many as 658 AI deals were closed and $5021 billion was spent on funding the AI startups in 2016, according to the report.
With total AI investment gaining momentum across different industries, an increasing number of companies are branching out to offer a variety of services that range from credit scoring to regulatory compliance and fraud detection.
In February 2017, Japan Exchange Regulation and Tokyo Stock Exchange, Inc. announced that they are working towards implementing AI in market surveillance operations, using technologies developed by NEC Corp and Hitachi, Ltd. Preliminary tests showed that AI solutions accurately identified the possibility of unfair trading. So far, conventional surveillance processes involved personnel who manually identified unfair trading patterns and then performed preliminary investigations. With machine learning, this process will make it easier for exchanges to identify abnormal patterns or even detect a slight possibility of unfair trading. AI will do this on its own from the voluminous amount of data, eventually leading to more efficiency in real time. However, the final decision in unfair trading investigations will continue to be made by surveillance personnel.
As stock exchanges introduce AI to detect patterns of trading frauds, hedge fund firms are gearing up for the next revolution through application of advanced AI algorithms in trading.
Hedge funds are looking at deep learning, which allows AI systems to adapt to changing circumstances. Deep learning, an extended wing of AI, allows trading firms to analyze large patterns of data and look for possible permutations to increase returns and reduce risk. Deep learning uses channels like social media behavior on Twitter, Facebook, and additional news stories to connect data points and make market predictions.
Last year, the Wall Street Journal reported that the world’s largest hedge fund firm, Bridgewater Associates LP, was looking at artificial intelligence to automate the management of the company, potentially running tasks such as hiring, firing, and decision-making through software. According to the Journal, David Ferrucci, one of the leading developers on one of the most advanced AI systems in the world, IBM’s Watson project, runs the project.
But while little is known about Bridgewater Associates’ potential project, other implications of AI in trading activity is quite evident.
A San Francisco-based firm, Sentient Technologies, uses AI to evolve and optimize investment strategies through its subsidiary, Sentient Investment Management, which is run by senior executives from both Wall Street and Silicon Valley. The purpose to employ AI for investment purposes is to continuously process and learn from endless stockpiles of data using the world’s most powerful distributed artificial intelligence system and develop new investment strategies that differ from other human and machine-guided strategies.
Guided by machine learning and distributed computing, financial technology firm Two Sigma boasts of not being “your typical investment manager” by applying a scientific approach to investment management. The firm currently trades forex, derivatives, trade equities, and futures in 40+ countries and uses diversified systematic strategies in the global financial markets.
A machine intelligence system named Emma AI aims to outsmart humans through advanced machine learning to operate autonomously in the field of wealth management, financial analysis, and research. According to a report in Recode, Emma’s creator, Shaunak Khire, believes the system of neural nets will consider complex situations like shift in management and geopolitical risks.
Another large firm, Hong Kong-based Aidyia, trades in U.S. equities and can take inordinate amount of data sets. It is continuing to work on developing intelligent software that can function independent of human interaction.
But while the AI disruption sounds enticing, its use in financial industry comes with a word of caution. Replacement of human jobs, such as financial analysts, asset managers, and hedge fund managers, is one of the most common worries across industries that are looking to rely on artificial intelligence.
For more on this topic, see The Role Of AI In Financial Trading—It’s Not What You Think.