If there is any area where AI is going to increasingly find deployment, it is in the financial markets. AI had already its way into the market, albeit in a rudimentary format with the high frequency trading systems which run the trading algorithms of institutional brokers. Increasing sophistication and deployment of this technology will have far-reaching ramifications for the industry, and aspects of these are discussed below.
How AI Will Revolutionize a Traders’ Job
We can look at this issue in terms of the core trading functions, as well as the impact on the labor market.
- AI and Core Trading
Institutional traders are continually getting better at trumping retail clients in all financial markets dealings. The numbers speak for themselves. A study of the trading outcomes of firms such as Goldman Sachs and JP Morgan will absolutely blow the minds of anyone analyzing their profit numbers. These astounding trade results are delivered handsomely by the legion of trading algorithms that power their systems. By taking away the trade executions from humans and placing it into the hands of AI-driven algorithms, institutional trades are getting faster, smarter and more sophisticated.
Retail traders are playing catch-up as they mostly cannot afford these AI-driven setups. Take the example of news trades. How effective can a human being be at receiving, analyzing and then trading the news? This is a difficult proposition. That is why the typical retail trader who wants to trade the news will always see the initial spike hitting the charts even before he or she can react to the numbers. No matter how hard a retail trader tries, there is simply no way to beat the machine-learned algorithms of the institutional trading firms.
The reality is that machine-based trading is the way into the future. Any retail trader who wants to change trading outcomes from a technological perspective will simply have to make some form of investment into artificial intelligence to bridge this ever-widening gap. We will see firms coming into the retail space to offer AI-driven robots which are capable of analyzing and reacting to the news in milliseconds, and offering these for outright sale or on a lease-only basis to end-users. A similar product for the crypto market is already in beta testing. It is also expected that institutional trading setups will be seeking for ways to improve their existing systems.
- AI and Employment Within the Industry
As far as the employment market in the trading industry is concerned, AI is going to cause a disruption. Institutional traders may find out that many of their existing roles may gradually be taken over by AI-driven systems, which could cause a major seismic shift in employment patterns in the industry. As these systems take up more complex functions such as risk analysis, market scans and core trading functions, we could see a massive reduction in the existing workforce in the investment banks and other institutional firms. There may be a skills demand shift, as the market may start to require that traders possess additional skills in AI to continue to remain relevant.
How AI Will Revolutionize Financial Regulation
AI-based technologies have the potential to pose challenges for regulators across the world. The difference in opinion among regulators regarding the regulation of cryptocurrencies is an example of how financial services regulators are typically unprepared for the entrance of emergent technologies such as AI and the blockchain. Regulators will find themselves having to deal with a number of issues that have been thrown up by the emergence of AI in the financial services space.
- Will the use of technologies such as AI which give certain players a competitive advantage over others negate the principle of transparency?
- Can AI-based systems be used to circumvent current fraud detection systems that are being used by regulators and compliance agencies?
- Will the use of AI lead to breach of privacy laws, owing to the large amounts of data required by these systems to arrive at decisions?
- Will AI undermine current regulatory frameworks?
AI-driven systems will challenge the traditional regulatory frameworks currently operating in the financial markets. Regulators may find themselves in a position where they may have to adapt AI-driven systems in their work, or formulate brand new regulatory frameworks that will among other things, determine to what extent AI should be used by participants and brokers in the financial markets.
How AI Will Revolutionize Portfolio Management
Portfolio management and brokerage-dealing operations will be impacted by AI in several ways. AI could be used to develop so-called Intelligent Portfolio Management Systems (IPMS), in which AI-based algorithms are able to construct client-specific investment portfolios using the trader’s demographics, risk preferences and other relevant information. Construction of such portfolios requires the use of large amounts of data, which is where an AI-driven system offers superior capacity to that of the human mind.
Technical analysis of the financial markets relies on three premises, one of which is that history repeats itself. This is the basis of many charting techniques and the process of analysis requires the use of significant amounts of data. In some cases, up to 20 years of price data may have to be analyzed and used to produce an algorithm that can identify such repetitive patterns. How effectively can the human mind analyze such large data packs without the element of fatigue or emotions setting in?
This is the stuff that AI thrives on: the ability to rearrange and analyze structured and unstructured price data which can then be used to design trading strategies. When asset selection and allocation is an additional objective, AI has the potential to deliver for the portfolio manager.
AI in portfolio management is an idea whose time is here and we will see this technology being used increasingly by providers in this industry.
Conclusion
The door was opened for AI when the big banks and institutional firms started to hand over their core trading functions to the computer-based algorithms. AI-based trading systems are therefore the next generation of algorithmic trading. We will also see AI being increasingly used in portfolio management.
The challenge will lie for the workforce in these firms as well as for regulators. To what extent will the human-AI interaction play out in terms of employment, and can regulators devise ways of harnessing the power of AI in their work, as well as formulate new regulatory frameworks that address how AI-based systems are used by market players? These issues will continue to dominate discussions around the topic.
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