Artificial Intelligence: What It Means for the Future of Investment Banking
“Hey Siri, how’s the weather today?” I said as I woke up from a good night sleep ready to start off my day. Siri responded promptly with the temperature range that ‘she’ probably drew from the Apple Weather app. A seemingly basic interaction that came off natural to us today is actually one of the simplest application of Artificial Intelligence (AI) out there. AI is made up of algorithms that work together to formulate meaningful responses and actionable insights. Of course, we have all heard about automation, the idea of making things work by itself as if they were robots. Artificial Intelligence encompasses more than just automation. Machine learning is an extended form of automation that stems from the experiential learning abilities of AI to remember all the steps that were performed by users without being explicitly programmed; it is continuously bound to improve decision-making with more data raked in.
Artificial Intelligence is a coming-of-age and tipped to be the next big thing in the digital era that we know now. One of the areas that will be largely affected is Finance. Asset management is the industry most likely to be confronted by AI and there has been a lot of speculation suggesting that managing portfolios will soon become a robot’s routine job. While automation in the asset management space is a prevailing topic, there has not been much discussion on how AI will play its role in investment banks. That said, this article weighs the pros and cons of AI creeping its way into investment banking.
Investment banks are typically made up of three operating arms: Sales & Trading, Corporate Finance (most people would refer this to traditional investment banking) and Research. When AI takes over investment banking, it will impact all three areas. AI should enable greater efficiency and cost savings through powerful interpretation of data, ease of use, and economies of scale.
In the Sales & Trading department, we will soon witness salespeople being replaced with digital assistants who are able to interact with clients as fluid as normal humans. Natural Language Processing (NLP), the ability of computer programs to understand the human speech, will play a big part in eradicating conversational, client-facing sales roles in investment banks. Traders can become obsolete with the arrival of AI, which is set to offer high-speed and ultra-precision in executing trades by the second. In fact, there has been a 20%-30% reduction in the front office sales and trading headcount over the past few years. Unlike traders, AI does not need to rest or take a potty break, it is always waiting to perform its next job. Data mining can also provide traders with alerts about new investment opportunities for their clients as they unfold.
The Corporate Finance department is what usually composes the majority of an investment bank’s businesses. Ranging from mergers and acquisitions, IPOs, and restructurings, the Corporate Finance department often have to deal with a large number of corporate and institutional clients who wants high-quality work to be done very quickly and accurately as well. With the arrival of AI, the massive amounts of data that investment banking analysts and interns have to collect should be available to sort from in a nick of time. AI can pull up gazillion analyst reports, SEC filings, conference calls, press releases, and management presentations all in one push of a button or even better, a voice command. Searching for internal documents can take up 1.5 hours a day on average for analysts. Using advanced interpretation of key words when performing searches, AI can reduce the time that analysts spend on modeling company valuations and making pitch books.
The Research department can realize the true value of artificial intelligence systems through improved accessibility of public information. However, as a sell-side business, the reports generated for buy-side firms tend to be biased towards the issuing investment bank. Equity or fixed income analysts will be very cautious of writing negative commentaries about their corporate clients’ stocks or bonds; management wants to preserve harmonious and long-standing relationships with clients who have been using its services regularly. The Research team can harness artificial intelligence systems by automating basic financial processes and facilitating the creation of neutral investment recommendations.
With intense pressure coming from management to slash costs and maximize returns in the near-term, the movement of AI into investment banking will likely be hastened. In recent years, investment banks have moved jobs associated with compiling and checking data on customers and transactions offshore to lower-cost countries. When AI become mainstream, at least among banks, those jobs would be automated. It is expected that 4,000 investment banking jobs will disappear by 2025. However, we would expect to see an increase in technology-related jobs such as data analytics and programming.
Not only does AI help with the three main services within investment banks, it also eases the burden of compliance and abiding to regulations. For instance, anti-money laundering (AML) teams will no longer be necessary when AI takes hold because AI would be able to detect suspicious financial transactions and ensure no dirty money is being circulated by their customers.
Another potential that can be derived from AI is biometric identification. Bank authorities have forever been asked to sign papers but the use of biometrics such as fingerprint identification or eye recognition can transform the way that authorities approve policies, reports, and other documents created by their subordinates.
We should not expect AI to replace analysts anytime soon – there is simply too much nuanced human interactions and and judgment calls for the machines to learn at its current development phase. At this stage in the development of AI, relying entirely on the machines to handle processes, conduct analysis, and make decisions is going to be very risky. Just like humans, the machines have to undergo training for some time before they can actually perform as they are designed. Human supervision will prove to be key, as the machines ingest data and learn from their intricacies. Without humans, they would rather be called Artificial Stupidity. Something as small as a misinterpreted signal could cause the stock market to collapse if people are to act upon AI’s analytical capabilities alone.
Running tests and validation scenarios will be crucial to stretch AI to its full potential. Many of its abilities are yet to be unlocked, but experts in the field are already identifying opportunities for the next wave of Artificial Intelligence systems. It won’t be surprising to see a rebound in the performance of investment banks when the overhaul by AI begins. The “Too Big To Fails” will be looking to AI to bring them back to its promising days before the financial crisis of 2008. We are talking about how much more efficient gathering data might be, from hours to mere seconds. Artificial Intelligence can shift the center of gravity, allowing investment bankers to focus more on the deals rather than the never-ending piles of grunt work.
The emergence of AI is inevitable; given all the benefits it can offer. Investors should understand that higher returns comes with higher risks. Whenever there are benefits, you will always find its associated costs. We can relate to the fact that AI is reducing the need for human labor and prizing jobs away from Wall Street. In 2000, Goldman Sachs’s cash equities trading desk consists of 600 traders. Today, there are only two traders left on the desk with machines doing the bulk of the work. Some will view this phenomenon as a disruption and some will see this as an opportunity for digitalization and personal growth; it boils down to who will be better equipped to adapt to the changing landscape of the financial services industry. This might mean having to learn new skills that will be applicable to the future job market. It is up to us to embrace AI’s potential and reap the fruits of our efforts.
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Wiseberg Teddy contributed to this article.
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