The Rise of AI in the Investment Banking Industry [Benefits and Challenges]

Artificial Intelligence is emerging in the digital era that we know now, expected to be the next big thing. One of the fields that will be largely changed is finance. Asset management is the industry most likely to be transformed by AI, with theories implying that managing portfolios will soon become a robot’s usual task. While automation in the asset management sector is a predominant topic, it hasn’t been discussed how AI will operate in investment banks. That being said, this article shows the benefits and challenges of AI in the investment banking industry.

Investment banks consist of three operating divisions: sales and trading, corporate finance (most clients would choose this over traditional investment banking), and research. When AI transforms investment banking, it will affect all three areas. AI should facilitate greater efficiency and cost savings through a robust analysis of data, ease of use, and economies of scale.

The Benefits of the Adoption of AI in the Investment Banking Industry

In the sales and trading department, we will soon see salespeople being replaced with digital assistants who can communicate with clients as easily as humans. Natural Language Processing (NLP), a computer program's capability to interpret human speech, will play a significant role in eliminating conversational, client-facing sales tasks in investment banks. Traders can become outdated with AI implementation, which is set to provide high-speed and extra precision in performing trades by the second.

There has been a 20%-30% decrease in the front office sales and trading headcount in recent years. Unlike traders, AI does not need to rest because it is always waiting to perform its next task. Data mining can also alert traders about new investment opportunities for their clients as they unfold.

The corporate finance department composes the majority of an investment bank’s businesses. From mergers and acquisitions, IPOs, and restructurings, this department often deals with many corporate and institutional clients who require high-quality work to be performed in a short period of time and with precision. With AI implementation, the extensive amounts of data that investment banking analysts and interns have to handle should be available to sort from immediately.

AI can extract numerous analyst reports, SEC filings, conference calls, press releases, and management presentations, all with a click of a button or, even better, a voice command. Looking for internal documents can waste up to 1.5 hours a day on average for analysts. Applying advanced interpretation of keywords when conducting searches, AI can decrease the time analysts use to create company valuations and develop pitch books.

The research department can leverage the true value of artificial intelligence systems through increased accessibility of public information. However, as a sell-side company, the reports created for buy-side businesses tend to be biased towards the issuing investment bank. Equity or fixed income analysts will be very circumspect of writing negative reviews about their corporate clients’ stocks or bonds.

Management will want to maintain cooperative and durable relationships with clients who have been employing its services regularly. The research team can leverage artificial intelligence systems by automating basic financial operations and expediting the creation of neutral investment recommendations.

With ongoing pressure coming from management to reduce costs and increase returns in the near-term, AI's implementation into investment banking will likely be expedited. In recent years, investment banks have transferred roles associated with collecting and examining data on customers and transactions offshore to lower-cost regions.

When AI is mainstream, at least in the banking sector, those jobs would be automated. It is predicted that around 4,000 investment banking jobs will be eradicated by 2025. However, we should expect to observe an increase in technology-related roles such as data analytics and programming.

Not only does AI support the three primary services within investment banks, but it also reduces the burden of compliance and abiding by regulations. For example, anti-money laundering (AML) teams will no longer be required when AI is implemented because AI can detect suspicious financial transactions and make sure their customers circulate no dirty money.

Another advantage that AI presents is biometric identification. Bank authorities have permanently been asked to sign papers through the use of biometrics. Fingerprint identification or eye recognition can transform the way that authorities establish policies, reports, and other documents generated by their subordinates.

The Challenges of the Adoption of AI in the Investment Banking Industry

We should not assume that AI will replace analysts anytime soon. There are simply too many nuanced human interactions and decisions for the machines to acquire at their current development phase. At this stage in the development of AI, depending solely on the machines to manage processes, lead analysis, and make judgment calls will be very dangerous.

Like humans, the machines have to follow training for some time before performing as they are designed. Human supervision will prove to be indispensable, as the machines collect data and learn from their difficulties. Something as small as a misinterpreted signal could lead to a stock market collapse if people act upon AI’s analytical abilities alone.

Running tests and validation scenarios will be essential to reach AI's full potential. Many of its capabilities are yet to be leveraged, but experts in the field already recognize opportunities for the next wave of Artificial Intelligence systems.

It won’t be unusual to experience a rebound in investment banks' performance when the AI overhaul starts. The “Too Big To Fail” banking companies will be adopting AI to bring them back to their golden days before the financial crisis of 2008. We are talking about more effective gathering data, from hours to mere seconds. Artificial Intelligence enables investment bankers to focus more on the transactions rather than the immense piles of hard work.

The adoption of AI is unavoidable, given all the benefits it can provide. Investors should recognize that higher returns come with higher uncertainties. Whenever there are advantages, you will always find its associated costs. We can admit that AI may reduce the need for human labor and decrease the number of Wall Street jobs.

In 2000, Goldman Sachs’ cash equities trading desk was holding 600 traders. Today, only two traders are left on the desk with machines doing the heavy lifting of the work. Some will perceive this trend as a disruption, and some will recognize this as a chance for digitalization and personal growth.

Bottom Line

It boils down to who will be better equipped to adapt to the investment banking industry's changing environment. This might imply having to acquire new skills that will apply to the future job market. It is up to you to leverage AI’s potential and enjoy the result of your efforts.

If you want to know more about integrating AI in the investment banking sector, don't hesitate to contact us. We'd love to hear from you!