AI in investment banking is emerging as the next big thing in the known digital era.
Finance will be one of the industries that experiences significant disruption.
Asset management is the sector that AI is most likely to change, with theories suggesting that managing portfolios could soon become a robot’s routine activity.
Although automation is a hot topic in the asset management industry, there has been little discussion of how AI will work in investment banks. The following essay demonstrates the benefits and challenges of AI in the world of investment banking.
Corporate finance (which most clients prefer to traditional investment banking) and research are the three operating segments that comprise investment banks. When AI changes the investment banking industry, it will have an impact on all three categories.
Through data analysis, ease of use, and economies of scale, AI could help make things more efficient and save money.
Artificial Intelligence’s Benefits for Investment Banking Sector Adoption
Salespeople will be replaced in the trading and sales departments by digital assistants who can communicate with customers just as well as people. Natural language processing (NLP), a computer programme’s ability to understand human speech, will largely eliminate conversational, client-facing sales work in investment banks.
With the introduction of AI, which is expected to deliver high speed and additional precision in completing transactions by the second, traders risk becoming obsolete.
Over the last few years, the front office sales and trading workforce has shrunk by 20% to 30%. AI does not need to rest like traders because it is constantly waiting for its next task to be completed. Data mining can alert traders when new investment opportunities for their clients arise.
The majority of an investment bank’s operations are handled by its corporate finance division.
This department frequently works with a large number of corporate and institutional clients who require high-quality work to be completed in a timely and accurate manner for a wide range of transactions such as mergers and acquisitions, initial public offerings, and restructurings.
The massive amounts of data that interns and analysts in the field of investment banking must manage should be instantly available for sorting with the use of AI.
AI can extract documents such as analyst reports, SEC filings, conference calls, press releases, and management presentations with the touch of a button or, better yet, a voice command. On average, analysts can spend up to 1.5 hours per day looking for internal papers.
By using sophisticated keyword interpretation techniques when searching, AI can reduce the time it takes analysts to put together pitch books and figure out how much a company is worth.
The research division can fully utilise the value of artificial intelligence systems by facilitating greater public access to information.
However, because we are a sell-side firm, the issuing investment bank is frequently favoured in the papers we provide to buy-side firms.
Equity or fixed income analysts will exercise extreme caution when producing reviews of their corporate clients’ stocks or bonds.
Management will want to maintain a cooperative and long-term relationship with customers who have used its services frequently.
The research team may use artificial intelligence systems to automate fundamental financial processes and accelerate the generation of objective investment advice.
Because management is constantly under pressure to reduce costs and increase returns in the near future, AI adoption in investment banking is likely to accelerate.
In recent years, investment banks have outsourced to lower-cost locations the tasks involved in gathering and analysing data on clients and transactions.
When AI is widely used, at least in the banking industry, these jobs will be automated. Approximately 4,000 investment banking jobs are expected to be eliminated by 2025.
However, we can expect a rise in positions involving technology, such as programming and data analysis.
AI supports the three main services provided by investment banks, which also reduces the work involved in complying with rules and following compliance procedures.
Anti-money laundering (AML) teams, for example, will be unnecessary when AI is used because the technology can detect shady financial transactions and ensure that consumers aren’t moving around shady cash.
AI also provides the benefit of biometric identification. The use of biometrics for document signing by bank officials is now required indefinitely.
Because of fingerprint identification or eye recognition technology, the way authorities create policies, reports, and other documents produced by their subordinates may change.
AI Adoption Challenges in the Investment Banking Industry
It would be a mistake to believe that AI will soon replace analysts. Human relationships and choices are simply too complex for machines to learn.
At this point in AI research, relying solely on computers to manage operations, analyse data, and make decisions would be extremely risky.
Machines, like humans, require training before they can function properly for an extended period of time.
Human supervision will become increasingly important as the machines gather information and face challenges. If humans rely solely on AI’s analytical capabilities, a simple misreading of a signal could cause a stock market crash.
Testing and validation scenarios are required to fully realise AI’s potential.
Despite the fact that many of its capabilities have yet to be fully realised, industry experts have identified opportunities for the next generation of artificial intelligence systems.
When the AI overhaul begins, it will not be surprising to see an improvement in the performance of investment banks. The “too big to fail” banking institutions will use AI to relive their glory years prior to the 2008 financial crisis.
We’re talking about more efficient data collection, which can go from hours to seconds. Thanks to artificial intelligence, investment bankers are now better equipped to focus on the deals themselves rather than the enormous amounts of tedious work.
Given all of the benefits AI has to offer, its adoption appears to be unavoidable. Investors must understand that greater rewards come with greater risks.
Always consider the costs associated with any benefits. We can all agree that the use of AI may result in fewer Wall Street jobs and a decrease in the need for human
In the year 2000, Goldman Sachs’ cash equity trading desk employed 600 traders.
With automation handling the labour-intensive tasks, only two traders remain at the desk.
Those who see this trend as disruptive will see it differently than those who see it as an opportunity for digitalization and personal development.
Conclusion
The key question is who will be better able to adapt to the ever-changing investment banking environment. This could imply that you need to recruit new talent that is relevant to the future labour market.
To reap the benefits of your labour, you must take advantage of AI’s potential.
Please contact us if you want to learn more about implementing AI in the investment banking industry. It would be great to hear from you!
