Four years ago, I wrote about how tech evangelist, former Goldman Sachs CFO and current partner and vice chairman at Sixth Street Marty Chavez predicted that it will be as important for traders to know how to code as “writing an English sentence.”
At the time, Citigroup echoed Chavez’s proclamation as it announced the bank’s plan to aggressively hire about 2,500 technology professionals, including coders, engineers and data analysts, to work in the trading and investment banking departments.
The convergence of financial services and technology continues to be a growing trend, as investment banks are increasingly using artificial intelligence in their operations. It is estimated that throughout the cross section of banking, wholesale and retail, generative AI could add between $200 billion to $340 billion in value, according to McKinsey research.
How Banks Are Using AI
The securities industry is utilizing AI to automate and streamline tasks, ranging from writing code, compliance monitoring to portfolio analysis, to boost productivity and effectiveness.
Banks are developing AI-powered tools to assist bankers, traders and wealth managers in making better, more informed decisions. This includes AI-powered equity selection and real-time customer insights. Financial institutions are experimenting with GenAI models, like ChatGPT, to create content, answer questions and assist with various banking tasks.
AI can help relationship managers collect, organize and distill information to generate personalized content and insights for clients. AI-powered natural language processing and generative models can analyze data from various sources to infer market sentiment and help clients adjust their investment strategies.
The fast-emerging technology can assess and forecast exposure to risks like interest rates, credit, liquidity and default, helping banks comply with regulations like stress testing. GenAI can help draft documents like ESG and audit reports by pulling data from across the organization.
The Deployment Of AI At The Big Banks
JPMorgan
JPMorgan applied to trademark a product called IndexGPT, according to a United States Patent and Trademark Office filing by the bank in 2023. The technology is intended to select investments for customers.
Morgan Stanley
In close partnership with OpenAI, the creators of ChatGPT, Morgan Stanley rolled out last year a chatbot to assist its financial advisors and their teams. The tool, called AI @ Morgan Stanley Assistant, provides the firm’s financial advisors with lightning-speed access to a robust database of about 100,000 research reports and documents, CNBC reported. Additionally, the investment bank is developing technology that would potentially generate meeting summaries, drafts for follow-up emails, appointment scheduling and more, according to Reuters.
Wells Fargo
Wells Fargo CIO Chintan Mehta said earlier this year that Fargo, the bank’s virtual assistant app powered by Google Cloud AI, will likely be capable of doing nearly 100 million interactions per year, as his firm continues to perfect the technology.
In April 2023, Wells Fargo joined Stanford University’s Financial Services and AI Corporate Affiliate Program, which engaged more that 4,000 employees in educational training via a webinar series.
Deutsche Bank
Deutsche Bank announced a multi-year partnership with NVIDIA in 2022 to help facilitate its deployment of AI and machine learning within its business. The technology “enables traders to manage risk and run more scenarios faster and at scale while also improving energy efficiency,” the bank said in the official statement.
Goldman Sachs
George Lee, co-head of applied innovation at Goldman Sachs, divulged at the Reuters NEXT conference last year that the investment bank is currently working on numerous tech initiatives. According to Lee, Goldman’s GenAI projects include writing code in English-language commands, as well as the capability of generating documentation.
Key Ways Hedge Funds And Private Equity Are Using AI
As competition intensifies among private equity firms, they are seeking innovative approaches to identify investment opportunities. This includes leveraging AI-driven algorithms to scour diverse channels for specific criteria and effectively creating a repository of potential businesses ideal for equity funding. This helps firms proactively hunt for deals rather than relying solely on personal networks.
AI is also used to analyze data on company performance and find needle-in-the-haystack correlations and patterns in large, complex datasets, market sentiment, web traffic and social media activity to rank and prioritize potential investment targets.
The technology helps portfolio managers discover insights, analyze earnings reports, predict trends and spot fast-moving trends, which allows money managers to make more informed investment decisions. Lastly, it can simulate gaming out market conditions to test trading strategies.
The Downside Of Deploying AI
The adoption of AI is a double-edged sword for jobs in the financial industry. On one hand, it is expected to create new roles in areas like data engineering, machine learning and AI governance. Financial institutions are already hiring aggressively for these AI-related positions. From October 2022 to March 2023, 40% of hiring within the banking industry were for AI-related job functions, according to an AI talent report by Evident.
On the other hand, AI is also projected to automate or degrade up to 300 million jobs globally, including banking roles in administrative support, legal and financial operations. This could lead to substantial job losses and the need for retraining of many professionals within the financial services industry.
Source: Forbes
