On November 22, 2022, an AI research company created and launched a revolutionary product. Today's Rosetta Stone, Open AI, has shaken our understanding of AI for the foreseeable future.
Source: Unsplash
Large-scale AI models like Large Language Models (LLMs) have gotten people hooked and fearmongering over the past year or so. LLMs are continuously emerging as powerful tools that allow workers to be more productive; they also increase the rate of innovation and set the groundwork for a boom in economic growth. The excitement and anxiety around these models reinforce the notion that these models are 'foundational' and a significant turning point for advancement in the field, most notably for fintech. Fintech – an amalgam of finance and technology – has exploded into the world, revolutionizing today's financial services.
Business and financial services accounted for 26% of US VC investments across industries in Q1 2023, second only to Information Technology.
Wall Street began using AI to rewire the world of finance, and when Wall Street starts to adapt to the trend, you must wake up.
How would generative and predictive AI change Wall Street?
Companies are going all out to increase their generative and predictive AI game. Before concluding that they're here to get rid of us, experts believe that this new radical technology is here to transform jobs, rather than eliminate them. Over 85% of employees believe that, at some point, they will require training that addresses how AI will influence their jobs, according to a Boston Consulting Group Inc. survey of about 13,000 workers across 18 countries.
If you want to impress Wall Street, add some artificial intelligence. Look at the following company portfolio below:
Source: DTech Staff
These are all examples of LLMs, primarily generative and/or predictive, and an excellent place to start. Wall Street has begun implanting these systems into their own due to the versatility of AI, which has various applications and some sense of scalability. These models crunch research at an accelerated rate as the user only needs to state the function they want to perform. LLMs have already been used by various investment banks, private equities, and hedge funds, performing sophisticated interest rate swaps, derivatives, hedging, and more. Financial services firms list the following benefits of AI:
1. Improved customer experience
2. Increased operational efficiencies
3. Cut of the total cost of ownership
4. Gained competitive advantage
5. More accurate models
6. New business opportunities/ revenues.
Potential risks
That being said, it's important to mention that risk comes intertwined with technological advancements. Wither generative and predictive AI, the main threat comes from the worry of exploitation, abuse, and further evolution of the technology. Further, the main risk of its implementation into Wall Street is the accuracy of data.
Looking at Fintech’s global landscape, global funding fell from $63.2 billion across 2,885 deals in the second half of 2022, or H2’22, to $52.4 billion across 2,153 deals in H1'23.
On the contrary, looking at the Americas landscape for Fintech, funding rose in the Americas, from $28.9 billion across 1,323 H2'22 to $36 billion across 1,011 deals in H1'23, with the US accounting for almost two-thirds of fintech funding within the Americas in H1’23.
Within fintech, AI and generative AI were the talk of H1'23 as they attracted a vast amount of attention in the first half of the year, with both traditional investors and corporates showing keen interest in applications within the fintech space.
Despite global headwinds, the macroeconomic outlook seems to ease out: global equity financing and dollars invested will rise in the year's second half, having dropped to $52.4b in H1'23 from $146.1b in H1'22.
Source: KPMG, July 2023; Pulse of FinTech H1'23
Nevertheless, interest in AI will continue to fast-track. The number of early VC funding indicates that startups will be incubated and topped to leverage AI to aid in operational efficiency and services, which is what Wall Street banks are looking for.
To conclude
Funding for fintech opportunities has increased since the pandemic. Enthusiasm has been driving AI-related stocks and investments this year. With a promising macroeconomic outlook for the remainder of the year, it is a great time to explore LLMs – generative and predictive AIs. With early VC and Angel seed funding rising for the technology, it is never too late to adapt to the evolving industries. It is crucial to understand that the world, including Wall Street, is reshaping, and they all want their hands on fintech software and systems.
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