Barclays and Revolut are two strong, popular UK banks with about 30 million customers each. While Barclays has a market capitalisation of £32 billion, Revolut's valuation is down to ~£15 billion from a high of £33 billion in it's last fundraise at the height of free money period. That's where the similarity between both banks end.
When the app stores exploded in popularity in 2010 on the back of iPhone and android launches a few years earlier, Barclays was one of the large, multi-generational banks in the UK which dominated the market. Revolut on the other hand didn't exist and wasn't founded until 2015. Today, an 8-year-old challenger bank compares favourably on some metrics against a 330-year-old institution.
Widespread adoption of the internet in the late-1990s set the stage for web and mobile based technology advancements. Technology companies founded since the 90s have disrupted several industries from ecommerce (Amazon), payments (Stripe), media (Facebook, Twitter etc) and banking (Revolut, Chime, Monzo).
In the past decade, bank branches have become largely obsolete due to rapid advancements in technology. Online banking, mobile apps, and digital payment systems have transformed the way customers interact with their banks, making physical visits to branches unnecessary. As a result, physical branches quickly turned from a moat to an albatross.
Despite the numerous technological advancements transforming retail banking, the corporate and investment banking arms have largely maintained their traditional practices and structures over the past few decades. The complexities and bespoke nature of services such as mergers and acquisitions, capital raising, and strategic advisory have kept investment banking reliant on human expertise and personal relationships. Consequently, this sector has not experienced the same level of disruption from technology as other areas within the financial industry.
But is Generative AI the proverbial straw that breaks the camel's back?
What is Generative AI?
Given the excitement over ChatGPT and other tools in the past 20 months, we'd all be forgiven for assuming that AI is new and limited to chatbots. In reality, generative AI (GenAI), the technology that powers Gemini, Claude, ChatGPT and other tools is a subset of machine learning (ML) which is itself a subset of artificial intelligence (AI).
Artificial intelligence (AI) is a broad concept that involves creating machines or systems capable of mimicking human behaviour.
Machine Learning (ML) is a subset of AI that focuses on enabling machines to learn from experience and improve their performance over time without being explicitly programmed for each task.
Generative AI (GenAI), emphasises the creation of new content, including text, video, software code, and images. Unlike traditional AI, which might classify data or make predictions, GenAI generates novel outputs based on learned patterns from existing data.
History of AI
In 1948, mathematician Claude E. Shannon published A Mathematical Theory of Communication, an article which went on to become cited over 10,000 times. The article is the first known reference to N-grams, now widely recognised as the foundation of Natural Language Processing and artificial intelligence. Over the next five decades, artificial intelligence remained a preserve of the research and scientific community. Like a bolt out of the blue, IBM's Deep Blue stunned the world when it defeated world chess champion Garry Kasparov in a game of chess. Deep Blue's win was a major public milestone for the field of artificial intelligence, signposting progress in catching up to human intelligence.
History of Artificial Intelligence
While the Deep Blue success over Kasparaov was a success for IBM, it was a dead end of sorts. On the other hand, the 2022 launch of Dall-E by OpenAI and Stable Diffusion, by Stability AI was the genuine start of a new technological revolution. The text-to-image models were the first peak the public had into generative AI tools. A few months later, in November 2022, OpenAI released its large language model, ChatGPT. This turned out to be a pivotal moment as it captured the public consciousness and led to wide adoption of generative AI tools by consumers. By January 2023, just two months after launch, ChatGPT had grown to over 100 million monthly active users, the fastest consumer product in history to reach the milestone according to Reuters.
How AI is Already Impacting Industries
Unlike previous technology waves where blue collar jobs were the first to be impacted and faced the most disruption, the GenAI wave is having an outsized impact on white collar jobs. Over the past 18 months, several OpenAI competitors have launched including Gemini by Google, Claude by Anthropic and [X byX]. These large language models have focused on helping consumers generate text, images and video instantly from prompts.
Given the focus of these tools on creating new content, it is not a surprise that writing, illustration, music composition, art and other creative tasks have been most impacted. In November 2022, Jason Allen, a 39-year-old American entrepreneur created controversy when his generative art work received an award in the the Colorado State Fair’s annual art competition.
Titled “Théâtre D’opéra Spatial", Allen's entry in the digital art category was created entirely using Midjourney, one of the leading text-to-image models. Expectedly, the award elicited fierce reactions from artists who were livid at what they considered "cheating". Other observers considered it fair, given Allen had noted he created the entry using Midjourney. As text-to-image models paved the way for “AI still art”, so did the introduction of text-to-video models lead to “AI video art”. In July 2024, Prix Ars Electronica, one of the world’s longest-running media art competitions, announced its annual winners for 2024. “The Hardest Part” by Washed Out, the first full video made with OpenAI’s SORA won the AI in Art Award, a brand-new category.
In less than two-years, game-changing generative AI tools have gone from zero to wide adoption faster than any other consumer tool in history. Organisations, including banks and investment firms, are grappling with decisions on how to integrate these tools to enhance productivity while protecting their organisations from inherent risks.
Kayode Odeleye, investment banker and tech startup founder, will help executives make sense of the fast-changing landscape and identify major risks and opportunities involved with implementation of generative AI in their institutions; and will share the top 5 generative AI use cases in corporate finance.
Watch our popular on demand webinar lead by Kayode Odeleye here.
Read the next part in our Generative AI series "Does Corporate and Investment Banking Need Improved Efficiency from AI?" here