The implications of ChatGPT and AI models on Fintech and Banking
A new text-based artificial intelligence (AI) tool called ChatGPT is making waves in the tech industry for its ability to accurately answer questions and complete a wide range of tasks, from creating software to formulating business ideas.
Launched on November 30, 2022 by OpenAI, the AI program has already impressed users and technologists with its ability to mimic human language and speech styles, while providing coherent and timely information. In just a few days, the service managed to cross the threshold of one million users.
Now industry observers and commentators are theorizing about the technology’s potential implications in the finance and banking sector.
According to Ethan Mollick, an associate professor of management at The Wharton School at the University of Pennsylvania, ChatGPT is a tipping point for AI and proof that the technology can be useful to a wider population of people.
In business, the ability to generate written content quickly and accurately means productivity can be increased in a variety of industries, Mollick wrote in a recent blog post on the Harvard Business Review. This will help organizations save time and resources, allowing employees to focus on other important tasks.
“This is particularly beneficial for industries such as marketing and advertising, consulting and finance, where high-quality written material is critical to communicating with customers and stakeholders,” he wrote. “Overall, the use of AI in writing will greatly benefit businesses by allowing them to produce more written material in less time.”
For Alex Lazarow, a global venture capitalist (VC) and author, AI models like ChatGPT will not only influence fintech thought leadership, but can also potentially deliver financial services.
First, these tools can significantly improve customer support and power a new class of services and chatbots, Lazarow wrote in a Forbes post. They can also be used for investment research, allowing analysts to scale their work beyond a narrow number of stocks.
Finally, AI models can help tackle transaction complexity, he said. If these tools are able to formulate sophisticated answers to complex questions, they should also be able to do the same for legal drafting. This would help accelerate the review of startup deals, but also any illiquid assets, Lazarow wrote.
The demand for artificial intelligence among companies has increased steadily over the past year. Data from the Global AI Adoption Index 2022, conducted by Morning Consult on behalf of IBM, reveals that 35% of the 7,500+ companies surveyed last year used AI. The number represents a four-point increase from 2021. In addition, 42% of companies reported that they are exploring AI.
IBM research also found that between the first and second quarters of 2022 there was a 259% increase in job postings in the AI domain, Ana Paula Assis, IBM’s managing director for Europe, Middle East and Africa (EMEA), told Euronews in December 2022.
In the UK, the central bank is currently looking at AI regulation amid accelerating use of machine learning (ML) by financial firms. A discussion paper was released in October 2022 to examine whether AI could be managed through clarifications of the existing regulatory framework, or whether a new approach was needed.
The paper was accompanied by the Bank of England’s second annual survey on the use of machine learning (ML), which found increasing use of AI. Of the financial institutions surveyed in the UK, 72% reported that they were either using or developing ML applications. The figure represents a five-point increase from 2019’s 67% adoption rate.
ML adoption among UK financial institutions, Source: Bank of England, December 2022
The study also found that ML applications are becoming increasingly widespread across multiple business areas in the UK financial sector. From the survey responses, it was found that 79% of ML applications were in the final stages of development. Notably, 65% of applications were already deployed across a significant proportion of business areas, with an additional 14% of ML applications reported to be business critical.
Stage of development of ML applications, Source: Bank of England, December 2022
Funding for AI companies has increased significantly over the past decade. In 2013, companies using AI secured US$3 billion through fewer than 1,000 deals, according to Crunchbase. In 2021, the total reached a peak of $69 billion across over 4,000 rounds. In 2022, global AI funding totaled USD 38 billion, at the end of November.
Annual venture investment in companies related to AI, Source: Crunchbase, November 2022
Featured image credit: edited from freepik
