Explore three scenarios of how Gen AI will change consumer finance

The rise of generative AI has led to much discussion and discussion about the potential for this technology to disrupt industries and displace widespread human jobs. But the impact of technology will vary by industry, so it's important to go beyond the big-picture discussion of disruption and consider exactly how it will change the financial services sector.

For financial services, the impact of generative AI can be simplified into three possible future scenarios. 1) Non-financial technology companies develop powerful generative AI-based personal assistants, disintermediating financial companies, and 2) The world's largest banks will become even more dominant in leveraging technology rather than disintermediation. , 3) No company has been able to establish a dominant generative AI assistant, and this technology will become commonplace without significantly changing market share.

Although the future cannot be predicted, it is important for financial services organizations to thoroughly consider the three possible outcomes and develop long-term plans for how the business will react to each of these scenarios.

Before we get into this topic, a word of caution. The purpose of this article is to make the subject approachable for those who are not familiar with the nuances of generative AI. This article does not discuss the technological developments that facilitate these results. For example, will it become cheaper and easier to build your own large-scale language models (LLMs)? This article explains, for non-technical people, how generative AI will impact the financial services industry.

Scenario 1: Non-financial technology companies occupy a dominant position

One possible outcome of generative AI technology is that consumer technology giants (such as Alphabet, Apple, and Meta) and/or breakthrough technology startups could It is about developing a personal assistant that the corresponding consumer can rely on. finance. Consumer behavior is changing and the average person looks to the leading generative AI-based virtual assistants with overwhelming market share to help with their questions and concerns.

This achievement will see the evolution of generative AI technology to enable tech companies to develop better personal assistants that are so advanced that consumers will use them almost exclusively. The assistant monitors the consumer's situation (through linked external accounts) and provides advice on questions such as “How can I improve my financial situation?” or “Is there a chance I could earn more with my savings?” This development could disintermediate financial services companies and allow assistants to influence consumers’ financial decisions and behavior. Become.

If this scenario becomes reality, financial services companies' reaction to this disintermediation will depend in part on how regulations are lifted and whether AI assistants can earn referral fees. Beyond inquiry questions, in the long run, this outcome could make things even tougher on the financial services industry.

In this scenario, financial services companies need to become more innovative and develop attractive and unique products and services. Financial services companies will need to encourage customers to actually log into their websites and apps, rather than relying solely on personal assistants. A typical product lineup or a typical customer experience will gradually lose market share in a world driven by high-powered virtual assistants from tech companies.

“In past hype cycles, incumbent tech giants were often slow to react,” said Remko Janssen, founder and CEO of European tech news media company Silicon Canals. When it comes to AI technology, big tech companies like Apple, Google, and Amazon acted quickly.
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They also have the advantage of having access to consumer payment data. The most difficult outcome for financial services companies would be a situation where one to three large technology companies become dominant in generative AI, similar to the dominance of mobile operating systems by Google and Apple. ”

Scenario 2: Largest financial company uses genetic AI to further strengthen its advantage

In this scenario, generative AI technology is developed in such a way that technology companies do not disintermediate financial services companies, but the cost and complexity of advanced AI technology means that the world's largest banks will Gain a competitive edge against larger rivals. As an example of the disconnect between top financial services companies and the next tier of financial institutions, as of May 10, JPMorgan Chase ($570.8 billion) and Bank of America ($300.69 billion) The market capitalization of both exceeds the total market capitalization. US Bancorp, PNC, Capital One, Truist. The combined market capitalization of these four institutions is “only” about $235 billion.

It turns out that the largest financial firms with access to expensive engineering talent and cloud computing resources can develop generative AI-based financial assistants that are meaningfully more powerful than the average financial services firm or third-party industry vendor. maybe. If the world's largest banks can offer better generative AI-based financial assistants, they will use this service to further strengthen their industry advantage and capture market share from smaller banks.

Scenario 3: A successful generation of AI assistants never emerges.

In the last scenario, generative AI technology becomes a kind of commoditization, and no company develops a significantly better generative AI assistant. Generative AI-based assistants will become a standard feature of financial services websites and apps without fundamentally disrupting the industry or changing market share trends. Financial services companies may end up utilizing multiple third-party generated models simultaneously, requesting different models depending on the needs of their users.

In this scenario, financial services companies need to be thoughtful about how to optimize their generative AI assistants to minimize costs and maximize revenue. Financial services companies rely on generative AI to handle customer service questions (preventing more expensive calls to customer service call centers) and drive desired actions (e.g., establishing direct deposits, opening new accounts, etc.) You will strive to continually improve your abilities. While his third scenario is less threatening to the average financial services company, developing a high-quality generative AI assistant remains a large and complex undertaking.

Dr. Andreas Rung, CEO and Founder of Ergomania, said: “Banks and financial institutions tend to keep large-scale technology initiatives in the experimental/concept stage for long periods of time. Time is of the essence when it comes to generative AI. Organizations must move quickly to adopt generative AI assistants to their customer base. To keep pace with their competitors, generative AI assistants will also become a seamless part of their UX and customer experience. is needed.”

Gen AI has the potential to transform financial services, and businesses need to start planning for future scenarios now

Only time will tell how generative AI technology develops and which of these three scenarios becomes reality. But organizations need to take a hard look at these consequences and start thinking about how to respond in each situation. If the need arises, can your organization restructure and invest heavily in developing a cutting-edge generative AI assistant? Your company uses a third-party AI vendor If your company “backs the wrong horse” and has to change to keep pace with the big players, what are the “switching costs”? In each of these scenarios, your company How do you adjust your workforce? It's better to start planning now than to scramble after the fact to keep up with changing market dynamics.

Milan de Riede, Founder and CEO of Nano GPT, said: “We are seeing customer preferences change in real time as new generative AI models and updates are released. There will be no clear 'winner' as of May 2024. Our customers seem to prefer different generative AI models for different tasks. At some point in the future, your company will change its generative AI infrastructure and these may need to be approached relatively quickly, depending on which of the three scenarios becomes reality. ”