Gen Z Loves AI Banking, & AI Adoption in Onboarding Is Growing
Here's what happened in AI x Banking this week
Hello, hello. Happy Thursday from the Greenlite team. There’s a lot to get to today, from Gen Z’s excitement around AI banking, a new Moody’s report, and yet another bank rolling out an LLM product for employees. Let’s get to it.
61% Of Gen Z’s Use AI To Manage Money
Overall, Americans are still tepid around AI & financial services. The BMO Real Financial Progress Index reaffirms that.
37% are using AI to help people manage their money,
49% are using it for financial education
48% are using it to creating & updating budgets
and 47% are using AI to identify new investment strategies
Those numbers change dramatically when talking about Gen Z’s.
A whopping 82% use AI to learn more about personal finance. 58% think that AI can help them make more informed financial decisions and 55% are confident that AI can help them make tangible progress on their financial goals.
The generational gap between Gen Z’s and other generations is in line with larger technology trends. Typically, younger people are quick to adopt new technology into their daily lives.
While it’s a great start, new tech needs to start penetrating older demographics to become mainstream. A great example of this is TikTok—the teen short form video app was popular with high schoolers and now have 170 million Americans using it monthly.
The good news is that older demo’s are interested in using AI for financial services too. Out of the group of people not using AI yet:
32% of them want to use it to learn more about personal finance
31% want to use it to increase their savings
29% want to find new investment strategies
29% want to create or update household budgets
27% want to use it for financial planning and/or retirement planning
To us, the most interesting fact from this survey is that people are already using or planning on using AI for financial education. There’s a big business around providing financial advice—while typically that’s been the role of wealth advisors and money managers, technology has dramatically reshaped that.
Now, there are tons of apps and website that provide financial advice for users. But, AI could be headed in the same direction as other massive search categories—instead of sifting through a bunch of websites, an AI chatbot simply provides the answer. That cuts down on the time-to-insight (the time between asking a question and getting an actual answer) dramatically.
Check out the full release from BMO here.
Banks Are Adopting AI, But Are Still Skeptical
A recent Moody’s report on entity verification shed some light on how banks are thinking about adopting Gen AI in functions like onboarding and KYC/KYB.
More companies are trialing or piloting use cases in AI & compliance than last year—up 6%. But, the banks were thinking about using AI fell dramatically—by 11%.
The Moody’s report writes that a lot of AI adoption in entity verification is dependent on data quality, which makes sense. While generative AI is great at making sense of unstructured datasets, you still need to have access to the right data, which often live across multiple departments and is deeply fragmented.
Notably, 93% of those surveyed from APAC and Middle East seem to think that AI will have a “critical” or “valuable” impact in modernizing entity verification.
JPM Rolls Out Internal Chatbot For Employees
It’s becoming clear that the most immediate uses of AI in banking is around making employees more efficient. At least, that’s what it seems based on recent product rollouts from Goldman Sachs, Morgan Stanley, and now JPMorgan.
The bank rolled out a new product they call “LLM Suite” to employees, based on an internal memo reviewed by The Financial Times. It’s essentially a custom version of ChatGPT that can do the work of a research analyst—that includes helping with writing, idea generation, summarizing documents, and more through third-party models.
The product is now live to about 15% of the company, or 50,000 employees.
You may wonder why this project is even necessary—why don’t employees just use ChatGPT, or Anthropic’s Claude?
They can’t, because of regulations. Compliance dictates that customer data is locked down and not allowed to leave their servers. AI chatbots publicly available are programmed to ingest data to improve the underlying LLM’s, which would be a clear violation.
So, building in-house chatbots makes sense, as does building out internal AI products. But that’s mainly because the engineering lift isn’t outrageous. For large scale projects, like building custom LLM’s or compliance software, vendors need to think about these rules during product development and sales. It’s why some banks are looking at on-prem solutions for a lot of AI products, which hasn’t been too popular.