Three Takeaways From Money 20/20
By: Tyler Brown
November 5, 2024
CCG Catalyst attended Money20/20 USA last week to capture insights on what’s hot in banking and fintech. Based on our observations, its content confirmed several trends we are seeing in the market, with a couple of more surprising highlights. Here are three takeaways that stood out to us:
Artificial intelligence (AI) got top billing — with a focus on risk and compliance. AI was the focus of a bullish address from OpenAI’s CFO and three enthusiastic sessions that featured executives from NVIDIA and Stripe. There were also thoughts shared on AI regulation and a session on applications for generative AI in financial services. We saw a fair share of companies advertising AI-driven products and services, though nothing to the casual observer screamed “AI.” Clear applications of AI fell into the risk and compliance category, with offerings that included biometric authentication and identity verification, risk decisioning, cybersecurity, and regulatory and compliance management. Some vendors also called out generative AI use cases, particularly generative AI-driven copilots for employees of financial institutions.
Open banking was also in the spotlight. Less than a week after the release of the Consumer Financial Protection Bureau’s (CFPB’s) open banking regulation, CFPB Director Rohit Chopra was on stage in a fireside chat to discuss the new rule. He revisited a familiar pitch that open banking would lower costs for consumers via greater competition in financial services and portability of customers’ data. He also touched on changes to compliance deadlines and specifications for the secondary use of consumer data. The text of the CFPB’s rule may worry bankers, particularly those who are unfamiliar with the technical language, but Chopra’s words could concern them more. During his remarks, he said he hopes there’s a point where “every [financial institution] feels that their customer can fire them.” In other sessions, speakers focused on preparedness for the open banking rule’s implementation requirements. Open banking infrastructure companies were notably present, on the floor and in meeting rooms.
Crypto was a topic of discussion, surprisingly. It’s been a few years since crypto was hot at Money20/20. And while it didn’t make a comeback, per se, sessions were bullish on aspects of the crypto industry and looked ahead to federal regulation and practical use cases for blockchain-based money movement. The consensus appeared to be that “crypto” in the form of stablecoins and certain tokenized assets will be complementary to traditional financial infrastructure in the long run. Also mentioned: The potential for licensed banks to issue their own stablecoins. Absent was any argument that crypto would replace fiat currency or aspects of the modern financial system, and there was little obvious presence from crypto companies anywhere at the conference.
Other themes were a grab bag — major sessions included digital innovation and the adoption of fintech in Mexico, cloud-based infrastructure modernization, and financial equity and inclusion; the last day consisted of marketing-oriented content for fintech and financial services companies. Looking beyond specific content, innovation in banking and fintech showed it’s alive and well, with well-rounded representation among vendors in sync with the industry’s basic technology needs, in addition to those on the bleeding edge.
Bankers’ AI Confusion
November 7, 2024
By: Kate Drew
Artificial intelligence and Community Banks
Artificial intelligence (AI) is a hot topic these days, but bank executives are struggling to define AI and what it could mean for their organization. For example, in a study by CSBS, using AI for customer interactions came in fourth place when community bankers were asked which technological developments would be promising for their bank in the next five years. In that same study, only 10% of respondents said the use of technologies like machine learning, natural language processing (NLP), or related tools is very or extremely important at their bank. Thirty-nine percent (the largest group) said it was slightly important, while nearly a third said it was not at all important.
Given that NLP and other associated technologies like generative AI are the building blocks of using AI for customer interactions, there is obviously a mismatch here. So, what is the difference? Well, one question asked about AI specifically, and the other didn’t use the term at all. Instead, the latter question focused on the specific technologies that fall under its umbrella. This discrepancy points to a major issue institutions have when thinking about and talking about AI — they do not have a clear idea of what it actually is.
Taking advantage of the AI opportunity requires understanding the technologies that it involves and how those tools can be used. For instance, machine learning is very good for deriving insights from large, tabulated datasets. It’s also been around for a long time. As noted in our latest report, machine learning has established use cases in financial services in areas like anti-money laundering, fraud detection and prevention, underwriting, analytics, biometrics, and automated document processing. Meanwhile, chatbots today, which represent one of the most obvious uses cases for AI are generally built using NLP, and more recently, generative AI. These are the kinds of technology that would be applicable to customer interactions, as noted above.
As executives contemplate this area, it is important to remember a few things. First, AI is a catch-all term for a set of tools that can be applied to different things. Second, you have to know what you are trying to solve for in order to apply these tools effectively. And finally, you do not need to use all of the tools, nor do you have to use any of them. In getting started, the smartest thing executives can do is educate themselves on the differences between these technologies, how they are used — and critically, what is already proven versus what is actually new.