Fintech AI Review #12
Are AI use cases in financial services elusive, here today, or both?
Hello, fellow fintech and AI enthusiasts!
While spring has sprung in the northeast United States, I’m leaving the beautiful flowering trees of Connecticut behind for a week and am writing today from Delhi, India, where I’m looking forward to spending time with my colleagues on this side of the world. Traveling provides valuable perspective on all things, including the differences in the need for, nature of, and access to financial services across the globe.
Today’s newsletter covers a variety of topics, including the challenges and opportunities in finding AI use cases, several compelling applications of AI in financial services today, the opportunity for generative AI to facilitate the expansion of credit in areas lacking a mature and well-structured credit data system, and AI-related security considerations.
As always, please share your thoughts, ideas, comments, and any interesting content. If you like this newsletter, please consider sharing it with your friends and colleagues. Happy reading!
Recent News & Commentary
The thing about any new technology is that - no matter how amazing - once widely available, it ceases to be a differentiator. A long time ago, factories that used electricity were revolutionary, and then the use of electricity became widespread and simply table-stakes. More recently, this happened in the consumer internet and with mobile apps. At first, having a website or an app was a big deal, and it quickly became an expectation. This shift will happen even faster with AI. As AI capabilities become widely available, mere integration of the technology itself does not make a valuable business. Rather, the success of a solution comes down to things like product design, customer experience, and brand. This excellent thought piece by Morgan Beller at NFX compares AI to bottled water - a product whose core technology is clearly a commodity but where novel brands continue to innovate and win. She asks: “If you took AI out of your pitch deck, is it still a good business?” Applying her thesis to applications in financial services, we are now in the era of 'adding AI' to existing use cases. While the technology certainly can provide benefits - particularly in speed, accuracy, or efficiency - it likely doesn't change the essence of the core financial product offered to customers. Once everyone 'adds AI' to products, it ceases to add distinction and simply becomes the norm. What products or experiences could not exist without AI? Build those!
Looking for AI use-cases - Ben Evans
“This is amazing, but I don’t have that use-case.” This is the central question asked by the always thought-provoking Ben Evans in his latest essay on generative AI. He writes of the birth of the personal computer (PC), how it was celebrated for its general potential but truly reached adoption when Visicalc and other spreadsheets made this potential obvious and specific. Likewise, he considers if, while chatGPT, Claude, etc. feel super impressive, LLMs haven’t had their Visicalc moment. What Ben does exceptionally well is to put technological trends and developments into a broader historical context. His general assertion here is that just like with past innovations, products that take advantage of them need to be researched and built, one-by-one.
Gauging Generative AI x Financial Services - a16z
While financial services is a highly-regulated industry, this has not caused it to delay adoption of generative AI. This post by Angela Strange and the a16z team mentions several real-world examples of companies solving practical, tangible use cases today. Interestingly, while employees at many institutions avoid mentioning AI in the earshot of a compliance person, this piece mentions multiple examples of how the technology can assist with compliance. For example, software available today can help write SARs (Sardine), interpret long regulations (Norm), or perform automated screening of suspicious customer activity (Greenlite). AI is also being used to streamline complex workflows (Vesta, Casca) and has the potential to automate various customer actions. Solid post and original tweetstorm as well.
Opportunities for Generative AI in Financial Services - Visa & This Week in Fintech
Visa and This Week in Fintech collaborated to write a thoughtful and comprehensive white paper on the current state and future possibilities for generative AI in financial services. The paper covers a wide range of applications, including those in fintech, banking, customer support, investing, commerce, and payments. What I particularly appreciate are the numerous real-world examples, including specific companies and links. It also discusses topics of potential uncertainty, including regulation, international adoption, and implications for the underbanked. Notable for its breadth as well as depth, this report is definnitely worth a read.
JPMorgan Says Its AI Cash Flow Software Cut Human Work By Almost 90% - Entrepreneur.com
JP Morgan has apparently given corporate clients access to a new AI-based cash flow forecasting tool. Boasting 2,500 current users and claiming a 90% savings in terms of manual work, the tool appears to be a success in streamlining the work of cash flow management in a complex enterprise. Bank of America and RBC have also launched similar capabilities. While the article here references the potential that banks could eventually charge for such a product, it’s short on details. For example, how much data for a particular corporation does the tool need to make accurate forecasts? How much human review is required to get from machine output to acceptable accuracy? It’s also not clear whether banks are best-suited to deliver such a capability or whether it will eventually be offered by accounting and ERP systems, which would logically have more real-time information on the operations and financials of a business.
Towards Generative Credit - Matthew Flannery, Branch
In the United States, we have relatively well-structured and consistently available credit data that does not exist everywhere. In other parts of the world, including India and Africa, making credit decisions can be substantially more difficult and requires the acquisition and analysis of a more diverse set of data points than would be practical (or compliant for that matter) to use in the U.S. In this Medium post, Matt Flannery of Branch discusses the role of generative AI in improving credit assessment for microfinance in geographies with less mature credit systems. LLMs can already be quite useful in labeling unstructured data, making it viable for use in statistical models to predict risk. This post also contemplates future developments, including automatic feature engineering, predictive synthetic data, and ‘AI as credit officer’. We certainly don’t have a good compliance framework for many of these concepts in the U.S. However, in markets without a well-established and reliable source of credit history, there could be great benefit in using non-traditional approaches enabled by AI to expand credit access.
The U.S. Treasury released a report on cybersecurity risks around AI in financial services. It’s a long read (52 dense pages), but it’s worthwhile to note a few interesting points. The report mentions a “fraud data divide”, where larger institutions have the data to train models, and smaller ones may not. It also mentions a skills gap, where many institutions lack the personnel and sophistication to tackle a rapidly-expanding set of AI-related security challenges. Most interesting perhaps is the concept of a “nutrition label”, stating what data was used to train models offered by vendors to financial institutions. This is relevant particularly for institutions relying primarily on vendor-contributed technology and wary of the privacy and liability implications of models trained on data from unknown sources.
What’s next for AI in Risk Management
On May 16th, I’ll be joining my friends Vinodh Poyyapakkam, CEO of coris.ai, and Ryan Hildebrand, CIO of Bankwell for a webinar to discuss what’s next for AI in risk management. You can expect a wide-ranging and enthusiastic discussion of how AI is being used by various partciipants in financial services and the many possibilities that exist for transformation. If you’re interested, please register. I’m looking forward to an exciting conversation!
Email header image: on the beach in Villers-sur-Mer, Normandy, France last month
AI is already taking over, true. But figuring out what can be done with it (and what can't or shouldn't be done) is going to take years. Interesting stuff!
Thank you for your thoughts and for curating a great selection of articles and analysis.