The State of AI in Fintech
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Weekly Rant ??
The State of AI in finance & what it takes to win
AI is now transforming finance. While 99% of companies are talking a good game, the very best are reducing costs, building new products, and changing how they work daily.
When Klarna announced they'd replaced half of their customer support with AI, the world of finance was captivated. Now, they've announced that Salesforce and Workday will also be replaced. Every incumbent CEO wants that, and every cynic wonders how inefficient they were before.
They're winning at AI because of the consistent, multi-year focus across the organization; they're using AI internally as a tool in their product and deploying agents.
Now with Open AI’s o1, agents will become much more accessible. Every white collar job could hire 10 agents to help them.
This piece explores how to think about GenAI in finance and how to win.
Then, we can discuss the 4 ways to win at Generative AI in a vertical like finance.
Ignore the memes.
When writing this piece, a big part of me was very aware that many people feel like AI is the emperor's new clothes.
But if that were true, it wouldn't make sense for the fastest-growing, most successful technology companies to be leaning in quite so hard.
The mainstream discourse always involves "responsible AI" or ethics in AI. Bloomberg adverts for Workday feature aging rock stars talking about this stuff. Governments and regulators are getting together to discuss regulation and the existential crisis.
As I discussed a couple of weeks ago, regulation with AI can be managed; we know how to do this.
Another big meme is hallucination, AKA "creativity." This makes the models nondeterministic. You don't get a set answer like you would from a calculator. This isn't very clear for newbies but second nature for statisticians.
Complex problems are multivariate. Generative AI models like LLMs or image generators can help you imagine new futures, be creative, and problem-solve.
These memes don't communicate complex reality or help you figure out what to do with technology. Even if the memes and Thotboi Twitter threads are annoying, something genuinely paradigm-shifting is happening.
And Fintech is ideally placed to win at this new chapter in AI.
Fintech is ideally placed to win at AI.
Talking about Generative AI seems like hyperbole if you're into the next big compliance drop from the CFPB.
While there's a risk of a bubble and plenty of snake oil out there, there's also a meaningful reshaping of the provider stack and back office of financial services (and every other industry). It will be at least as meaningful as the shift to cloud or SaaS, probably significantly more.
Tiny models (like Apple Intelligence) that run on a mobile device can be private, operate on personal data, and begin to act as personal agents. It's still a little janky for consumers, but that is starting to change. The consumer use case is a matter of time.
The internal use case is here. Whether it's risk assessing a business, a management team, or having a feel for compliance when building new products, a lot of assumed knowledge is hard won when you deliver financial services products to market.
And yet.
Most people still don't have a daily-driver LLM or set of AI tools.
That's not true in the Fintech growth companies, and they're a great place to show who's winning at AI in Fintech and how to win.
Three models to package AI
It's this third one that I think the mass market buyer gets. AI as a product disappears into the background and never gets appreciated (like all great design). Co-pilots are awkward and a little janky. AI agents for software engineering, demand gen, compliance, and everything else? That's where we're headed.
The Agent-ification of AI is coming to Fintech. Here are some other Thotboi thought starters for your next brainstorming session.
What is an AI agent?
Software engineers often use the term "Marketichture" (marketing + architecture) to describe things that sound technical but are far from correct. As a practical reality, the term "agent" has no direct technical definition, but it's a helpful simplification. "Agent" is the perfect example of Marketichture.
Conceptually: The idea of an AI agent is software with the agency to make decisions, where humans can review but don't have to approve before an action is taken.
1. Owning the workflow of growth companies is the best place to be.
The biggest Fintech winner from AI is Stripe. Of the top 50 GenAI companies, 82% are Stripe payments or billing customers. Stripe has always indexed to the next growth customer, but they're also marketing masters.
Having the CEO tweet something like the below or having the Nvidia CEO show up at your customer conference is a unique and timely flex. Whatever the Silicon Valley wave is, Stripe is riding it.
Stripe owns the payment and billing workflow and is naturally placed to use it behind the scenes (although they're being somewhat coy about the direct uses).
Another example is Ramp, whose CEO, Eric, has been on every VC and tech podcast lately, discussing how they use AI internally and for customers. Ramp is using AI as a product when it adds features like AI to understand what a user is trying to do and help them navigate to the right screen.
Whether it's their internal sales database bot Toby or the AI that can help you navigate their UI, they're becoming default-AI or AI-first. Not just in marketing but in tooling and going to market.
Ramp owns the spend management, CFO, and finance workflow. It's winning at the growth customer segment. Having an AI story keeps it there,
Finally there's Klarna. Unlike Stripe or Ramp, they don't serve companies but consumers. As a direct-to-consumer play, they use AI more directly for customer support. They claim to have reduced the customer workforce by 50% and ripped out both Salesforce and Workday.
Klarna directly owns the shopping and checkout workflow. Their core business model of BNPL and shopping ecosystems has consistently driven growth. Using AI customer support, they can continue to re-engage shoppers and manage issues like delivery or returns elegantly
2. Innovation on top of Incumbents with Agents
Loan agents sit on top of Loan Origination systems. Casca* offers a loan officer agent that can manage communications with customers, collect documents, and directly drive underlying legacy systems like a loan officer would.
Compliance agents deal with manual work. Greenlight and Parcha can investigate business customers flagged for manual review by a KYB process and approve or decline their onboarding. Axle can respond to transaction monitoring or sanctions alerts and approve/decline them. All of these are examples of AI-as-agents.
Often, they're sitting on top of a legacy system like NiCE Actimize or a loan origination system (LOS). Their natural buyers are incumbents who have legacy systems or very early-stage companies that don't have the staff breadth to handle the alerts or volume of manual work.
By leading with agents as the thing they sell, it's easy for the buyer to comprehend what the product does and how it fits their workflows today.
This is true for marketing, CRM, sales, and countless other parts of a company's value chain. Ramp and Klarna noted that they use GenAI for their marketing images. Every SaaS tool has an AI agent that can work with or displace that SaaS tool.
The interesting question for these companies is: can they can become the daily driver? We've seen Klarna displaced Salesforce and Workday. Will we see more stories like that? Will that become normal? Or was Klarna just not that big of a Salesforce user in the first place?
3. Incumbent workflows adding AI Agents
I haven't seen notable examples of this in the major payment companies, core banking providers, or legacy platforms that financial institutions use. Perhaps the AI agents from the SAP, Oracle, and Microsoft crowd have more opportunities.
Salesforce is actively marketing its AI. The market seems to think Salesforce is more threatened than it has opportunities. Their "Einstein GPT" creates personalized content for every employee. But it's ultimately ChatGPT embedded in Salesforce. The model here is AI-as-co-pilot.
Microsoft has been aggressive at embedding AI into its productivity suite, perhaps even more so than Google. Most back-office workflows at legacy businesses still exist on a Microsoft stack. Microsoft Excel and legacy Mainframes hold up the global financial system. Could they turn these into agents? This is also packaging AI-as-co-pilot.
The incumbents seem to have speed-run launching the co-pilot model to defend their market position, but ironically, they just wrapped ChatGPT and have not meaningfully innovated.
Currently, some Microsoft data integrations directly into Excel could be very interesting. This gives the potential for a Powerpoint to auto-update with live data, but this isn't what's being sold or what the incumbents seem to know how to buy.
They do know how to buy agents.
4. Incumbent workflows buying or partnering with AI agents.
Incumbents are no strangers to channel partners, integration partners, and the marketplace. Giants like Salesforce and SAP have businesses specializing in implementation and their own app stores.
An AI agent could sit on top of your existing provider. Today, they already do, but it's more of an early-Plaid-like agent, directly interfacing with back-end systems and driving them as a human would, handling human comms, emails, and documents. This could be done more formally with a simple re-seller or partnership arrangement.
An AI agent could be tightly coupled with incumbent core systems. What if agents to operate a system, come packaged with the system itself. It feels like the obvious "value added service" for these companies to sell directly. Legacy providers have a habit of acquiring companies that do this sort of thing eventually.
Winning the AI Era
Firstly, the fundamentals. You have to get the basics right in data. You need a team that understands how AI works from the top down and is using it daily.
领英推荐
What Shopify, Klarna, Ramp, and Stripe have in common is that despite being late-stage, they're founder-led. And I'm not saying this in some cringe "founder-mode" hyperbole. I'm saying it in the Tobi from Shopify tinkers with AI because it's fascinating. These founders and companies are using the tool to grow their businesses.
Then, there is compliance and quality. Financial services compliance. If you communicate with customers, you must immediately worry about UDAAP and customer fairness, disclosures, etc.
Quality. There's nothing worse than an AI chatbot that doesn't work. The balance between low-cost open-source models and using RAG and fine-tuning is critical to creating and packaging any experience for users. Raw LLM models are an expert tool; productizing them requires work.
Use AI as a tool. You cannot build with AI if you don't use it every day. The number of CEOs on TV and in the media who don't use AI daily is so obvious. There's a massive difference between companies and cultures that use it to do their jobs and those that just buy it as a SaaS tool or use ChatGPT to occasionally write marketing copy.
I've included AI as a co-pilot for completeness. There's good and bad here. The good is using AI as your thinking buddy, your sparring partner—not always outsourcing whole tasks, but working with it, dancing with it. The bad version is wrapping ChatGPT into your product and saying "Einstein GPT." It looks odd.
AI as a product is the artful inclusion of AI in the UI.
AI agents will be where the real unlock is. They can perform the tasks previously reserved for humans with creativity, problem-solving, and unstructured data. Building AI agents requires all of the fundamentals, quality, skills, and AI product experience.
They're the hardest to build, and today, they naturally get applied to existing processes. However, things could get spicy when they start getting creative as engineers, compliance officers, or loan officers. (Within legal and good product limits of course)
Summary
Ignore the memes, play with AI, and put the foundations in place to take advantage of it immediately. This is a generational shift, and like every hype cycle, the first to take advantage will be the small and growing companies. Your competitive advantage will ultimately come down to how far up the AI-era hierarchy you can climb.
Are you just wrapping up ChatGPT, or are you doing the hard data engineering work to rethink your entire value chain?
We're well past the age of shit chatbots.
If your experience of AI is not being able to get ChatGPT to do something the way you intended, you're doing it wrong.
The lesson here is that winning in the AI era is about shifting your default. Shifting your thought pattern. Shifting to every UI could be an AI "agent." Every white-collar job could be an agent.
Not because this is the perfect technical description.
Because, like all marketing, it's a helpful metaphor.
Play more.
Let go and dance with the AI.
Because it's only by engaging with it you'll figure out where the true value is.
Part of me groans every time I see a Klarna press release because, no doubt, it hides a lot of complexity, like being a great cover for headcount reduction and vendor consolidation. You also have to see why it's working.
They're aggressively engaging with the technology, and showing you how they do it.
Stop what you're doing right now, open ChatGPT o1, Claude or Replit, and try creating a prototype Trello board app or UI. Don't quit until you've got something working.
Or, keep trying to get to inbox zero.
Your call.
ST.
4 Fintech Companies ??
1. Agree - Docusign + Stripe Billing + GenAI
Agree helps users create, send, and sign digital agreements and contracts. It bakes in invoicing and payments to the agreement platform. Users can create, collaborate, and negotiate an agreement between multiple parties. The AI can clarify documents in plain English and allows users to ask questions about the contract. Then, the platform handles invoicing, payments, and payment collection.
?? This is a clever business model. Give the agreement signing away for free vs. charging like Docusign, but monetize the following payments, invoicing, and billing. In the process, you also reconcile any agreement against the billing. A contract is, by nature, unstructured data, but if you go upstream to it, you make it the source of truth for all invoices and billing events. Smart.
?? It also combines two megatrends: AI-driven Lawtech and AI-driven finance workflows. Both of these require a lot of unstructured data and expertise to solve issues. I've seen countless companies doing one side of this problem but not the other. Very, very cool.
2. Flex - The online checkout for HSA/FSA
Flex allows wellness companies, opticians, gyms, and mental health support services to allow their customers to pay with their HSA/FSA cards. This has driven a 20% increase in the average order values (AOV) and creates a simple user experience to spend the HSA/FSA dollars.
?? This feels like a win/win. Consumers save 30 to 40% when they use their HSA/FSA, which gives them more spending power; what might have been a luxury health service is much more within reach if it's 40% cheaper. Making that as slick as any e-commerce experience for the growing market of wellness companies feels directionally spot on. Growth market, moving online, remove friction. Solid.
3. Alaan - The UAE's "#1" spend management card
Alaan offers corporate cards, spend management, payment automation, and 2% cashback on all transactions. It is adept at identifying available sales tax refunds and simplifying claims. They claim to save 16 hours per month per finance team and provide finance teams with a dashboard, controls, and insights into spending analytics.
?? UAE and the MENA are a growing tech hub poorly served by traditional banks. This is a Y-com-backed start-up that will expand across the region. Whenever I talk to founders, they see the UAE as their wedge market, a little like getting traction in Silicon Valley before going wider. This is especially important when CFOs are your clients, who tend to value relationships and don't often attend conferences. If they're in the region right now, they're probably in the UAE.
4. Valyx - Finance ops for India's fast-growing businesses
Valyx automates invoicing, collections, and reconciliation for growing businesses in India. It helps build simple routines, waits for steps, chases emails for payment, and provides a cash flow dashboard. The service automagically reconciles payments against accounts.
?? A great business is one whose primary competitor is companies managing internal comms on Whatsapp. Whatever workflow lives in Slack, Whatsapp, or elsewhere could be automated. How long until someone builds a Slack integration to identify tasks the team is doing that AI could automate? ??
Things to know ??
From Jason Mikula’s LinkedIn: “In a letter sent yesterday, Democratic Senators Elizabeth Warren and Chris Van Hollen expressed concerns about bank/fintech partnerships, specifically naming companies like Stripe, Chime, Venmo, and, yes, Synapse.”
The Senators describe the current model as a threat to safety and soundness and request clear rules for the management of 3rd parties. Regulators have this authority under the Bank Service Company Act (BSCA).
?? Almost every Fintech company (and I imagine most banks) would welcome clarity here. The current storm clouds make it hard to do business, and a blizzard of enforcement actions isn’t solving the issue.
?? Next week we have the results of the RFI on 3rd parties. Everyone in Fintech is waiting to see what comes out of that because we’re hoping for some clarity and possible engagement. My guess is it will rule make for direct oversight of 3rd parties under the BSCA, but lets see.
?? Often Fintech companies receive feedback from regulators second hand, after remediation has been agreed between the bank and regulator. This means Fintech companies have no direct relationship with regulators or insights on the concern for good faith actors, making compliance harder.
?? We need more direct engagement between Fintech companies and regulators. I’m involved in work with the Association for Innovation in Regulation to organize roundtables to build this dialogue. Direct supervision is inevitable, so lets start the conversation about the real issues and how we solve them.
Klarna has announced it is shutting down Salesforce and will soon do the same with Workday. This is part of a wider initiative to shut down and consolidate SaaS providers. This follows a headcount reduction of over 50% in customer service and halving its overall headcount.
?? Klarna is a case study in becoming AI-first. They were an early partner for Open AI and have been aggressive in the internal adoption of AI tools as a default.
?? Focussed, intentional, and long-term effort is paying off. The CTO, CEO and entire team have leaned into to AI and stayed consistent with it, not just for the press, but with execution.
?? The leverage is real. The companies doing best with AI are those using it as their operating system on a daily basis. It’s one thing to use ChatGPT to help with your day job; it’s another to rewrite your internal stack with AI.
?? It bothers me how perfect this PR is. When putting slides together to explain AI to others, Klarna is now one of the best reference points because they’re telling so much of the story in the lead up to their IPO
Good Reads ??
I really enjoyed this breakdown of the tradeoffs between being a bank vs a Neobank. The core argument is that perhaps now the business case has flipped. At one point most Fintech companies would perform jujitsu not to be a bank.
But others are winning.
That's all, folks. ??
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(1) All content and views expressed here are the authors' personal opinions and do not reflect the views of any of their employers or employees.
(2) All companies or assets mentioned by the author in which the author has a personal and/or financial interest are denoted with a *. None of the above constitutes investment advice, and you should seek independent advice before making any investment decisions.
(3) Any companies mentioned are top of mind and used for illustrative purposes only.
(4) A team of researchers has not rigorously fact-checked this. Please don't take it as gospel—strong opinions weakly held
(5) Citations may be missing, and I've done my best to cite, but I will always aim to update and correct the live version where possible. If I cited you and got the referencing wrong, please reach out
This is a thought-provoking take on the evolving landscape in fintech. The clarity from regulation could indeed pave the way for stronger frameworks. How do you see companies adapting to these changes in the near future?
Data Science | Machine Learning | Credit Risk | ECL | Insurance | Ecommerce
1 个月Fintech is really fascinating
Top Thought Leadership Voice | Top Artificial Intelligence Voice | FINTECH | DIGITAL TRANSFORMATION | ARTIFICIAL INTELLIGENCE | SOCIAL GOOD | METAVERSE | TEDx Speaker | Keynote Speaker | Author
2 个月Clarity and transparency are crucial in the evolving landscape of Fintech. Your insights on the impact of AI in financial services are thought-provoking, Simon Taylor. Looking forward to more discussions on this.
The Payment Solutions Guy — I'll help you decrease processing fees by 20%, and improve approval rates (guaranteed) by finding the best Payment Providers for your business | Visit my website to learn how
2 个月Exciting developments in fintech and AI, but let's see how the industry adapts to new regulations and advancements!
Thanks for the mention, Simon! ?? Exciting times for fintech, especially as AI continues to reshape the landscape. At Valyx, we’re thrilled to be part of the movement driving financial operations forward for fast-growing businesses in India. The agent era has arrived, and we’re ready to embrace the future! ??