Hi, I'm Julie VerHage-Greenberg with This Week in Fintech, along with my co-host Lauren Crossett, Head of Go-to-Market at Spade, a data and AI platform that turns messy transaction strings into structured, verified records.
We're on Episode 4, and this one felt especially fun to record, partly because we're pulling back the curtain on the company Lauren actually works for, and partly because Oban's origin story is one of the more unlikely ones I've heard in a while.
We're joined by Oban Mactavish, Co-Founder of Spade, who went from shutting down his first company during COVID to hand-labeling merchant data in Vancouver with basically no money, no payments experience, and no incorporated business and somehow beating a venture-backed competitor in a blind test before he even had a way to accept payment. And by Allen from Oak HC/FT, Spade's lead investor, who admitted he was skeptical this was solvable when he first met Oban, then watched him go out and solve it anyway.
In this conversation, we get into what Spade actually built and why it was so hard, what the fintech winter years looked like from both the founder and investor side, why Oban calls himself a crypto skeptic on the record, and what all three of them would tell a new grad trying to break into fintech right now.
Let's dive in!
🎧 Episode Summary: Hand-Labeled Data, Fintech Winter & Why Right Now Is Spade's Best Moment
[00:00 – 08:30] How They Each Got Into Fintech
After some banter about how long ago 2023 actually was, Julie asks both guests to walk through how they first found their way into fintech.
Allen traces his path back to 2013, when he was at Columbia Business School and downloaded one of the very first versions of Betterment. He was so intrigued that he cold-emailed founder Jon Stein asking if he could do project work on the side — which turned into spending his second year of business school working with co-founder Eli Breiberman. (Catch Jon Stein on Season 1 of Fintech OGs if you haven't already.) From there, he moved into consulting, then investing, eventually joining Oak in 2019.
Oban's road is wilder. He co-founded a company called Hubli out of college — practice management software for wealth managers — and ended up doing Barclays Techstars in New York in 2019, living in a seven-by-five-foot bedroom in Chinatown. That was his first real exposure to the U.S. fintech universe, which felt almost foreign to him as a Canadian. He went back to Vancouver, COVID hit three months later, his first company ran out of money, and he stepped away to figure out what came next. What came next was Spade.
[08:30 – 16:00] The Origin Story of Spade
Spade was born out of necessity. Oban was doing odd jobs for fintech founders he'd met through Techstars — pitch decks, market sizing, whatever paid the bills — and noticed they were all complaining about the same thing: bad data. This was neo-bank heyday, everyone was building rewards programs and trying to create Cash App-style experiences, and the transaction data underneath all of it was a mess.
The initial idea was almost comically simple: what if they just built an API that returned logos? That's it. Clean logos on transactions. Oban asked a founder friend if he'd pay for that. He said yes. The catch: Spade wasn't an incorporated business yet and couldn't accept payment, so technically the first customer never paid. But the signal was there.
From that starting point, Oban and his co-founder Cooper made a bet that most people hadn't made: instead of throwing machine learning at transaction data (which Visa and Mastercard had already tried with infinitely more data), they treated it like a search problem. They hand-labeled everything. They scraped store locators. Oban got very good at a free Photoshop alternative called Photopea. They wrote regex by hand for every possible way a merchant name could appear in a transaction string. It was the least scalable approach imaginable — and it worked. In a blind comparison against a venture-backed competitor, Spade won by a wide margin. Oban found out via Slack.
[16:00 – 21:30] The Doubt, the Dip & What Made It Hard
Julie asks if there was ever a moment where the approach felt like it might not actually work. Oban's answer: yes — around merchant 1,500, when millions were still left to go. Every new customer brought new requirements, and match rates that looked great for one use case would crater for another. A consumer card company's transaction data looks completely different from a small business card company's. You're not just solving one problem; you're solving it again and again for every new context.
Allen adds that from the investor side, the hardest part of the problem was that it had to be solved across four dimensions simultaneously: coverage, accuracy, depth of attributes, and latency. The fact that Spade had built that capability across all four — plus picked up logos like Stripe, CashApp, and FIS — is what made Oak want to be involved.
Lauren offers a gentle caveat that match rates are well beyond 80% now. Oban clarifies they were talking about 2021.
[21:30 – 35:00] Career Highs and Lows — Fintech Winter Edition
Lauren asks both guests to share a career high and low.
Allen goes low first. Joining Oak in 2019 and then immediately navigating COVID, followed by the fintech correction of 2022 and 2023, meant a lot of very hard conversations with portfolio companies — about de-prioritizing roadmaps, letting go of people, figuring out how to survive when payment volume can go from steady to zero overnight without the recurring revenue buffer a SaaS company might have. SVB didn't help. The high: watching companies come out the other side stronger, some of them almost finding a second life after getting lean and then re-capitalized. He's also found real joy in watching companies in unexpected markets — Latin America, Canada — become genuine players.
Oban's low is the fintech winter in visceral detail. Spade had raised at near-peak valuations in March 2022 with Andreessen Horowitz, then watched their earliest customers — nearly all neo-banks — evaporate. They had to pivot quickly away from the PFM and aggregate data space when it became clear that market was collapsing. Revenue was essentially flat for a stretch. The discipline that came from it — building something people actually want to pay for, not just growing the top of the funnel — shaped how Spade thinks about the business today.
His high: right now. He describes it as finally living in the future state he'd been selling toward for years. Banks that once would have been dismissive are now the most eager buyers in the room, because they understand that whatever AI era they're entering, they need better underlying data to participate in it.
[35:00 – 42:00] Stablecoins, Crypto Skepticism & Where Spade Fits
Julie surfaces a comment Oban made earlier in the conversation — that he's a self-described crypto hater — and asks how Spade thinks about blockchain and stablecoin data.
Oban walks it back slightly to "skeptic" (he says Axios called him that once and he'll take it), and explains that his hesitation isn't about the technology, it's about where the market is going. For now, stablecoins aren't a focus — Spade needs to stay disciplined and serve the customers relying on them today. But the framework is clear: if stable coins become a meaningful payment rail for Spade's largest customers, Spade will be there. The core capability — deeply understanding who someone is transacting with and for what purpose — applies regardless of whether the underlying rail is a card, ACH, wire, or stablecoin.
Allen adds context from Oak's portfolio, including their investment in Bridge. His view: stablecoins are most relevant right now in international markets, particularly Latin America, where they're used not just for transactions but for savings and remittances. If Spade eventually expands internationally, that's where the stablecoin question becomes real. For now, it's probably a couple of years out.
[42:00 – End] Advice for New Graduates Entering Fintech
Julie closes by asking all three — plus co-host Lauren — what they'd tell a new grad trying to break into fintech, especially as AI eliminates more entry-level roles.
Oban's advice: go where you can learn, not where sounds good at dinner parties. He's always tried to find the places with the most interesting problems and the steepest learning curves, and credits a willingness to do the unglamorous work with a lot of what Spade has become. Fancy titles don't compound. Knowledge does.
Lauren's take: find a role where you're forced to really understand how the product works, not just sell it. She moonlights in product herself and thinks that depth, especially in fintech where the product complexity is real, is a superpower for anyone in a go-to-market function.
Allen's practical advice for 2026 specifically: become the best AI-enabled version of yourself in whatever role you're in, right now, while most of your peers are still sleeping on it. The productivity gap between early adopters and everyone else is widening fast, and there's a two-to-three year window to build a real advantage. His more meta advice: find the thing where work doesn't feel like work, and pursue that intersection of passion and difficulty — because that's where most of the real value in the world gets created.
Julie adds one more: think about the job you want after this next job, and choose the current role based on what skills it will give you to get there.
