Fintech One-On-One

Arpit Goel built his first company, Gamma, on a simple pitch: legacy data-loss-prevention tools took nine months to show value, and Gamma got customers there in two weeks. Palo Alto Networks acquired Gamma in 2021. Now Goel is running the same play in a completely different industry. Root is a payments orchestration layer that lets enterprises move money bank-to-bank in about five seconds, with no intermediary ever holding the cash. In this conversation, Arpit explains why he thinks the US is finally close to a tipping point on instant payments, why Root never takes custody of the money it moves, and how the company handles banks that can't yet receive instant payments.
What We Covered
Growing up in India, and the ADHD diagnosis that pushed him toward IIT Delhi
Why he calls himself an "ignorant" founder rather than an experienced one
The nine-months-to-two-weeks wedge that built Gamma, and why Root uses the same one
Discovering the payments inefficiency by reading through ADP's 10-K
Why 40% of US SMBs don't accept cards, and it isn't about the fees
The dual pressure of RTP and FedNow that made 2024 the right moment to start Root
The heart, arteries, and capillaries analogy for how Root fits into the banking system
What actually happens to money in the five seconds between sender and receiver
Why reliability, not transaction scale, is the hard engineering problem in payments
How Root handles banks that can't receive RTP or FedNow
Where stablecoins fit into a bank-rail-agnostic platform
Why Root wants to be the pipes underneath the industry, not the brand
Key Takeaways
SMBs refuse cards mostly because of settlement delay, not fees — restaurants earning their week's cash on a Saturday night don't see it until Tuesday, right when they need it most to restock.
Root never takes custody of funds. Money moves directly between the sender's and recipient's own bank accounts, and Root charges a fee on top rather than earning float.
Reliability, not transaction volume, is the hard engineering problem — Root has built retry and fault-tolerance systems, using the workflow engine Temporal, so a bank outage doesn't have to mean a failed payment.
Arpit sees instant payments as a market that hasn't tipped yet but is close — RTP and FedNow now operating together create sustained pressure that neither rail created alone.
About Arpit Goel
Arpit Goel is the founder and CEO of Root. He holds a computer science degree from IIT Delhi and a PhD from Stanford, and previously founded Gamma, a data-security company acquired by Palo Alto Networks in 2021, where he went on to lead product for the data-security business.
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René Saúl spent seven years running an offline agricultural lending business in Mexico before selling it and pouring the proceeds into Kapital, a bet that the future of B2B fintech in Latin America belonged to companies willing to become regulated banks. Today Kapital is the largest B2B fintech in the region, and René is the only founder in the space who has bought not one but two banks, one of the deals agreed to on a napkin.
What We Covered
Why the future of fintech is regulated, and why that was a contrarian call in 2021
René's seven years running an offline agricultural lending business in Mexico
The founding thesis behind Kapital's one-stop B2B banking ecosystem
How Mexico's electronic invoicing system became Kapital's underwriting moat
The "red car theory" of spotting opportunities before they arrive
Buying Banco Autofin on a napkin, and growing its deposits from $150 million to $400 million in three months
Acquiring the banking, brokerage and payments assets of Grupo Financiero Intercam
Building instant, 24/7 cross-border payment rails on top of SWIFT
Closing the small business financing gap with AI-native underwriting
Why Mexico is becoming a cornerstone of America's AI manufacturing boom
The limits of banking an economy that still runs largely on cash
Kapital's growth numbers and its path to a dual listing in New York and Mexico
Key Takeaways
Mexico's electronic invoicing mandate hands Kapital more than 50,000 data points per customer, a seven-year head start on underwriting that competitors using third-party providers cannot easily close.
For large enterprises and cash-strapped SMBs alike, a banking license, not a slicker app, is what earns the trust needed to hold their money and their cash flow.
Opportunities have to be hunted, not waited for. Kapital tracked potential bank acquisitions for years so it could move in days when the Autofin deal appeared.
Staying liquid and profitable before either acquisition is what let Kapital move fast when the opportunity came, rather than scrambling to raise capital under pressure.
About René Saúl
René Saúl is the co-founder and CEO of Kapital, which he built after selling an offline agricultural lending business that financed berry and avocado exporters in Mexico and Peru. Under his leadership, Kapital has grown into a licensed financial group serving more than 300,000 customers across Latin America, with more than $5.3 billion in assets and two bank acquisitions behind it.
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Enova International has spent two decades using machine learning underwriting to serve consumers and small businesses who sit outside prime bank criteria, and its pending $369 million acquisition of Grasshopper Bank would give it a national charter for the first time. Steve Cunningham became CEO in January 2026 after nearly a decade as the company's CFO, following earlier stops as a bank regulator at the FDIC and as chief risk officer at Discover. He joins the show to explain what a fully digital lender looks for in a nonprime borrower, why credit quality looks solid in his portfolio right now, and how he's answering the senators and state attorneys general who want regulators to block the Grasshopper deal.
What We Covered
Steve's path from FDIC regulator to Capital One, Harley-Davidson, and Discover
Moving from the CFO chair to the CEO chair six months in
Enova's brand portfolio: CashNet, NetCredit, and OnDeck
Underwriting nonprime and near-prime consumers versus underwriting small businesses
The lift Enova's proprietary models get over a plain FICO or VantageScore
Why all their products use different underwriting models
What Enova's weekly vintage data shows about the health of the consumer
Why gas prices matter less to consumer spending than headlines suggest
How Enova is using generative and agentic AI across the business
The real thesis behind the Grasshopper Bank acquisition (see my podcast with CEO Mike Butler)
Steve's response to the senators and state attorneys general opposing the deal
What banking-as-a-service adds to Enova's roadmap
Where Enova wants to be by 2030
Key Takeaways
Enova's NetCredit yields and losses aren't outliers when benchmarked against what banks themselves report to the FDIC each quarter, Cunningham argues, pushing back on the "predatory" framing critics apply to the company.
The Grasshopper deal is primarily about simplifying a patchwork of direct state licenses and bank partnership arrangements, not chasing cheap deposits, though the deposit base is a welcome bonus.
Because Enova's consumer loans repay every two weeks or faster, the company sees shifts in borrower behavior in its own vintage data well before those shifts show up in macro statistics.
Small business underwriting at Enova is built around the health of roughly 900 different industry codes rather than a borrower's personal credit, making it a fundamentally different discipline than consumer underwriting.
About Steve Cunningham
Steve Cunningham is CEO of Enova International, a role he took on in January 2026 after nearly a decade as the company's CFO. He previously served as chief risk officer and treasurer at Discover, CFO of Harley-Davidson Financial Services, held senior finance roles at Capital One, and began his career as a bank regulator at the FDIC.
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Very few people in this industry have sat in all three of the seats that matter in the bank-fintech story. Amanda Swoverland started as a compliance examiner at the Federal Reserve Bank of Minneapolis, spent nine and a half years at Sunrise Banks rising to Chief Risk Officer, then joined Unit as its fourth employee and Chief Compliance Officer. Six months ago she became President of Hatch Bank, a California-chartered ILC that works exclusively with fintech lending partners. She still describes herself as a banker at heart, and this conversation is a good explanation of why that matters more now than it did five years ago.
What We Covered
From Fed compliance examiner to bank president
Why she was never the department of no
Learning product and sales inside a fintech infrastructure company
Hatch Bank's credit-only model, with no deposits
The five lending verticals Hatch focuses on
Going deep with a few partners instead of diversifying across 30
What a fintech gets from a small sponsor bank that scale cannot offer
Lifting a BSA/AML consent order in under a year
"Maturing for scale" as the theme of her first six months
Using AI internally without sending agents out into the wild
Why the quality of founders approaching sponsor banks has gone up
The direct versus not direct debate after Synapse
Why every fintech should have a second bank partner
Where AI is genuinely working in compliance today
DIDMCA, state charters and the usury patchwork
What separates the sponsor banks that survive the next cycle
Key Takeaways
The "direct versus not direct" framing that took hold after Synapse is, in Amanda's view, a distraction. If a bank has a program, the bank is in charge of it, whatever technology sits in the middle and whoever is acting as program manager. Everything else is a question of how you oversee it, not who is accountable.
The next failure will not look like Synapse, because that particular gap has been closed. What worries her is banks that never learned the fundamentals: liquidity, credit oversight, BSA/AML, and how a multi-party lending program behaves when the cycle turns and payments stop arriving on time.
A second bank partner is good for the fintech and good for the bank. Concentration risk cuts both ways, and Amanda actively introduces her own clients to other banks she trusts, and is happy to be someone else's second bank.
Compliance is heading toward 100 percent sampling. Amanda thinks the days of testing a selected sample of transactions or complaints are ending, provided you test the system, watch the outputs, and keep a human in the loop.
About Amanda Swoverland
Amanda Swoverland is President of Hatch Bank, a San Marcos, California ILC that works exclusively with fintech lending partners across home improvement, small business, clean energy, student lending and healthcare financing. She began her career as a compliance examiner at the Federal Reserve Bank of Minneapolis, spent nine and a half years at Sunrise Banks where she became Chief Risk Officer, and then five and a half years at Unit as Chief Compliance Officer, joining as the company's fourth employee. She was named to Forbes' 2026 list of the women shaping fintech infrastructure and banking strategy.
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Mike de Vere runs Zest AI, a company that has been applying machine learning to credit underwriting for over two decades, starting with some of the largest banks on the planet and now serving a large share of the credit union market. Since his last appearance on the show three years ago, Zest has expanded well past underwriting into fraud detection and portfolio management, tied together by an intelligence layer and a generative AI companion called LuLu. Mike makes a specific argument in this conversation: machine learning still makes the credit decision, generative AI makes the feedback loop faster, and the real advantage available to community financial institutions is a willingness to pool what they know.
What We Covered
Zest today, from underwriting to fraud to portfolio management
Why the intelligence layer is what makes an ecosystem
Starting with Discover, Citi and Freddie Mac, then moving down market
LuLu, named after a corgi, and what she actually does
Safety and soundness as the first use case for most institutions
Replacing quarterly reports that used to take weeks
Peer benchmarking versus building your own data lake
Collective intelligence across 2,000 credit models in production
Why generative AI has no role in making the credit decision
Shrinking model refit cycles from 18 months to daily evaluation
Zest customers versus non-customers on growth, delinquency and efficiency
Cash flow underwriting, and why generic national models fail
Zest Protect and fighting AI-powered fraud with AI
The two objections that come up most in sales conversations
Takeaways from the IQ AI Lending Forum in Santa Fe
Key Takeaways
The performance gap is measurable. Comparing Zest customers to non-customers across 2024 and 2025, Mike says his customers grew 16 times faster, ran roughly 20 points lower on delinquency, and were 501 basis points better on efficiency ratio.
Generative AI belongs around the credit decision, not inside it. Zest still uses supervised, locked-down machine learning models for underwriting, because a regulator will ask you to explain the decision. What generative AI changes is the speed of evaluation, from an 18-month refit cycle to daily.
Comparison is where the value sits. A lender looking only at its own data lake has visibility on itself and nothing else. LuLu is built to normalize performance data across institutions so a chief lending officer's instinct can be checked against thousands of real policy instances rather than one career's worth of experience.
Community lenders have a structural advantage they underuse. The credit union industry holds roughly $2.4 trillion in assets. If it acted as one institution, it would be bigger than Wells Fargo, and unlike the big banks these institutions are actually willing to share.
About Mike de Vere
Mike de Vere is the CEO of Zest AI, the AI lending technology company that has been doing machine learning in credit since well before AI became a standard fintech conference track. He came to Zest from a career in data and consumer insights, with leadership roles at J.D. Power, The Harris Poll and Nielsen. Zest now touches $5.6 trillion in assets under management, and by the end of this year expects one in three credit union members to have their consumer loans decisioned with its technology.
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