Yuval Refua is the Chief Product Officer at Navan, the global travel and expense platform he joined seven years ago when it was still just a travel booking service. Since then, he has built out its payments and expense products from the ground up, turning the company policy that used to live in a PDF into code that runs on the card itself. This conversation matters because T&E is one of the most universally disliked workflows in business, and Navan is rethinking it from scratch just as AI and agentic commerce start to reshape how companies spend.

What We Covered

• Falling in love with credit cards at American Express
• Why Navan started as a travel-only booking service
• The reconciliation pain that led to launching a card
• Coding company policy directly onto the card
• Real-time approval the moment you swipe
• Why travel-first beats procurement-first
• Context as the key to managing distributed spend
• Going global with VAT, GST, per diems and mileage
• The e-invoicing wave hitting more countries
• The GTA model for revealing complexity gradually
• The Expense Admin Companion and recommended actions
• From single approvals to bulk to full automation
• The Visa partnership and the Connect product
• Waymo for travelers, Formula One for finance

Key Takeaways

• The expense report exists to answer a question that company policy already settled. Coding that policy onto the card removes the work instead of automating it.
• Starting from travel gives Navan context (where the employee is, why they are there, who they are visiting) that procurement-first tools lack, which makes per-employee limits far smarter.
• Going global is less about features and more about mastering country-by-country tax, e-invoicing, per diem and mileage rules.
• The path to full automation runs through trust. Navan moves finance teams from a single recommended action, to bulk approvals, to hands-off automation, which is also how it intends to handle agentic spend.

About Yuval Refua

Yuval Refua is Chief Product Officer at Navan. He started two companies of his own early in his career before moving into fintech and product management at Thomson Reuters, then American Express, where he developed a deep love for credit cards and the rails behind them. He joined Navan around seven years ago and has built out its payments and expense products from the ground up.

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This episode is part of our occasional Fintech Revealed series, where we do an extended deep dive into one topic with two industry experts. The topic today is vertical fintech, and I am joined by Matt Hennessy, the Business Lead at Increase, the modern banking infrastructure company, and Jamie Fox, the General Manager of Fintech at Tekion, the AI-native cloud platform that runs the entire business for auto dealerships across the US, Canada, and the UK.

Tekion built its embedded banking on Increase, so the two of them give us both sides of the same story: the platform that lives inside the dealership and the infrastructure that connects it to the banking system. We get into the surprisingly large money flows inside a single dealership, why paper checks still beat instant rails for many operators, how compliance and trust get engineered into the product, and just how big this embedded banking opportunity gets.

What We Covered

• What vertical fintech is and why it matters now
• The money flows hiding inside a single car dealership
• Why outbound dealer spend is roughly 2x inbound
• Operating account vs. ledgering account adoption paths
• Dealer-to-dealer payments as a ledger change with zero rail fees
• Instant rails: RTP, FedNow, and Request for Payment
• The persistence of paper checks and the cost to operationalize them
• Direct Fed access vs. layers of middleware
• Compliance as code, codified into the product
• Building trust in building blocks
• Where agentic payments and "know your agent" fit in
• How large the embedded banking opportunity ultimately gets

Key Takeaways

• Owning the financial system of record inside core operating software is the defensible position in an age when light "systems of engagement" can be replicated with AI.
• Outbound payments, not inbound, are the bigger prize: US auto dealerships pushed out roughly $1.3 trillion in 2024, about 2x what they took in.
• The barrier to instant rails is education, not technology. Many dealers do not know RTP or FedNow exists, or that they can pay a vendor any day of the week.
• Trust cannot be launched all at once. Holding a dealer's operating cash is a different level of trust than processing a payment they can fall back on, and it is earned in building blocks.

For the founding story and more about Increase, check out my conversation with CEO and Founder Darragh Buckley from last year.

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Elliott Lorenz took an unusual path into consumer lending, moving from applied mathematics and high-frequency trading into the business of pricing credit risk. Today he is the CEO and co-founder of Edge Focus, a technology-enabled private credit firm that sits between consumer lending platforms and the institutional investors who want to deploy capital into the asset class. In this episode, Elliott explains how the firm's credit engine works, why speed is its biggest edge, and how he reads the recent wave of criticism aimed at private credit.

What We Covered

• From engineering and applied math to high-frequency trading
• What Michael Lewis's Flash Boys got right and wrong about HFT
• Spotting an edge in LendingClub's public loan data
• Turning a data-science hobby into Edge Focus
• The Origin credit engine and how it makes decisions
• Expanding a lender's credit box with an orthogonal view of credit
• Modeling with a single month of payment history
• Updating a credit model within a day
• The Lens portfolio analytics tool
• Where alpha comes from beyond the underwriting model
• Fraud and asset liability mismatch in private credit
• Building the EDGEX ABS shelf and partnering with Fortress
• Proving ML models are free from bias
• Where consumer lending goes over the next few years

Key Takeaways

• Edge Focus competes less on having a single better model and more on combining technology, capital, and platform relationships in one package, which Elliott calls the firm's "big unlock."
• The firm can incorporate even a single month of payment history into its models and push an update within a day, letting it react to macro shifts faster than firms that wait 12 to 24 months for data.
• Most of the recent private credit criticism falls into two buckets, fraud and asset liability mismatch, and Elliott sees the fraud cases as largely idiosyncratic and the redemption problems as a function of investors misjudging illiquid assets.
• Because Edge Focus invests its own capital alongside partners rather than acting as a pure technology vendor, its incentives are tied directly to loan performance.

About Elliott Lorenz

Elliott Lorenz is the CEO and co-founder of Edge Focus, a technology-enabled private credit firm focused on consumer lending. He trained as an engineer and applied mathematician, earned a master's in finance from Princeton, and spent several years in high-frequency trading before bringing those modeling techniques into consumer credit in 2013.

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Andrew Davies has spent more than three decades fighting financial crime, starting with sanctions screening tools for central banks in the mid-1990s and arriving at ComplyAdvantage after nearly 16 years at Fiserv. He sits at the center of one of the most consequential questions in financial services: can we finally move the needle on financial crime detection after decades of catching less than 2% of what's laundered globally?

ComplyAdvantage serves more than 3,000 enterprises across 75 countries with its AI-native Mesh platform. If you want to learn more about the founding story and their early days, check out my podcast with founder Charlie Delingpole from 2019.

What We Covered

• Why the industry has historically caught less than 2% of money laundered globally
• How the money laundering economy ranks as the world's third largest at an estimated $5.6 trillion
• The evolution from sanctions screening to FRAML to multi-dimensional financial crime risk
• The Mesh platform and what a unified financial crime system means for compliance teams
• Cassie, the agentic AI analyst automating customer screening investigations
• How 90% of compliance work was historically spent chasing false positives
• Real-time payments compliance and the risk-based approach to payment screening
• The SEPA Instant Payments challenge and batch screening against the EU journal
• Stablecoins, unhosted wallets, and the compliance infrastructure gap
• FATF's finding that stablecoins represent 84% of illicit crypto transaction volume
• Data sharing consortiums as the next inflection point in fighting financial crime
• The network problem at the heart of money laundering and terrorist financing

Key Takeaways

The money laundering economy is estimated at $5.6 trillion, making it the third largest in the world, above Germany, yet we detect less than 2%. Agentic AI tools like Cassie are designed to eliminate false positives so human analysts only work cases that genuinely warrant their expertise. Data sharing consortiums, where organizations contribute to shared detection models, represent the most promising path to materially improving financial crime outcomes. Stablecoins create real compliance risk at the unhosted wallet layer, the Bank of England has floated a ban, while the US is unlikely to go that route, leaving a gap.

About Andrew Davies

Andrew Davies is the Global Head of Financial Crime Compliance Strategy at ComplyAdvantage. He began his career in the mid-1990s building sanctions screening tools for central banks and large financial institutions, and spent nearly 16 years at Fiserv in their financial crime division before joining ComplyAdvantage.

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Joshua Silver has spent two decades in embedded payments. Before co-founding Rainforest, he built Patient Co, a healthcare payments business scaled to billions in processing volume and tens of millions of patients, then spent several years consulting with software founders on building their payments programs. Rainforest is payments as a service, purpose-built for vertical SaaS — and in this conversation Joshua makes a compelling case that embedded payments is not just a revenue opportunity but a competitive moat.

What We Covered

• Why vertical SaaS companies are still leaving money on the table with embedded payments
• The gap in the market Rainforest was built to fill
• How payfac as a service works and who it is designed for
• Why the number of registered payfacs is shrinking, not growing
• The $5 billion volume threshold for when becoming a full payfac makes economic sense
• How Rainforest differentiates from Stripe and Adyen for vertical SaaS platforms
• Vertical-specific risk models versus general-purpose tools
• Rainforest's real-time ledger and what it unlocks for complex payment structures
• Adding PayPal and Venmo for untapped vertical SaaS markets
• Expanding into Canada and building the playbook for international growth
• How AI is being used across the business and the rising threat of AI-driven fraud
• What success looks like for Rainforest in the next five years

Key Takeaways

Embedded payments builds a moat. Joshua's closing point is the sharpest: once merchants are running their money through your software platform, competitors face a much harder job dislodging you. Payments isn't just a revenue line — it's a retention strategy.

Vertical-specific risk models matter enormously. Stripe and Adyen have to serve everyone, so their risk tooling is built for the lowest common denominator. Rainforest has built models tuned to individual verticals — lawn care looks different from HVAC, which looks different from nonprofit donations — and it takes the fraud liability rather than passing it to the platform.

The $5 billion payfac threshold is the new reality. A decade ago the rule of thumb was around $1 billion in card volume. Regulatory and compliance burdens have risen so sharply that Joshua now puts the threshold at $5 billion with line of sight to $10 billion before it makes economic sense to go full payfac.

A real-time ledger is a competitive differentiator. Most legacy processors are batch-based, settled overnight on mainframes. Rainforest's ledger is real-time, enabling split payments, franchise fee hierarchies, and complex billing structures that batch systems simply cannot support.

About Joshua Silver

Joshua Silver is co-founder and CEO of Rainforest, a payments-as-a-service company purpose-built for vertical SaaS platforms. Before Rainforest, he co-founded Patient Co, scaling it to billions in healthcare payments volume before a sale, and subsequently consulted with software founders on building their payments businesses. He has been working in embedded payments for twenty years.

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Michael Tannenbaum became CEO of Figure in early 2024, taking over from founder Mike Cagney and leading the company through its September 2025 IPO. In this conversation, we get into the mechanics of how Figure's blockchain-based platform competes with Fannie Mae and Freddie Mac, what it actually takes to cut mortgage origination costs from $12,000 to $1,000, and where the real opportunities in tokenization lie.

What We Covered

• Taking over as CEO from Mike Cagney and the Big Rocks framework
• How Figure describes itself: building the future of capital markets on blockchain
• The B2B partner network and how it compares to Fannie Mae's function
• Cutting mortgage origination costs from $12,000 to $1,000 and 45 days to five
• Why Figure competes directly with Fannie Mae and Freddie Mac
• How blockchain eliminates third-party diligence and prevents loan double-pledging
• The Figure Connect marketplace and its rapid growth since June 2024
• Where tokenization adds real value — and where it doesn't
• YLDS: Figure's SEC-registered yield-bearing stablecoin and its role in capital markets
• The timing and mechanics of Figure's September 2025 IPO
• Building a rate-agnostic business across different macro environments
• Three growth areas: consumer mortgages, Democratized Prime, and on-chain equities

Key Takeaways

Figure's origination platform and its capital market are the same system — you can't separate them, and that's the competitive moat. Tokenization only creates liquidity when the underlying assets are standardized and fungible; putting unique assets on a blockchain doesn't conjure buyers. The recent fraud cases involving double-pledged loans (Tricolor, First Brands, MFS) have turned blockchain's immutability from a skeptic's objection into a selling point. And Figure is running at what Michael calls the rule of 150 — 100% year-over-year growth at 50% margins — in one of the most rate-sensitive and entrenched markets on earth.

About Michael Tannenbaum

Michael Tannenbaum is the CEO of Figure, a blockchain-based capital markets company he took public on Nasdaq in September 2025. Before Figure, he was an early executive at both SoFi (Chief Revenue Officer) and Brex (COO), and sat on the Brex board when it was acquired by Capital One. He began his career in investment banking at J.P. Morgan.

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Thomas Galbraith is the CEO and co-founder of Barkr, an AI-driven valuation platform for asset-backed lending. He spent his early career in high net worth insurance at AIG and AXA, where he grew comfortable with the challenge of pricing hard-to-value assets. That thread ran through every role he held until it crystallized into a company built around a simple but structural problem: in asset-backed lending, appraisers give you a price and then spend the rest of their report telling you they're not responsible for it. Barkr is built to change that.

What We Covered

• Thomas's background in high net worth insurance at AIG and AXA
• How a common thread across luxury assets led to founding Barkr
• Starting with fine art and private jets before expanding to other asset classes
• The two-part failure in traditional appraisals: accuracy and absence of liability
• How Barkr pairs an AI valuation with a contractual performance warranty
• The progression from Lloyd's of London to AXA to Munich Re
• $2 billion in covered valuations and what patience actually means in this business
• GPUs as a surprisingly durable and long-lived collateral asset class
• How Barkr finds clients, from pavement pounding to Nvidia referrals
• Monthly mark-to-market on hard assets throughout a loan's life
• Building a domain-specific LLM with human review in the loop
• Plans to build an in-house insurance vehicle to unlock capacity

Key Takeaways

Traditional appraisal firms hedge their liability by design. Page one is the price; the rest of the report is the disclaimer. Barkr's contractual warranty flips that model by standing behind the number.

Barkr's data on GPU durability challenges the conventional narrative. Chips five and seven years old are still generating revenue and still have meaningful resale value, which changes the risk calculus for lenders considering AI infrastructure as collateral.

Augmenting, not replacing, is the right positioning for valuation technology. Barkr actively encourages clients to keep using their existing appraisers and treats third-party appraisals as additional data inputs that improve their own accuracy.

Building a reinsurance relationship takes years. Barkr worked through Lloyd's, then AXA, before landing Munich Re, and each step required demonstrating proof of concept at the prior level first.

About Thomas Galbraith

Thomas Galbraith is the CEO and co-founder of Barkr. He began his career in high net worth insurance at AIG and AXA before founding Barkr to bring accountability and AI-driven accuracy to asset valuation in the lending market. Barkr has covered approximately $2 billion in valuations across art, private jets, vehicles, and GPUs.

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Patricia Montesi didn't start her career in payments, she started it in car rental. After nine years at Alamo and National Rent-A-Car, she was recruited into fintech with zero industry experience. That outsider perspective became her edge, and she never let go of it. Today, she's the CEO and co-founder of Qolo, a payments infrastructure platform that combines card issuing, money movement, and a bank-grade ledger on a single API-first stack.

What We Covered

• How nine years in car rental shaped Patricia's outsider approach to payments
• Getting recruited into Wild Card Systems with no payments background, and why that fresh lens became an advantage
• The fragmentation problem at the heart of payments infrastructure and why point products create hidden complexity
• Qolo's three-product suite: Quantum Ledger, Qascade money movement, and Qinetic card issuing
• Why Qolo isn't quite a side core, it overlays and integrates with existing bank cores rather than running in parallel
• Rail agnosticism and why Qolo still supports checks in 2026
• The dual go-to-market: commercial banks and B2B fintechs, same platform, different vernacular
• How the Synapse collapse changed the ledger conversation for banks and fintechs alike
• Winning KeyBank in a competitive RFP against much larger players, and launching virtual account management in nine months
• How banks are using Qolo to protect commercial deposits from modern non-bank competitors
• AI inside Qolo: from Glean to Claude, and their internal "Turning Hours into Minutes" program
• 130% year-over-year growth and 142% net revenue retention

Key Takeaways

The moat problem: Patricia set out to build a company where customers stay because of the value delivered, not because switching is too painful. That philosophy shaped every product decision at Qolo.

Ledger first: Most point-product fintechs have basic ledgers that only support one rail. Qolo's bank-grade dual-entry forward-posting ledger underpins every rail, making reconciliation and real-time money visibility a solved problem rather than a vendor management challenge.

Synapse's legacy: The debacle forced banks and fintechs alike to ask harder questions about who actually owns the ledger and where money sits at any given moment. Qolo had been making that argument for years before the market was ready to hear it.

Bank as distribution: KeyBank and Huntington aren't just clients — they're strategic investors using Qolo to defend their commercial deposit base against modern non-bank alternatives.

About Patricia Montesi

Patricia Montesi is CEO and co-founder of Qolo, a payments infrastructure company she built from the ground up after more than 20 years in the industry. She started her career at Alamo and National Rent-A-Car before being recruited into fintech with zero payments background — an outsider perspective she has held onto ever since. At Qolo, she and her team built the ledger, money movement, and card issuing stack as first-party infrastructure, without relying on third-party processors underneath.

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