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.

Connect with Fintech One-on-One:

• Tweet me @PeterRenton
• Connect with me on LinkedIn
• Find previous Fintech One-on-One episodes