Fintech One-On-One

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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