At ETHConf in New York City, a highly technical fireside chat took place between Reid Simon, Head of Democratized Prime at Figure, and David Hoffman, Co-Founder of Bankless. Entitled “Fireside Chat with Reid Simon,” the session offered an analytical deep dive into the operational realities of institutional real-world asset (RWA) tokenization.

While the first generation of tokenization focused primarily on static, reserve-backed instruments like fiat stablecoins or gold tokens, Simon detailed a secondary paradigm: bringing the entire ancillary lifecycle of highly complex credit instruments entirely on-chain. From origination and credit decisioning to warehousing, tokenized borrowing markets, and secondary securitization, the conversation mapped how structured finance is migrating onto decentralized rails to bypass the monopolistic cost structures of legacy banks.

Bypassing the $11,000 Legacy Bottleneck

Hoffman opened the panel by asking why Figure, a highly successful financial platform founded by Mike Cagney (the original architect behind SoFi), chose to build its core on-chain credit pipeline around Home Equity Lines of Credit (HELOCs), a seemingly niche and esoteric asset class.

Simon explained that the selection of HELOCs was a deliberate, counter-cyclical engineering play designed to attack a structural inefficiency embedded in traditional banking frameworks. Under legacy TradFi infrastructure, the administrative, legal, and operational overhead required for a financial institution to originate a standard home equity loan is staggering:

“If you’ve bought up a house in the US, the mortgage process is quite difficult, it’s expensive, and it takes a really long time… Ultimately, for the bank to originate that loan, it cost somewhere around 11 or $12,000. So when you think about… what is the size of the loan and the interest rate you need… for the bank to then make that profitable, it’s quite high.”

This massive operational friction effectively prices out smaller, consumer-tier credit lines. If a homeowner with $1 million in outright equity seeks a modest $20,000 loan to complete home repairs, a traditional bank cannot mathematically process that loan at a profit.

By rebuilding the entire credit stack on top of a public ledger, Figure slashes the origination time from months to minutes and drives the administrative cost floor to near zero. This optimization transforms a once-unprofitable banking product into a highly scalable, automated primitive. To date, Figure’s ecosystem has originated over $23 billion in blockchain-based credit lines, powered by a network of 380 structural partners plugging directly into its technology stack on the Provenance blockchain.

Democratized Prime: Unifying RWA Liquidity and Isolated DeFi Vaults

A persistent criticism of early-stage RWA implementations has been the “represented vs. distributed” liquidity trap. Many legacy institutions have used blockchains purely as a glorified internal recordkeeping system, inflating Total Value Locked (TVL) metrics on-chain while keeping the actual assets entirely isolated from public trading venues.

To transition from a static ledger record to an active, liquid asset, a tokenized product must demonstrate genuine on-chain economic utility. Figure achieves this through its flagship product, Democratized Prime, which acts as a liquid borrowing and financing market built against AAA-rated HELOC tokens.

Historically, Figure relied on traditional, highly restricted warehouse financing lines provided by Tier-1 investment banks to fund loans before they were packaged into secondary securitizations. These monopolistic middlemen routinely charge up to 300 basis points over SOFR (Secured Overnight Financing Rate) for virtually risk-free, senior-secured exposure.

The Morpho isolated Vault Strategy

To break this monopoly, Figure deployed its credit primitives across public DeFi infrastructure, specifically utilizing the Morpho Blue protocol on Ethereum. Simon noted that while Figure originally launched an MVP on Solana, the sheer depth of deep institutional stablecoin liquidity on Ethereum made EVM integration a necessity.

Morpho’s isolated market architecture allows Figure to spin up customized, asset-specific lending vaults:

• Whitelisted Curation: Vault curators can audit the performance data of Figure’s $23 billion underlying credit portfolio, enabling deep risk analysis.
• Cost of Capital Optimization: By connecting these real-world credit assets to the public stablecoin market, Figure can finance warehouse credit lines on Morpho at 4.4%, well below the 6.7% rates typically demanded by legacy bank warehouse facilities.
• Narrow Banking Disintermediation: This creates a direct competitive rail to commercial banks, allowing ordinary stablecoin depositors to act as the warehouse financiers for real-world American consumer debt.

Global Access to the American Consumer Credit Layer

When assets are successfully migrated onto public commercial blockchains, it broadens the potential user base, opening up access to completely new capital pools. Simon broke down the current on-chain capital mix into two distinct growth segments:

The first cohort consists of native DeFi participants, vault curators, yield-aggregators, and individual decentralized lenders who thoroughly audit historical loan-performance telemetry and supply capital into the Morpho pools. This native stablecoin liquidity has been highly sticky, with tokenized credit markets maintaining an average 95% utilization rate.

The second, and potentially larger, growth vertical consists of international capital coming on-chain for the first time specifically to capture stable, institutional US credit yields:

“We’ve been having a lot of conversations with Asian family offices and high-net-wealth [individuals]. Access to American consumer credit is nearly impossible for them to access… They say, ‘Okay, let’s actually discuss how do I bring some capital on-chain to access this liquidity.’ So I’m optimistic about new capital entering.”

For international family offices and sovereign wealth management, navigating the compliance overhead, legal restrictions, and localized brokerage requirements to buy into American consumer debt portfolios is incredibly complex. Tokenization reduces this friction, allowing capital to cross borders instantly via public smart contracts.

Expanding the Credit Matrix: Auto Loans and Residential Transitions

Rather than remaining concentrated in a single real estate vertical, Figure is scaling its tokenization model into a generalized framework for multi-asset class credit issuance. The protocol is building out comprehensive strategic partnerships to capture the entire lifecycle of separate lending industries:

• On-Chain Auto Finance: Partnering with Bora, an AI-driven loan originator, to deploy auto-loan originations, distributions, and financing directly onto Figure’s underlying blockchain platform.
• Residential Transition Loans (RTLs): Announcing the acquisition of Kiavi, an originator specializing in residential transition and real estate flip financing, to bring another high-yielding asset class on-chain.
• Trade & Inventory Infrastructure: Actively developing specialized lending rails for small and medium-sized businesses (SMBs), focusing heavily on inventory tracking and international trade finance.

The Technologist’s Takeaway

The fireside chat between Reid Simon and David Hoffman highlights a core structural transformation: the rise of the narrow banking thesis. Blockchains are fundamentally designed to eliminate un-needed intermediaries, and the traditional commercial bank is the ultimate middleman.

By combining institutional asset origination with clean, automated data tracking and composable DeFi lending protocols like Morpho, financial technology is creating a far more efficient capital marketplace. With Figure projecting its on-chain assets on Ethereum to scale securely into the billions by the end of 2026, the mandate for systems architects is clear: the future of finance lies in building automated, programmatic bridges between deep real-world debt and public, decentralized liquidity layers.

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