Issuer Fraud Beyond Double Pledging: Notes From Our Webinar
In July we hosted a webinar on issuer fraud in structured credit with Steven Renwick, CEO of Tilores, and Chen Zamir, fraud strategy advisor and founder of Native[risk]. Natalie Schleiz and Nicolas Kipp spoke for Credibur. The question was simple: what can asset-backed lending borrow from industries that have been fighting fraud for years?
Double pledging is the fraud we already know about
Several recent collapses in private credit point to the same alleged mechanism. The same collateral was pledged to more than one lender. Each lender saw only its own slice of the book and relied on the borrower's own numbers. Nobody had the full picture, including some of the most sophisticated lenders in the market.
Double pledging gets the headlines. It is far from the only way an issuer can mislead its lenders.
Where issuer fraud happens in a debt facility
The first layer is the assets. Inflated receivables, double pledging and data drift all sit in the loan tape and portfolio data. The borrower compiles that data, and the lender rarely rebuilds it from the source.
The second layer is the documents. Fabricated invoices, missing collateral documents and fields that don't match between systems. Producing a convincing invoice or shipment confirmation keeps getting easier.
The third layer is the cash. Collections that never arrive, payments from the wrong entities, money moving in circles. Bank transactions are the hardest layer to fake. They are also the least watched.
The gap between what the lender sees and what is underneath
In a standard facility the lender sees the eligible pool, the borrowing base, covenant compliance, collections and arrears. All of it comes from the borrower's reporting. Underneath sit the loan management system, the documents and the bank accounts. In most facilities nobody checks one against the other independently.
What other industries already do
Payments and identity fraud teams have dealt with this for a long time, and it is where Steven and Chen have spent their careers. Detection there rests on three things. Coverage: data sources lenders never had automated access to, and transactions rather than balances. Frequency: daily data instead of a monthly report that is stale within days. And pattern analysis: behavior and non-obvious links between entities, not static rules.
How to detect double pledging before capital is drawn
Applied to a debt facility, it starts with the bank accounts. Connect directly to the originator's accounts and watch the actual cash, rather than relying on reported figures.
Then compare. If the eligible receivables claimed across all facilities are far larger than the cash actually moving through the business, that gap is a warning sign for over-pledging, however many lenders are involved.
Next, score the receivables against known fraud patterns: counterparty behavior, invoice timing, payment velocity. Outliers should surface before a drawdown request is approved, not in the next annual audit.
The structural fix sits underneath: a shared register that tracks unique asset identifiers across facilities. That stops a double pledge at the point of pledge, not at the point of funding.
Thank you, Steven and Chen, for a sharp discussion. If you want to see what this looks like on a live facility, schedule a demo, or read what independent verification actually looks like.