Tokenized FTX claim is used as collateral for a loan

Spread the love

A creditor of now-bankrupted crypto exchange FTX pledged a claim as collateral for a loan in the decentralized finance (DeFi) protocol Arcade. The transaction was the first on-chain loan backed by an FTX claim, according to the bankruptcy claims platform Found.

The $31,307 claim was tokenized, and its ownership was represented by a nonfungible token (NFT). On June 23, the NFT was used as collateral for a $7,500 loan to be repaid in five days. In the event of a payment default, the lender is entitled to the claim.

The transaction is an example of real-world assets (RWA) tokenization, in which a token represents an asset’s ownership rights on a blockchain. Within DeFi, asset tokenization is one of the most prominent areas, as a wide range of real-world assets can be tokenized, including stocks, government bonds, real estate and commodities.

On Twitter, Found said the original creditor and lender went through its biometric Know Your Customer and Anti-Money Laundering screenings. According to the company’s website, it allows users to access loans using bankruptcy claims as collaterals under a 10% transaction fee on successful trades.

Related: Mainstream media challenge decision to protect FTX customers: Report

Crypto exchange FTX filed for bankruptcy in November 2022, locking billions of dollars in users’ accounts for court proceedings. According to some estimates, FTX claim holders could recover between 35% and 66% of their face value.

Crypto-related bankruptcy cases have flooded the courts in the past year — many stemming from the collapse of FTX — including cases associated with crypto firms Genesis Global Trading and BlockFi.

The surge in bankruptcy filings is driving on-chain claims solutions. Found, for example, was launched at the beginning of this year, and the co-founders of collapsed hedge fund Three Arrows Capital launched the claims trading platform Open Exchange in April.

Magazine: ‘Moral responsibility’ — Can blockchain really improve trust in AI?