Brazil has registered its first livestock-backed tokenized loan on B3, the country's main stock exchange and financial market infrastructure provider, marking a new milestone in the intersection of agricultural finance and digital asset technology.

Pilot Transaction Details

A dairy farmer in the southern state of Paraná secured a 100,000-real loan by pledging 10 tokenized Holstein cows as collateral. The livestock carried an estimated value of 120,000 reais, ensuring the collateral exceeded the loan amount. Cowmed and Target FIDC structured the financing, while B3 recorded the transaction on its registry.

Each cow received a unique digital identity linked to B3's registry system, enabling lenders to verify ownership more efficiently and preventing borrowers from using the same animal to secure multiple loans simultaneously. This addresses a longstanding challenge that has historically deterred financial institutions from accepting livestock as collateral — a significant gap in a country that maintains one of the world's largest commercial cattle herds, with more than 200 million head of cattle nationwide.

The transaction introduces blockchain-based verification into agricultural finance without altering the underlying value of the physical assets. Instead, it creates a persistent digital record connected to each animal throughout the financing period. For Brazil's agricultural sector, which accounts for a substantial share of national economic output, expanding collateral options through digital infrastructure could open credit channels for producers who have limited access to traditional bank financing.

AI-Powered Livestock Monitoring

Cowmed's financing model is supported by its AI-powered Smarty Collar, which tracks every pledged animal in real time. The device monitors each cow's health, location, and daily behavior, linking that data to its digital identity.

Cowmed representative Thiago Martins told CNN Brasil that the company transforms a physical cow into a digitally monitored asset backed by a unique identification code. This provides lenders with continuous verification that the collateral remains available throughout the life of the loan.

The system offers flexibility for herd management. If an animal dies, the farmer can replace it without disrupting the financing agreement. Borrowers may also add livestock to increase collateral on an existing loan.

Brazilian banks have traditionally been reluctant to accept livestock as collateral due to difficulties in ownership verification and animal tracking. These limitations created legal uncertainty, increased lending risks, and restricted financing opportunities for smaller agricultural producers.

Cowmed currently monitors approximately 100,000 dairy cows across more than 1,000 farms, with the monitored herd valued at over 2 billion reais. The company estimates that roughly one-fifth of those farms could eventually adopt tokenized financing, potentially unlocking as much as 400 million reais in additional agricultural credit.

B3's Broader Tokenization Strategy

The livestock-backed pilot aligns with B3's wider digital asset strategy, as the exchange develops infrastructure for tokenized real-world assets alongside a stablecoin pegged to the Brazilian real.

The initiative reflects broader growth across the tokenization sector. Tokenized real-world assets reached an estimated value of $34 billion in 2026, led by United States Treasury assets, followed by commodities and private credit.

Market forecasts point to significant expansion. McKinsey projects tokenized assets could reach $4 trillion by 2030, while Standard Chartered estimates the market could grow to as much as $30 trillion by 2034.

Brazil's first tokenized livestock-backed loan demonstrates how digital asset infrastructure can modernize agricultural financing without replacing traditional collateral. If the pilot performs as expected, tokenized livestock could provide farmers with broader access to credit while giving lenders greater confidence through real-time asset verification. The outcome may also inform whether other agricultural economies with large livestock sectors adopt similar tokenization frameworks.