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Blockchain and data processing use grows in commodity trading

In commodity trading, the use of blockchain and data processing is growing, according to a report from the United Nations Conference on Trade and Development (UNCTAD).

Commodity trading “has traditionally relied on vast paper records to execute, authenticate and process every transaction.”

The industry has lagged behind other sectors in the use of digital solutions, but is catching up on digitization and adoption of new technologies.

Frontier technologies can be used to optimize the efficiency and transparency of transactions. In particular, Blockchain technology can serve as a natural fit solution for business applications.

For example, in a hypothetical scenario of trade in soybeans from the United States to China, the estimated savings through the use of blockchain technology were 2.3 cents per bushel of soybeans and a 41% reduction in the total time required, even for the documentation and transit, which is important for agribusiness and other agricultural stakeholders evaluating the benefits of adopting such technology in international commodity trade.

Commodity trading

In addition, UNCTAD explained that smart contracts that use blockchain technology, which are automatically executed when predefined conditions are met, can be used to automate commercial agreements, since their use allows commercial functions that involve the transfer of information and value that provide clues. of transparent and auditable information in a reliable way.

Commodity trading faces significant price volatility from speculators who buy assets for a short period in the expectation of profiting from price fluctuations and may never produce the commodity.

On this, the Commodity Futures Trading Commission of the United States affirms that automated trading increased in 2013-2018 and, in 2018, constituted more than 70% of the futures markets of energy products, metals, cereals and seeds oilseeds.

Artificial intelligence, particularly machine learning algorithms, can be used to associate trading patterns with fundamentals and price movements, to help reduce noise, improve decision-making, optimize hedging programs to improve reduction risk management and portfolio optimization and improve efficiencies across the commodity industry.

 

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