The global commodity trading business is a central part of the modern or digital ability to lay off or take on risk. The unprecedented speed of technological progress and rising pressure on profit margins amidst trade wars, and political uncertainties around the world are making the commodity markets as unpredictable as they were during the global financial crisis.

In 2020, following the domino effect of government-imposed lockdowns during the COVID-19 pandemic, the chances of repeating the industry’s most profitable years are remote.

Additionally, commodity-driven companies are experiencing eroding margins, in the view of increasing price transparency, competitive intensity, and the capital requirements of the business. During such periods of heightened uncertainties, it is paramount for industry operators to be cognizant of flaws in their decision-making, often leading to suboptimal results.

Today, as a consequence of decreasing margins and volatile markets, commodity traders and risk managers have to increase volumes while improving efficiency. Subsequently, it has spurred an increased need for a more sophisticated robust commodity trading and risk management system.

The Rise and Race of Commodity Trading and Risk Management

In the past, the typical commodity trading and risk management system or trading operations would resort to a collection of spreadsheets – an inefficient way to manage scalability. Additionally, these systems were known to be highly expensive, priced out of range for small businesses. With each challenge, the calls have been growing louder for a more efficient risk management system that meets the overall requirements of prospective buyers.

Today, with the emergence of a more digitalized age and greater access to technologies, a wide range of risk management solutions for commodity trading businesses are being introduced. Moreover, a host of potentially disruptive technologies are set to play a significant role in the delivery of commodity trading risk management solutions.


  1. Blockchain – The Panacea for Risks in Commodity Trading

In the commodity trading and risk management space, the interest levels in blockchain are high, as it brings more speed and transparency at lower cost to the process.

While the technology is currently not implemented on a large scale, senior executives in the commodity industry are lining up to invest in blockchain-based platforms. To illustrate, Mercuria, one of the world’s largest energy and commodity traders, set up a $100-million venture fund – Mercuria Technology Ventures (MTV) – targeting investments in blockchain and AI companies.

The blockchain technology’s ability to transparently record complicated transactions and track goods is making it a great fit for the commodity business. Further, the preservation of privacy will become algorithmically guaranteed and the fraud risk will be considerably lowered.


  1. Commodity Trading Risk Management Solutions in the Cloud

An integration between a commodity company’s risk management system and its enterprise resource planning (ERP) system remains essential to better manage the business. With a significant increase of cloud solutions in the enterprise software, a growing number commodity trading risk management system vendors are offering hosted solutions.

In recent years, both blockchain technology and Artificial Intelligence (AI) have attracted a huge attention from large commodity firms. However, the development of fully functional ERP and commodity trading risk management solutions in the cloud is targeted at small- and medium-sized enterprises in the industry.

These hosted solutions are aimed to meet the needs of smaller firms including reduced setup costs. The vendors are further incorporating software-as-a-service (SaaS) in commodity trading risk management, allowing smaller buyers that are trading in spreadsheets to move to an enterprise platform for more efficient operations and better understanding of risk exposure.


  1. Artificial Intelligence – Set Up the Stage for Futuristic Systems

In an increasingly digital workplace, commodity traders have access to a wide and rising number of data sources and large volumes of data of all types. Today, the use of AI and machine learning are becoming a clear solution to maximize the opportunities and minimize the risks presented by real-time trading.

Moreover, significant progress in the areas of these technologies along with mass collection of data has opened up new operational possibilities for commodity trading risk management systems.

With the ability of various AI-based systems to respond together to certain actions to mimic human intelligence, the technology is set to complement human decision-making and create robust and neutral methods that offer multiple benefits to the trader.

Innovations have been forthcoming for machine learning techniques to tackle challenges faced by commodity trading companies, especially price predictions of commodities based on voluminous data sets. This is where AI-powered risk management software can transform business, improving the plan of action to manage price fluctuations and finance risks.


  1. Robotic Process Automation to Streamline Risk Management Operations 

The application of Robotic Process Automation (RPA) in commodity trading and risk management systems is set to reduce the burden of repetitive and simple tasks on employees, thereby allowing human resources to focus on more challenging tasks.

Although the implementation of RPA in the commodity trading risk management system is in a nascent stage, it is becoming apparent that risk management software can lead to significant cost reductions and improvements in organizational effectiveness.

‘Robots’ are at the heart of RPA; they can be introduced to existing software applications to streamline the process that is currently manipulated by human workers. Most significantly, RPA is expected to benefit the companies relying on legal software solutions.

Most of these applications cannot be configured to coordinate with other applications, requiring a user to manually migrate the information. RPA can automate such transfers for firms to gain mastery of their inherent risks and maintain an acceptable level of financial performance.


There is no doubt that the global trading industry is highly sophisticated and on the fundamental change. A wave of stricter regulatory requirements and application of new technologies will be the trigger that drives investment in reliable and flexible commodity trading risk management systems.

As the transition from third party solutions to in-house systems persists among larger firms, systems providers are innovating their offerings to meet specific needs at different budgetary levels.

The growth in technology usage across the industry will continue to develop new market structures. The key for commodity trading businesses is to  recognize the importance of tech-driven risk management software and implement them in a way that aligns with the risk management goals of a commodity-driven company.

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