RISK MANAGEMENT TRENDS IN COMMODITY MARKETS
Emerging Trends Shaping
Commodity Markets
Commodity markets have grown increasingly attractive to traders in recent years. The high volatility of commodity prices, combined with political uncertainty on the one hand, and new ESG-related regulations and energy transition policies on the other, have brought both innovative products and new players into the market. Additionally, advancements in digitalization and the growing adoption of data-driven trading models are accelerating this trend.
New market entrants, such as tech-focused trading firms, hedge funds, banks, and companies involved in mining and processing, are driving demand for enhanced liquidity and sophisticated risk management solutions.
As McKinsey noted in their paper , the commodity trading value pool has doubled since the pre-pandemic era, rising from $29 billion in 2017 to an estimated $104 billion in 2024. Particularly strong growth has been observed in agriculture and LNG markets, which experienced 30–40% year-over-year growth between 2022 and 2023.
With the increasing value of many commodity markets, competition is expected to intensify. Large trading firms are likely to scale their capabilities in globally traded commodities, while startups with advanced
technological expertise are anticipated to disrupt traditional market structures. Banks with commodity desks and hedge funds which left commodity markets a few years ago are now starting to come back.
Several trends are influencing commodity markets and shaping the risk management needs of market participants:
• Geopolitical Uncertainty and trade restrictions: Commodity trading is significantly affected by evolving restrictions, tariffs, and regulatory measures which are subject to constant change. Rapid adaptation to new tariffs, regulations, or trade restrictions is essential. This includes the capability to simulate potential scenarios, assess their impact, and determine appropriate response measures effectively.
• Geopolitical Uncertainty and short-term markets: The uncertain geopolitical climate is prompting buyers to seek more flexible long-term contracts to better manage demand risks. This, in turn, heightens exposure to global market price fluctuations as companies turn to spot markets to realize short term shortages or surpluses. Efforts to diversify supply chains have also driven a move away from long-term point-to-point contracts in favor of short-term agreements. This leads to growing trading portfolios as the number of short-term deals is significantly higher compared to the past.
• Cross-Commodity Interdependencies: The energy transition is creating new opportunities for
traders by linking traditionally separate markets and leading to rise of correlations between commodities critical for this process. For example, the production of green hydrogen connects industries such as oil, food and agriculture, chemicals, and metals. The growth of LNG markets, in particular, has increased global interconnection and interdependence by linking gas markets. Transition of Europe from Russian natural gas to LNG means strong ramp up for the global LNG market.
Interdependence between commodities are driving traders to explore new markets and diversify their portfolios. However, entering these new markets often necessitates additional software solutions to address the unique characteristics of specific commodities. Many commodities involve complex quality attribute pricing, making it nearly impossible for a single CTRM system to effectively cover all traded commodities. As a result, the industry increasingly adopts an ecosystem of tools, including multiple CTRMs, ERP systems, Price Databases and shipment support solutions, to manage the growing complexity of trading operations efficiently.
• Energy Transition Commodities and products: The energy transition course building renewable production worldwide, which in turn means increased demand for critical raw materials. As companies continue to invest in renewable energy and green hydrogen, the green transition is driving significant demand for raw materials like lithium, rare earth, basic metals, etc.
• ESG-related regulations and new market products: Due to penetration of ESG-related rules and regulations the market for environmental
products is developing fast, bringing new types of products and making the certificate trading more global.
• Global Scale and Financial Strength: With the growing interconnectedness of commodity markets, trading firms are expanding globally. Achieving success in cross-commodity trading requires strong balance sheets to cover margin calls and establish creditworthiness with counterparties.
Players who can effectively leverage correlations between commodities and capitalize on market volatility across a broad spectrum of markets will gain a competitive edge. A cross-commodity presence allows firms to diversify their portfolios and optimize risk/return expectations for their invested capital. This requires both proprietary insights and robust predictive analytics capabilities combined with effective risk control functions.
Modern Risk Management Requirements
Commodity trading firms managing global, multicommodity portfolios face complex risk management challenges. To remain competitive, firms need advanced solutions capable of addressing the following needs:
1. Data Management and Analytics: Companies must handle vast amounts of data from diverse markets. This data must be cleansed, harmonized, analyzed, and visualized in user-friendly formats for traders, controllers, risk managers, back-office users and more. Efficient and high-performance data management is critical. The shift toward shorter-term trading also necessitates intraday
and, in some cases, real-time calculations. Most companies adopt a data-driven approach and require the implementation of data lakes with open, scalable architecture, capable of accommodating all types of data from any source, from structured to unstructured data. Data lakes provide core data consistency across a variety of applications, powering big data analytics and other forms of intelligent actions.
2. Comprehensive Risk Coverage: Modern risk management must account for a wide range of risk tools, including liquidity risk, supply chain disruption, operational risk, market price and counterparty credit risk.
4. Cloud-Native Scalability: Large portfolios can only be processed efficiently in cloud-native environments. Horizontal and vertical scaling ensures the optimal use of computational resources to meet the demands of modern trading.
5. Rapid Adaptation to Evolving Markets and regulations: As markets evolve due to various regulations, restrictions as well as energy transitions, risk management systems must quickly adapt to accommodate new assets, valuation models, and market rules. Traders and analysts often develop proprietary models outside standard systems, so seamless integration of these models is essential. Equally important is the ability to swiftly incorporate new market data sources into risk calculations.
3. Flexibility and Transparency: Risk management systems must offer flexible grouping, drill-down capabilities, and aggregation options, along with customizable dashboards. Transparency is key, requiring systems to provide detailed insights into risk KPIs and calculation inputs. Out-of-the-box reports, such as “Explained” metrics (e.g., PnL Explained, VaR Explained), are now indispensable.
RISK MANAGEMENT SOFTWARE SOLUTIONS
The landscape of risk management solutions is diverse, ranging from basic risk functions embedded in deal management or treasury systems to advanced, specialized risk management platforms. The journey from basic position-keeping to sophisticated risk management capabilities varies from company to company, shaped by its unique history and development path. Nevertheless, some common approaches can be identified.
Commodity companies usually prioritize implementing deal management, operations, and back-office solutions, as well as ERP systems, before focusing more deeply on risk management. CTRM or ERP systems typically provide basic analytical and risk functionalities that are sufficient at the initial stages. Over time, many companies develop in-house solutions to address specific analytical needs.
However, as businesses grow and operate in more markets, managing a patchwork of custom solutions becomes increasingly challenging. This complexity often signals the right moment to consider external risk management solutions.
Companies seeking to enhance their risk management capabilities have three primary options:
1. Rely on the risk functions provided by their CTRM systems.
2. Extend their CTRM systems with custom functionality to address gaps.
3. Integrate external risk management solutions into their software ecosystem.
Let’s explore each approach in detail.
Rely on the risk functions provided by their CTRM systems.
Legacy CTRMs typically offer basic risk functionalities, and their time to market for adaptation to market changes or evolving business processes is slow. Vendors often prioritize deal lifecycle and operational requirements over advanced risk capabilities. Certainly, most advanced CTRMs offer strong risk management functionality. However, these are high-end solutions which are usually very expensive and only affordable for Tier 1 customers only.
Furthermore, legacy CTRMs are rarely cloud-native, making it difficult to scale as portfolios grow. The situation becomes even more complex when a company uses multiple deal management systems for different commodities.
Modern CTRMs, built on contemporary architecture, offer greater flexibility and integration tools, enabling quick inclusion of new markets and assets, supporting
scalable cloud-based calculations, and customizable trading screens. Technically, they provide the sound foundation for implementing advanced risk aggregation capabilities.
However, modern CTRMs often lack the depth and breadth of legacy systems, particularly when it comes to out-of-the-box risk KPIs. Building bespoke functionality on top of these platforms requires significant development expertise, which may be inaccessible for smaller organizations. Maintaining and adapting inhouse solutions to accommodate market and business changes can also become resource-intensive over time.
Specific case of multiple CTRM systems.
As highlighted earlier, the adoption of multiple CTRMs is becoming a prevalent trend in commodity trading. For CTRM systems specific commodity related features and functions such as pricing, quality management, inventory management and logistics play crucial role. In most cases CTRMs cover full functional scope for certain groups of commodities and provide only basic support for other commodities. This drives multicommodity traders to consider multiple CTRM systems for their business. Companies expanding their trading portfolios to include a wider range of commodities, each with unique features and requirements, frequently face the need to add additional trading solutions to their landscape. In some instances, firms deliberately choose best-of-breed solutions for specific business areas to optimize functionality. In other cases, the use of multiple CTRMs arises from mergers or the natural
evolution of business operations. However, managing risk becomes increasingly complex in a multi-CTRM environment. Relying on the native risk features within each system is neither practical nor effective. To ensure comprehensive and accurate risk management on the overall portfolio level, implementing an external risk aggregation solution becomes essential, reliance on the native CTRM’s capabilities is practically impossible.
Extend their CTRM systems with custom functionality to address gaps.
Despite these challenges, many risk managers still view building some bespoke functionality on top of CTRM as an advantageous approach because:
1. Analytics remains fully under control, avoiding reliance on “black box” solutions.
2. The number of interfaces is minimized, as basic risk aggregation is handled within the standard CTRM system.
However, in practice these solutions are relatively expensive due to continuous maintenance costs, the need to implement required changes, necessity to keep corresponding skills in the business, in-house hosting and more.
Integrate external risk management solutions into their software ecosystem.
External risk management solutions address many of the limitations of CTRMs and in-house systems, offering
several key advantages:
1. Focus on Risk Functionality: Specialized risk management software prioritizes risk-related capabilities, making it the ideal choice for companies following a best-of-breed ecosystem approach. These platforms provide flexible dashboards, a comprehensive range of risk KPIs, advanced drilldown and aggregation functionalities, and enhanced visualization and reporting tools—designed to meet the exact needs of risk managers.
2. Transparency and Explainability: Transparency in calculations and explainability of results are critical features of external solutions, ensuring users can trust and understand the outputs.
3. Risk aggregation: In a multi-CTRM setup for deal management, external risk systems play a crucial role as aggregators. Each CTRM may supply different types of deal data and price information, reflecting the specific characteristics of the commodities it manages. An external risk system bridges these gaps by collecting, processing, and enriching data from multiple CTRMs. This centralized approach enables the calculation of portfolio level risk KPIsas well as a unified view of overall risk exposure across the entire trading portfolio.
4. Streamlined Integration: External risk solutions typically offer standardized interfaces, simplifying integration with existing systems. Many solutions include out-of-the-box support for standard market interfaces, reducing the time and cost of implementation.
5. Adaptability to Market Changes: External systems are often more responsive to market changes, quickly introducing valuation models for new asset types and adapting to evolving regulatory requirements.
Despite their advantages, external risk solutions often raise concerns about additional costs, the need for new interfaces, and the perception of a “black box” approach.
However, for companies that prioritize robust, scalable, and transparent risk management capabilities, the benefits of external solutions often outweigh these concerns. By focusing on their core strengths, external risk systems enable firms to navigate the complexities of modern markets with confidence and precision.
RADARRADAR’S APPROACH TO ADDRESS THE CHALLENGES OF AN EXTERNAL RISK SYSTEM
RadarRadar provides advanced risk- & margin management capabilities tailored for multi assets, multicommodity traders and processors, offering a wide range of risk-related KPIs. But how does RadarRadar address customers’ concerns and convince them to adopt an external risk system?
One common concern is about data management and system integration. For RadarRadar, ensuring a robust and trustworthy data foundation is paramount. Multicommodity risk systems require diverse data types from a variety of sources, often located in different systems and formats. RadarRadar’s solution focuses on its ability to seamlessly integrate these data sources - whether from Excel, CTRMs, ERP systems, or other platforms - and manage them effectively.
Data management provided by RaderRadar is a key differentiator in the market. Incoming data can be loaded manually or automatically, with the system performing rigorous validation, harmonization, normalization and outlier detection to ensure accuracy.
One of the most labor-intensive tasks in data management is mapping data points to hierarchical master datasets, including products, markets, counterparties, and more. RadarRadar leverages AI to simplify and accelerate this process, providing intelligent suggestions for master data mapping. Customizable business logic can also be applied at any stage of the data pipeline, ensuring flexibility to meet the unique needs of each user.
RadarRadar’s solution harmonizes data by unifying fields, filling gaps, and then normalizing the data by transition to units of measure (UoM) and currencies. This creates a clean, consistent dataset that’s ready for business logic applications, aggregation, and advanced analytics on risk and margin. The solution includes full data historization for both incoming data and calculated data.
Data security is a top priority for data management. All data is safeguarded by the platform’s built-in security systems as well as advanced cloud-based security tools. By establishing trust in the underlying data, RadarRadar ensures the reliability of all subsequent analytics and reporting processes.
RadarRadar also addresses concerns about the time and complexity of setting up interfaces. According to Norbert Verhagen, Managing Director & CTO at RadarRadar, the company can configure all necessary interfaces for a project within just a few weeks. The ability to integrate any data source with any data format in a timely manner is the key feature of the solution. Standard connections to major market data providers, such as Reuters, Bloomberg and SAP as well as key
derivative brokers such as Marex, StoneX, JPMorgan or RJO’brien come pre-configured, significantly simplifying the onboarding process.
Transparency of calculations is another common concern among risk managers. RadarRadar’s solution handles this area by offering comprehensive drill-down capabilities. Users can analyze any risk KPI down to the sub-deal level, ensuring complete clarity and confidence in the results.
Additionally, the platform includes detailed reports that explain changes in KPIs between calculation cycles.
Features like PnL Explained and VaR Explained empower risk managers to identify the key drivers of portfolio risks, facilitating more informed decisionmaking.
Finally, RadarRadar’s flexible licensing model addresses concerns about costs. Pricing is tailored not only to the number of users but also to the complexity of the solution required. This approach ensures affordability for smaller, less complex organizations while remaining scalable for large, sophisticated multicommodity traders.
RADARRADAR’S SCALABLE AND DATA-DRIVEN RISK MANAGEMENT
The solution is built on a modern, cloud-native architecture, enabling seamless scalability of calculations. Even as customers’ portfolios grow significantly, the system maintains optimal performance. According to RaderRadar, enterprise clients can import easily millions of new records daily. All historical data—both imported and calculated—remains accessible in the live system without any degradation in performance.
Risk aggregation capabilities
RadarRadar is designed to address the challenges of risk aggregation for companies operating with a diverse software ecosystem. In environments where multiple components, such as ERP systems and various CTRMs, differ significantly in technology, data models, and interfacing requirements, aggregation is an essential
requirement and a challenge. With flexible interfacing and robust data management capabilities, RadarRadar integrates data from various sources, processes it into standardized datasets, and calculates enterprise-level risk indicators. This enables organizations to achieve a consolidated and consistent view of their overall risk exposure.
Flexible Dashboards and Intuitive Reporting
Configurable dashboards have become a critical requirement for any risk management application, and RadarRadar delivers full flexibility in this area. Users can easily create custom reports and dashboards, with the ability to drill down into sub-deal level results intuitively. The platform supports both graphical and tabular data presentations, ensuring information is accessible and actionable. Additionally, integrating RadarRadar with third party BI platforms such as PowerBI is possible with relative ease.
Advanced and Adaptive Calculation Capabilities
From a calculation perspective, the system adapts to whatever data is available. If customers provide PnL at the deal level along with required market data—such as volatilities, correlations, or Monte Carlo scenarios—the system processes this information to produce final risk indicators. Conversely, when only raw prices and deal data are supplied, RadarRadar generates all derived values, including volatility surfaces, correlations, and PnL, before calculating the risk KPIs.
RadarRadar does not aim to offer complex valuation models for exotic deal types but focuses on delivering robust, reliable, and transparent risk metrics for portfolios of any size. Customers needing exotic valuation models can easily integrate their custom solutions into RadarRadar’s calculations, ensuring flexibility without compromising core functionality.
The solution offers not only the possibility of a deep understanding of the risks in a portfolio but also effective risk controls and limit system performance under complex market conditions. Notifications in case of certain events can be configured.
The Data Analytics Hub (DAH)
RadarRadar also offers a Data Analytics Hub, enabling customers to leverage the vast dataset managed and stored by the system. This includes physical & financial purchases & sales, stocks, counterparty-, market-, and product-related data, as well as calculated financial and risk results. Customers can utilize this comprehensive dataset to train AI models, create forecasts, or support other advanced analytics. The system allows seamless replication of data into external repositories, while customers can connect directly to the DAH using its own preferred BI tools.
Market Trends Driving the Need for Enhanced Risk Management
As stated in the beginning of the paper, the growing interdependencies between commodities and the rising demand for materials critical to energy transition technologies are reshaping commodity trading markets.
Geopolitical uncertainty and steadily changing regulations are forcing companies to pay more attention to risk management.
These trends encourage traders & processors to expand their portfolios and acquire specific solutions
for specific commodities. They need risk aggregation tools to esses risks on corporate and on sub-portfolio level.
Additionally, the influx of new market entrants and the increasing focus on financial stability of counterparties underscore the need for deeper insights into
counterparty risk and margin management.
These developments are driving demand for professional risk management tools, positioning RadarRadar as a key player poised to meet the evolving needs of the market.
ABOUT RadarRadar
RadarRadar is an industry expert in the commodity trade, production, and processing business, operating in the most fundamental industries of the world: food, energy, metals, and other commodities. Since 2010, we have delivered high-profile projects for the world’s leading commodity producers, traders, and processors.
We work with clients to configure bespoke and
extendable data solutions that enable successful digital transformation across critical functions such as risk management, margin processing, and regulatory compliance.
https://radarradar.com/demo
ABOUT
Commodity Technology Advisory LLC
Commodity Technology Advisory (ComTech Advisory) is the leading analyst organization covering the Energy and Commodity Trading and Risk Management (E/CTRM) and Energy Transition technology markets. Led by Dr. Gary M. Vasey, along with affiliate analysts Dr. Irina Reitgruber and Kevin Mossop, ComTech Advisory provides invaluable insights, backed by primary research and decades of experience, into the issues and trends affecting both the users and providers of the applications and services that are crucial for success in markets constantly roiled by globalization, regulation and innovation.
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