When the Russia-Ukraine war broke out in 2022, wheat prices went up by 50% in a matter of weeks. Agricultural businesses that had been using spreadsheets for position management suddenly found themselves unable to get an accurate picture of their exposure quickly enough to act. By the time the reports were ready, the market had already moved.
What caught many agricultural businesses off guard wasn't so much the price spike itself but how long it took to understand what it meant for them. When exposure sits across a handful of spreadsheets and disconnected systems, building a reliable view takes time the market doesn't give you.
With that in mind, we've created this guide to look at the operational realities of agricultural trading and how modern CTRM systems support it.
Agriculture is one of the most complex commodity markets to trade, with prices moving due to weather forecasts and disruption across shipping. A single trade can involve multiple counterparties, while quality specifications change at delivery as settlement terms move with floating price benchmarks.
Most businesses that have been operating for any length of time have accumulated a patchwork of tools, often a trade capture system alongside an ERP for finance. The spreadsheets bridge the gaps between them.
The problem isn't any individual system per se as much as it is that none of them talk to each other in real time. Positions are manually reconciled, which means the same data has to be pulled together repeatedly before anyone can trust it.
Beyond that, inventory figures are hours or days out of date, and risk exposure has to be calculated rather than read. When a market event occurs, the first hour is spent trying to establish the current position.
Before working with Quoreka, one grain cooperative had a reconciliation process that required 82 manual steps and 11 spreadsheets and consumed 20 working days every month. It’s an operational problem created by disconnected systems rather than a limitation in the technology.
A modern CTRM platform is a different operating model altogether.
Trade capture happens at the point of agreement, which means position data is aligned with market activity as it happens. Every contract update is logged through to settlement, with a full audit trail throughout. Settlement itself is automated, and regulatory reporting, which happens across frameworks including EMIR, CFTC, and MiFID, is built into the workflow.
The risk management layer is where the difference is most noticeable, as traders and risk managers can view portfolio value at any point in the trade lifecycle. User-defined alerts flag when limits are approaching breach, and credit exposure moves in step with trading activity as opposed to lagging behind it. Having a real-time view across both books is what makes a hedging strategy executable if you’re an agricultural business running physical and derivatives positions simultaneously.
Quoreka pulls in external data feeds automatically (think weather forecasts; market price data via providers like Refinitiv, ICE, and S&P Platts; and logistics updates) and brings them into the same environment where trading decisions are being made. While it sounds straightforward, in practice, it removes the manual data collection step where accuracy most commonly breaks down.
Agricultural businesses consistently identify the same operational pressure points. Here's what a modern CTRM platform does about each of them.
Commodity prices in agricultural markets are always on the move, often reacting to policy decisions and broader economic shocks that can be difficult to anticipate. Hedging with derivatives mitigates exposure, but it doesn't eliminate it entirely. The effectiveness of any hedging strategy depends on how well you understand current exposure.
Previously, risk managers would need to reconstruct what happened the previous day. But with real-time position visibility across physical and financial trades, they can see where they stand and respond to market movements in real time.
Grain may move through several storage points before reaching a buyer, and shipments are often in transit across different routes at the same time. It’s fair to say that agricultural logistics rarely follow a simple path.
Quoreka brings it all together and keeps track of inventory across storage locations, contracted volumes and goods already moving through the network. And when there is disruption, you can model the likely impact and decide how to respond based on the full position rather than partial information.
Manual data entry across disconnected systems slows everything down and increases the likelihood of errors. Automating settlement and compliance reporting removes much of that friction, so you only need to focus on decisions that require judgement.
Accurate, timely market data is a trading edge. A modern CTRM platform pulls in external data feeds and makes them available straight away, meaning you’re working with current information rather than waiting for reports to catch up. Traders can then model how changing conditions affect their positions and decide how to respond while the market is still moving.
Compliance in agricultural commodity trading spans multiple jurisdictions and reporting frameworks. Modern CTRM systems connect directly to trade repositories and handle transaction submission automatically, with reporting status visible in real time. Alerts flag acknowledgements or rejections as they happen, so issues can be dealt with before they turn into violations.
CBH Group, Australia's largest grain cooperative, spent 18 months evaluating CTRM vendors before selecting Quoreka. What they needed was a single platform uniting their teams across Australia, Japan and China, with a consistent real-time view of their entire operation. After implementation, 1,000 employees had web-based access to live data across all three geographies.
A separate agricultural trading business launching European operations chose Quoreka and went live in 16 weeks, ready to process one billion transactions when the harvest season began. Missing that window would have meant losing out on an entire harvest. The implementation timeline was the deciding factor.
Both implementations reflect what modern CTRM makes possible when scoped and executed the right way. Quoreka's standard implementation timeline runs 12 to 16 weeks, against an industry norm that typically stretches to six months or longer.
The operational case for moving away from legacy systems and spreadsheets has been clear for some time. What's changed is the cost of not moving. Markets are more volatile, and the pressure on supply chains and reporting requirements continues to build up. A modern CTRM platform doesn't remove the difficulty of agricultural trading, but it does help with the operational friction that gets in the way of managing it.
If you'd like to see how Quoreka's platform works in practice, speak to one of our experts.