Energy and commodity trading firms manage some of the most complex data landscapes in business. Trades move across exchanges, brokers, and internal desks at high volumes and speed. Risk managers need up-to-the-minute positions. Compliance teams need structured data for regulators. Operations teams need reconciled books with minimal errors.
The problem is that most firms run a mix of SaaS platforms and legacy ETRM or CTRM systems. Without strong data orchestration, these systems do not align. Information gets delayed, duplicated, or lost. That adds risk and costs time.
Data orchestration solves this by connecting systems and automating workflows so data flows where it is needed. The challenge is that SaaS and legacy environments require different integration strategies.
SaaS data orchestration in trading
SaaS applications are now standard across trading operations. Risk analytics, market surveillance, and reporting platforms are often cloud-based. They are easier to scale than on-premises systems, but integration has limits.
Most SaaS providers restrict API calls. For example, Salesforce and similar platforms limit how many requests can be made per day. For trading firms handling thousands of trades, hitting those limits is common. If not managed, costs increase or processes slow down.
Automation is the solution. With bulk uploads, streaming pipelines, and real-time orchestration, firms can move data without breaking API thresholds. In trading, this means:
- Risk teams get live position updates instead of stale end-of-day reports.
- Surveillance teams receive alerts in real time, not hours later.
- Compliance teams have the data they need to prepare reports before deadlines.
Manual uploads and ad hoc fixes are not sustainable. Automated orchestration makes data timely, accurate, and consistent across SaaS applications.
Legacy ETRM and CTRM data orchestration
Legacy systems are still at the core of many energy and commodity trading operations with ETRM and CTRM platforms often running trade capture, settlement, and back-office processes. The challenge is that many of these systems were not built for modern integration.
Legacy systems often bring several integration challenges. Many have outdated or missing APIs, making it difficult to connect them with newer systems. Data is often exported in batch files, which delays updates and prevents real-time visibility. In many cases, firms also depend on custom coding to bridge gaps, but these solutions are fragile and require ongoing maintenance.
These limitations slow down analytics and increase risk. Replacing a CTRM outright is rarely realistic, given the cost and operational disruption. The more practical option is to strengthen orchestration so legacy data flows into modern workflows.
Trade surveillance integration
Trade surveillance is a top priority for energy and commodity firms, especially as regulators increase scrutiny of market activity. Effective surveillance requires pulling data from multiple venues, including exchanges, brokers, and internal trading systems.
Data orchestration supports trade surveillance by automating the flow of trades into monitoring platforms, normalizing data from different sources, and reducing latency so alerts trigger in real time. It also ensures a complete audit trail is maintained for regulators, improving transparency and compliance. Without orchestration, surveillance teams spend too much time reconciling feeds or chasing down missing trades. This slows down investigations and creates compliance risk.
Regulatory reporting workflows
Energy and commodity markets face strict reporting requirements under regimes such as EMIR, REMIT, and Dodd-Frank. Each regulation requires specific formats, fields, and delivery schedules.
Regulatory reporting is made more efficient through data orchestration, which gathers trade data from both SaaS platforms and legacy ETRM systems, standardizes it into the required formats, automates submissions to regulators or trade repositories, and maintains an audit trail for compliance checks. Manual processes leave too much room for error. Automated orchestration reduces risk and ensures firms can meet deadlines without last-minute scrambles.
Hybrid environments: SaaS and legacy
Most firms now operate hybrid environments where SaaS platforms and legacy systems work side by side. For example, a CTRM may handle trade capture while a SaaS platform manages regulatory reporting. A cloud-based surveillance system can monitor trades from both exchanges and on-premises databases. Risk teams may rely on SaaS analytics, but still need position data coming from a legacy CTRM.
Data orchestration is the bridge that makes these setups work. Automated workflows ensure information is consistent across all tools, regardless of where it originates.
Key takeaways for energy and commodity trading
- ETRM and CTRM orchestration is critical to modernize legacy trade capture and settlement systems without costly replacements.
- SaaS orchestration requires automation to manage API costs and deliver real-time updates.
- Surveillance integration depends on timely, accurate, and complete trade data across venues.
- Regulatory reporting workflows need standardized, automated processes to reduce errors and meet strict deadlines.
- Hybrid orchestration is the reality for most firms and requires tools that can connect both SaaS and legacy environments.
- Low-code and no-code orchestration helps reduce reliance on fragile custom code and keeps IT backlogs manageable.
Connecting SaaS and Legacy Platforms
BroadPeak helps energy and commodity trading firms connect SaaS platforms and legacy systems through low-code data connectors. Our solutions automate trade data flows, support surveillance and regulatory reporting, and reduce reliance on custom coding. A low-code ETL (extract, transform, load) interface turns raw data into a structured, actionable resource, delivering reliable data across the enterprise and allowing teams to focus on analysis rather than manual work.
