AI agents, software that can plan and carry out multi-step tasks rather than simply answer questions, are arriving in trading operations. Vendors are adding agent capabilities to ETRM and CTRM platforms, and new tools sit alongside them. The opportunity in middle and back office is real. So is the risk of automating the wrong things without the right controls.
A simple way to decide: consequence and reversibility
A useful rule of thumb is to judge each task by two questions. What happens if the agent gets it wrong? And how easily can a mistake be detected and reversed? Tasks with low consequence and easy reversal are good candidates for automation now. Tasks that move money, change limits or create legal commitments should keep a human firmly in control.
What can be automated safely today
Document intake and data extraction
Reading confirmations, broker statements, invoices and emails, extracting the relevant data and proposing CTRM entries for human approval is one of the most mature uses. The agent prepares; a person approves.
Matching and reconciliation
Matching confirmations to deals, invoices to settlements and shipments to contracts, then flagging breaks for review, saves significant time and lets operations staff focus on genuine exceptions.
Data quality monitoring
Agents can continuously check reference data, missing fields, stale prices and inconsistent records, and raise issues before they affect reports or settlements.
Report preparation and commentary
Assembling daily position, P&L and risk reports, and drafting first-cut commentary on what changed, gives analysts a head start. Review remains essential.
Chasing and coordination
Following up missing confirmations, documents or approvals, and keeping track of outstanding items, is well suited to agents operating within clear rules.
What should wait, or stay human-led
- Autonomous trade booking without approval
- Payments and settlement release
- Changes to credit or risk limits
- Contract amendments or legal commitments
- Regulatory submissions without review
These may become candidates over time, but only with mature controls, proven accuracy and clear accountability.
The controls you need
- Least-privilege permissions: agents get only the access they need, separate from human user rights.
- Human approval points: defined steps where a person must review before anything is committed.
- Full audit trails: every agent action and its inputs recorded and reviewable.
- Explainability: agents should show why they proposed something, not just what.
- Monitoring and thresholds: track accuracy, and route low-confidence cases to people automatically.
- Vendor and model risk management: understand where models run, what data they see and how they are updated.
European regulators have highlighted explainability, human oversight and third-party reliance as key AI risks in financial markets, so these controls are good practice and likely to be expected.
Start with a pilot
Pick one or two well-defined, high-volume processes, measure today's effort and error rate, run the agent alongside existing processes and compare. Scale only when the results and controls are proven.
For a wider view of how AI is changing trading platforms, read our article Is Your ETRM or CTRM Holding You Back? Orivyn helps firms identify the right use cases, assess their platforms and implement AI safely as part of implementation and integration programmes.
