How can banks ensure consistent decisions in market abuse surveillance across teams and regions?
Structured, policy-aligned evaluation ensures trading behaviour is assessed consistently across desks, instruments, and jurisdictions, producing clear, auditable outcomes.
The Trade Surveillance Agent on Iris 7 autonomously investigates and decides complex alerts against internal surveillance policies and market abuse regulations, analysing behaviour across traders, instruments, and market conditions to deliver consistent, policy-aligned outcomes.
Each alert produces a clear decision – closure, escalation, or referral under defined governance rules – supported by structured reasoning that demonstrates alignment with internal policy and regulatory expectations.
Key Client Challenges
Market abuse surveillance generates large volumes of alerts that require expert interpretation, creating pressure on surveillance teams and investigation workflows.
Financial institutions must routinely:
Investigate high volumes of alerts across desks, products, and trading venues
Rely on senior surveillance analysts for complex investigations
Traditional surveillance systems detect patterns but do not interpret behaviour or make decisions.
As a result, experienced analysts spend significant time manually reviewing alerts, slowing investigations, increasing operational burden, and limiting the scalability of surveillance operations.
Trading Context Assembly
Relevant trading activity is brought together across time, instruments, traders, and market conditions to establish a complete view of the behaviour under review.
Behavioural and Policy Evaluation
Trading patterns are evaluated against internal market abuse policies and regulatory expectations, considering intent, strategy consistency, and contextual market signals.
Structured Decision Output
Each alert results in a clear outcome – closure, escalation, or further investigation – with structured reasoning that explains how the decision aligns with policy and regulatory expectations.
Trading behaviour assessed across instruments and time
Designed to operate within institutional governance frameworks
Expert AI interpretation of trading behaviour, enabling institutions to investigate market abuse alerts faster while maintaining consistent, defensible surveillance decisions.
