Monitoring for issues is no longer enough — regulators now want to know precisely how and why every compliance decision was reached, and firms are struggling to keep pace.
According to StarCompliance, the demands placed on compliance teams have shifted fundamentally in recent years. Identifying a potential breach or flagging a suspicious trade is just the starting point.
StarCompliance recently explained how the growing burden of explaining compliance outcomes and why it matters.
What follows — validating the outcome, reconstructing decision logic, and producing documentation robust enough to withstand regulatory scrutiny — has become the more time-intensive challenge. For firms operating across multiple jurisdictions with complex rule frameworks, this creates a growing operational burden that automation alone has not resolved.
Research from Thomson Reuters highlights just how acute the problem has become, with compliance teams spending between 30 and 40 per cent of their time on manual reviews and investigations. That figure points to something deeper than inefficiency: it reflects the extent to which compliance still hinges on human interpretation, applied after the fact. Reviewers must validate data inputs, interpret rule outcomes, cross-reference internal policies, and document their reasoning — all in a way that is coherent, accurate, and consistent across cases.
As caseloads grow, so does the pressure. Variability between individual reviewers can introduce inconsistencies into decision-making, and reconstructing the logic behind a ruling days or weeks after it was made increases the likelihood of documentation gaps. Even well-designed control frameworks can become difficult to defend under examination if the rationale underpinning individual decisions is not immediately clear and repeatable. Automation has addressed parts of the workflow, but the point of greatest friction — explaining what happened and why — has largely remained unchanged.
Regulatory expectations have also evolved. Authorities are increasingly focused not just on whether controls exist, but on how those controls operate day to day. Firms must now demonstrate consistency, transparency, and the ability to show their workings in real time, not merely at year-end review.
To address this, StarCompliance has launched StarAssist, an AI-powered tool designed to embed explainability directly into compliance workflows rather than adding it as a separate layer. Rather than requiring teams to piece together decision logic retrospectively, StarAssist delivers clear, contextual explanations of rule outcomes at the moment a decision is made, grounded in the firm’s own data, policies, and controls.
The practical effect is a meaningful change in how compliance operates. By surfacing real-time explanations, StarAssist reduces the ambiguity that can arise when reviewers interpret rule outcomes differently, standardises understanding across teams, and removes the need to backtrack through audit trails to reconstruct what happened. Every decision is supported by a structured, policy-aligned explanation from the outset, improving both consistency and the firm’s ability to defend its controls if questioned internally or by a regulator.
Crucially, the tool operates within defined governance boundaries. StarAssist does not make compliance decisions — it summarises rule outcomes and surfaces the underlying rationale, while decision-making authority remains with the compliance officer. The AI assists; it does not adjudicate.
As compliance frameworks become more sophisticated and expectations around transparency continue to rise, the firms best placed to scale effectively will be those that can not only automate decisions but explain them — clearly, consistently, and immediately. StarAssist represents a step towards embedding that capability as a standard part of the compliance process, rather than something added on after the fact.
Read the full StarCompliance post here.
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