As firms prepare for their third annual Consumer Duty Board report, expectations are shifting from demonstrating governance and management information (MI) to evidencing effectiveness and measurable improvements in customer outcomes.
Senior leaders and Boards need confidence that what they are signing off is grounded in defensible evidence across products, channels and customer cohorts.
For many firms, the challenge is not intent – it is scale and traceability. For instance, how should customer interactions be monitored consistently, emerging risks detected early, whilst maintaining an audit-ready trail from insight to action? This is where AI-enabled monitoring and quality assurance (QA) can strengthen the evidence base for Board reporting.
Read our five priorities to refine for your year three report, with practical considerations for how technology can support them.
1. Explain what the data says about outcomes – not just what it tracks
Board reports often contain large volumes of Consumer Duty MI but some may stop short of answering the Board’s core questions: what does the data indicate for customer outcomes, where are outcomes weakening and what is being done as a result?
Purpose-built (predictive) AI tools can help convert tracking into insight by analysing customer interactions at scale (including recorded customer calls, face-to-face meetings and emails) to identify recurring drivers of friction, misunderstanding, delays and repeat contact. This provides stronger triangulation behind MI and supports a clearer Board-level narrative on what is happening, why it matters, and which interventions are expected to improve outcomes.
2. Make Board challenge visible, specific and outcome-focused
In year three, it is increasingly important to evidence not only that the Board reviewed the Consumer Duty report, but that the challenge was targeted, informed and led to change. Generic statements about oversight are unlikely to reassure in an outcomes-focused supervisory environment.
AI-enabled QA and monitoring that uses predictive AI analytics can support this by creating structured, comparable evidence of what was reviewed, what issues were found, how they were prioritised and whether remediation was effective. When this evidence is surfaced clearly, Boards can challenge with precision and the report can demonstrate traceable follow-up from challenge to improved outcomes.
3. Strengthen oversight of outcomes delivered through third parties
Where distribution chains, appointed representatives (ARs), outsourcers or technology suppliers influence the customer experience, Boards need a realistic view of where visibility is strong, where it is weak, and what the firm is doing to close gaps. It is not enough to acknowledge reliance on third parties. The report should demonstrate how the firm monitors and acts on outcome-related signals.
Technology can support scalable oversight by applying consistent monitoring and quality checks across interactions, highlighting exceptions and emerging trends. This helps firms evidence adherence to standards, identify where harm may be introduced in the distribution chain and demonstrate that oversight is active.
4. Deepen analysis of consumer understanding and support across the journey
High-level indicators (such as satisfaction, complaints and persistency) can be useful, but they rarely explain whether customers are genuinely understanding key information and getting the support they need – especially at moments of change, stress or vulnerability.
Using predictive AI analytics tools, firms can add depth by analysing interaction content and journey signals to identify themes such as confusion, misaligned expectations, disclosure gaps, repeat explanations, and delays in getting help. Used well, this supports stronger testing and monitoring. In turn, this means the Board report can evidence where communications and support are working, where they are not and what changes are being made to improve outcomes for different customer groups.
5. Show how Consumer Duty insight is shaping decisions (and improving outcomes
The most credible Board reports demonstrate a clear chain. For example, monitoring to identify risks or weak outcomes > management intervenes > the firm can evidence whether outcomes improved. Reports that describe frameworks without showing the impact of decisions will struggle to meet rising regulatory expectations.
Purpose-built AI models for monitoring and QA can strengthen this insight-to-action chain by detecting issues earlier, quantifying their scale, and supporting consistent post-remediation testing. That makes it easier to evidence to the Board not just what the firm decided, but why, and most importantly, what changed for customers afterwards.
Build audit-ready evidence base for year three
As Consumer Duty supervision becomes more outcomes-focused, Boards will benefit from reporting that is concise, evidence-led and clear on impact. Refining the five priorities above can help firms move beyond describing activity to demonstrating effectiveness.
Recordsure provides proprietary AI technology to help financial services firms monitor interactions at scale, strengthen QA and provide a robust audit trail to evidence actions and outcomes. This can lead to supporting stronger governance and more confident Board reporting.
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