Another great think tank for 2025 with Credit Connect. I always enjoy this event as a way to sum up the year and start to kick off thinking about 2026. Interestingly there was definitely a heavy regulatory and data theme this year… there has been a lot of activity in this space. I suspect the focus on data, and the backend engineering work to collate and organise data, is going to be a big focus for next year. (it helps with AI too!)
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Some notes from the session below. (full detailed session notes for subscribers here)
Key Take Aways
- Regulatory pressure and the volume of change remain the most significant challenges for firms, especially smaller lenders facing existential threats from cumulative requirements such as PSD, subscription contracts, and affordability assessments.
- Customer financial stress is deepening among those already struggling; while overall delinquency volumes remain stable, the “struggling cohort” is worsening, with distribution payments from DMPs nearly halved.
- Customer behaviour under stress leads to avoidance, short-term decision making and reduced engagement, requiring tailored communication strategies grounded in behavioural insight.
- Digital engagement continues to rise, but telephone contact remains crucial for identifying vulnerability, understanding context, and gathering complex information that is not readily available through digital channels.
- Omnichannel strategies are essential, allowing customers to move fluidly between digital, email, app, SMS, WhatsApp and telephony depending on life events and emotional state.
- Firms report rising DSAR volumes and increased scrutiny of data transparency, with expectations that future AI-driven finance apps may generate thousands of automated DSARs.
- AI adoption is accelerating, but expectations frequently exceed practical value; firms emphasise starting small, ensuring data quality, and avoiding perceiving AI as a “magic blanket”.
- Sector-specific AI language models are emerging to interpret collections vocabulary, vulnerability cues and customer intent while maintaining data privacy by running models locally.
- Behavioural analytics and journey mapping are increasingly used to segment customers, identify mindsets and tailor communication based on tone, timing and channel preference.
- Customer expectations of immediacy created by instant messaging channels mean firms must manage response times carefully to avoid creating friction.
- Fraud risk is rising as fraudsters exploit advanced technology faster than regulated firms can adapt, increasing the urgency for robust data governance and transparency.
- Industry perceptions remain mixed; improved data, education, transparency and oversight (e.g., Enforcement Conduct Board) are expected to support more accurate external views of the sector.
Innovation
- Adoption of industry-specific AI language models combining multiple small and large models run locally to maintain data control.
- Use of predictive analysis to determine best contact time, channel, and customer receptiveness at various points in the collections life cycle.
- Application of behavioural insights, including customer mindset mapping, stress-driven bias identification, and data-informed persona development.
- Increasing focus on radical transparency and easy-access customer data portals enabling self-service DSAR retrievals.
- Expected emergence of AI-driven personal finance agents acting independently on behalf of consumers, contacting creditors and generating high DSAR volumes.
Key Statistics
- 2,000+ DSARs received in a single day by one firm.
- 80–90% reduction in lending volumes seen in some markets due to tightened affordability expectations.
- Distribution payments from DMPs almost halved year-on-year.
- 40% of customers in one portfolio have at least one current vulnerability, with an average of three.
Key Discussion Points
- The cumulative burden of regulatory change, including consumer duty, product sales data and affordability demands.
- Ambiguity and retrospective interpretation of regulation creating risk and repeated rework for firms.
- Customer financial stress and the widening divide between those managing vs. those deteriorating.
- Importance of treating communications as customer-experience assets, including simplicity, reading-age reduction and tone of voice.
- Increasing need for omnichannel capability and flexibility as preferences shift throughout the customer life cycle.
- The role of behavioural science in designing journeys, interventions and trigger-based communications.
- Challenges for smaller firms lacking the resources to meet regulatory and technological expectations.
- Data transparency pressures, DSAR surges and the need for robust governance infrastructure.
- Emerging risk that customer-side AI automation will transform engagement patterns and volumes.
- The growing importance of identifying vulnerability through speech analytics, face-to-face insights and AI-driven intent detection.
- Fraud risks escalating as criminals exploit AI at pace.
- Anticipated increases in claims, redress activity and cross-sector data access as historic data becomes newly accessible.
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