A great session around the use of behavioural science and how this can be leveraging to engage customers. This session discussed the frameworks and instructure needed to implement effectively in the Collections process with Mark Brown from Symend.
This session explored how to apply behavioural science to enhance digital debt collection strategies.
It examined the limitations of traditional risk segmentation and introduced a predictive archetyping model based on customers’ capacity to pay and readiness to act.
Key Take Aways
- Digital communication volume has significantly increased, creating customer overwhelm and message fatigue.
- Consumers face an estimated 35,000 decisions per day, reinforcing the need for behaviourally optimised communications.
- Behavioural personas and archetypes can complement traditional risk models to enhance segmentation and customer engagement.
- Any platform needs to identify changes in consumer behaviour over time, adapting messaging accordingly.
- The solution should use a blend of first-party data, behavioural interaction data, and engagement metrics to build predictive models.
- It is important to continuously test and iterate messaging to avoid “message decay” and maintain engagement.
- Real-time customer interactions enable journey personalisation and optimisation based on behavioural archetypes.
- Some organisations can eliminate outbound dialling entirely while improving customer outcomes and reducing operational costs.
Innovation
- Combining behavioural science with real-time data analytics can optimise personalised debt collection journeys at scale.
- Introduce predictive archetyping based on capacity to pay and readiness to act, allowing dynamic journey design.
- Use of behavioural engagement scoring (e.g., likelihood to recover, likelihood to respond) to inform message strategies.
- Dynamic content adapts based on behavioural feedback loops, enabling real-time learning and message iteration.
- Prioritise empathy, cognitive bias alignment, and channel suitability in message delivery.
Key Statistics
- Customers make approximately 35,000 decisions daily.
- One financial services client reduced operational expenses by 35–45% by eliminating outbound dialling.
- Achieve between 6x and 12x ROI
Key Discussion Points
- Delinquent customers often do not behave rationally; communications must be empathetic and behaviourally informed.
- Traditional risk segmentation is valuable but incomplete without behavioural overlays.
- Archetypes are designed on a two-axis model: capacity to pay and readiness to act.
- Different archetypes receive different messaging cadences, channels, and behavioural nudges.
- Behavioural insights (e.g., empathy, anchoring, future insight) are embedded within message content.
- The platform continually adapts based on real-time engagement to optimise outcomes.
- Message “decay” is proactively addressed by updating content when it loses efficacy.
- Governance and compliance are built-in, with all clients hosted in single-tenant architectures.
- Data privacy is ensured through full SOC 2 and GDPR compliance.
- Consumer Duty and vulnerability considerations are increasingly integrated into digital collections strategies.
- Behavioural archetyping allows early identification of potential re-entry into delinquency.
- A gradual reducing reliance on blanket messaging, adopting segment-of-one strategies.
See also Behavioural Science in Collections
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