A great day in Manchester talking about affordability, assessment of ablity to pay and income maximisation in the UK. Some common themes; troubling changes around worsening affordability, the building of trust across the credit lifecycle and some ideas to really help.
Some notes from the session to follow below, plus the music video supporting the event.
w/ thanks to Paylink, Arum Global, Mega.AI, IE Hub, Hope Macy, Inicio.AI, Policy in Practice, Welfare Together and Finvence for sponsoring the event.
The Affordabilty Summit – UK 2026 focused on the evolving landscape of affordability, financial vulnerability, and income maximisation within financial services, utilities and adjacent sectors.
With panel discussions, practitioner insights, and technology demonstrations, the session explored how organisations can better assess affordability, support customers in financial difficulty, and leverage data and AI to drive improved outcomes.
The discussion highlighted the need for earlier intervention, more integrated data approaches, and a balance between automation and human support, all within an increasingly outcome-driven regulatory environment.
Find the event page and agenda here
Key Take Aways
- Affordability should be reframed as a holistic construct, integrating income maximisation, expenditure management, and customer context rather than relying on static budgeting approaches.
- Early engagement at the first missed payment is critical to improving both customer outcomes and recovery performance.
- There is a persistent “last mile” gap between identifying benefit eligibility and successfully converting that into realised income for customers.
- Digital solutions alone are insufficient; human-led support remains essential for vulnerable and digitally excluded segments.
- Regulatory expectations are shifting toward outcome-based frameworks, requiring firms to demonstrate real customer impact rather than process compliance.
- A 360-degree customer view—combining affordability, creditworthiness, and vulnerability—is becoming the industry standard.
- Significant value remains untapped in income maximisation, with many customers eligible for support they do not claim.
- AI and automation are transforming affordability assessment but require strong governance, transparency, and safeguards.
- Firms must transition from reactive collections to proactive intervention models, using data to identify distress earlier.
- Affordability assessments today are often inconsistent, manual, and prone to poor-quality data, limiting their effectiveness.
- Technology adoption success depends less on the tool itself and more on implementation discipline, integration, and operational ownership.
- The industry is converging toward integrated ecosystems, where data sharing, partnerships, and cross-sector collaboration improve outcomes for customers.
Innovation
- AI-driven conversational affordability agents that guide customers through financial disclosures in a more natural and engaging way
- Integration of open banking, benefits data, and household-level insights to enhance accuracy and completeness of affordability assessments
- Development of “last mile” support services to ensure customers successfully access entitled benefits
- Use of real-time dashboards and data feeds to identify households missing support and enable proactive outreach
- Predictive analytics and early-warning systems to identify financial distress before default occurs
- Personalised affordability modelling based on dynamic household circumstances rather than static snapshots
- Affordability data portability across creditors to reduce duplication and improve customer experience
- AI-enabled compliance and underwriting assistants embedding policy and regulatory rules into decisioning
- Behavioural data modelling leveraging large-scale transaction and repayment datasets
- Hybrid service models combining automation with human intervention for complex or vulnerable cases
- Continuous monitoring frameworks replacing point-in-time affordability checks
- Structured technology selection frameworks focusing on outcomes, not features
Key Statistics
- £24 billion in unclaimed benefits across approximately 7 million households
- £825,000 secured for customers by Welfare Together since inception
- Up to £10,000 in missed support identified for some households
- Around 40% of Universal Credit claimants are in employment, with a significant proportion in full-time work
- Eligibility examples include individuals earning over £80,000 in certain circumstances
- Savings thresholds of £15,999 cited as still compatible with benefit eligibility
- AI-assisted complaints may account for over one-third of cases
- Approximately 5% of the population registered within vulnerability frameworks
- Payment volumes increased by 60% in one AI-driven affordability implementation
- Payment plan “stick rates” improved by 50%
- Call handling times reduced from 50 minutes to 8 minutes in one case
- Some organisations use less than 40% of the capability of purchased technology
Key Discussion Points
- How to redefine affordability to incorporate income maximisation alongside expenditure
- The importance of engaging customers earlier in the financial difficulty journey
- The limitations of digital-only approaches for vulnerable populations
- The role of stigma and lack of awareness in benefit under-claiming
- Increasing regulatory scrutiny on outcomes and customer fairness
- The need for forward-looking, data-driven affordability assessments
- Managing risks associated with AI adoption and data integrity
- Opportunities and challenges in affordability data sharing across organisations
- Balancing innovation with risk management and compliance obligations
- The complexity of technology selection and implementation in regulated environments
- The role of cross-sector collaboration in addressing financial vulnerability
- The impact of macroeconomic pressures and cost-of-living dynamics on affordability
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