With Access Evo, providers can now use AI to gain early visibility into rent payment behaviour, centralise income data across systems, and personalise support workflows—all while improving collection performance.
A growing problem, and a shrinking margin for error
Access PaySuite’s latest Rental Arrears Index reveals just how urgent the situation has become:
- 41% of council-owned tenancies are now in arrears—up from 35% five years ago
- The average local authority is owed £3.14 million, a 71% increase since 2019
- In London, that number jumps to over £10 million per council
Housing associations are now carrying a record £798 million in rent arrears, up 8.4% in the past year alone. In this environment, doing “more of the same” is no longer an option.
The real cost of traditional income management
Legacy income systems are often reactive, generic, and administratively heavy:
- Teams spend hours sifting through data that’s already outdated
- Tenants receive the same messages, regardless of risk or context
- Interventions come too late - after trust, stability, and payment momentum are lost
This model doesn’t just hurt recovery rates. It erodes relationships and wastes resources on misdirected or mistimed efforts.
Access Evo: Where AI meets human-centred income management
Access Evo changes the equation.
It’s an AI-powered platform that enables housing providers to:
- Spot early signs of arrears risk—before payments are missed
- Segment tenants by actual need—not assumptions
- Automate the routine—and personalise the response where it matters
- Bring together payment and benefit-related data* into a single, unified view
- Identify households showing early signs of payment difficulty through real-time engagement signals
*Benefit-related data (e.g. Universal Credit) can be incorporated via third-party systems, provided by the customer.
How It works: Precision without pressure
Access Evo continuously analyses a wide range of real-time data points:
- Payment history and lateness patterns
- Changes in benefit-related status (e.g. Universal Credit)*
- Local economic signals like energy prices or inflation trends
- Behavioural cues—like reduced engagement or missed logins
Rather than assigning a risk score, Evo presents these indicators in a clear, dynamic interface—empowering staff to spot trends and take proactive action.
- A tenant struggling with benefit delays? Easily identified and flagged for early check-in
- A household showing reduced payment reliability? Automatically routed to flexible support options
- A stable, low-risk tenant? Let automation handle the rest
No guesswork. No delay. Just data that’s accessible, actionable, and human-centred.
*Benefit-related data can be included via third-party systems, provided by the customer.
Protecting the vulnerable, sustaining the mission
This isn’t just smart tech—it’s a smarter approach to social impact.
With Access Evo, housing teams can:
- Intervene sooner, with support that fits the situation
- Free up staff time, focusing effort where it’s most needed
- Recover more rent, without relying on escalation or enforcement
- Strengthen trust, by acting before problems become crises
It’s about bringing compassion and efficiency together—not trading one for the other. A step change, not just a system change
Housing providers who’ve adopted Evo report not just better financial performance, but better outcomes across the board:
💬 “We’re having conversations we would’ve missed six months ago.”
💬 “Our teams are less reactive, more strategic.”
💬 “Tenants feel heard—not hounded.”
Access Evo isn’t another reporting tool. It’s a central hub for insight, action, and impact—where real-time data powers human connection.
Income resilience starts here
The housing sector doesn’t need to choose between compassion and collection.
With Access Evo, you can build both—at scale.
- Surface early indicators of financial strain
- Personalise support without adding admin burden
- Improve collections while safeguarding relationshipsThis is what AI-enhanced rent collection looks like: fair, focused, and financially sustainable.