Predicting Tenant Arrears in Real-Time with AI

But what if we could spot the warning signs earlier? Could artificial intelligence (AI) and predictive analytics help housing providers move from reactive arrears chasing to proactive tenant engagement?  

In this article, we’ll explore the potential of AI in income management, why predictive insights matter, and how housing organisations can lay the groundwork for smarter, more connected solutions. 

Why tenant arrears are so hard to manage 

Traditionally, arrears management has been reactive. Income officers often rely on historical data and manual processes to identify tenants at risk. By the time a missed payment is flagged, the arrears may already be growing, making it harder and more costly to resolve.  

This reactive approach creates several challenges:  

• Delayed interventions: Support often comes too late to prevent financial hardship.  
• Resource strain: Income teams spend valuable time chasing arrears instead of engaging proactively.  
• Tenant stress: Late interventions can damage trust and increase anxiety for tenants.  
• Loss of revenue in a challenging financial climate: For public sector organisations already under budgetary pressure, every missed payment impacts cash flow and financial resilience, making arrears prevention more critical than ever. 

The question is: how can housing providers get ahead of the problem? 

Social housing is at a tipping point

For millions, social housing is more than shelter, it’s security in uncertain times. But the sector is under increasing strain. Access PaySuite’s Rental Arrears Index reveals the scale and urgency of the challenge.

Between 2019 and 2024: 

• The average number of social housing units in arrears per local authority rose by 17%, from 3,733 to 4,426. 
• The average value of arrears increased by 71%, from £1.84 million to £3.14 million. 
• The proportion of tenants in arrears rose from 35% to 41%. 

This analysis is based on Freedom of Information (FOI) responses from 82 local authorities - representing over one-third of the UK’s council-owned housing stock and more than 1,500 data points collected between 2019 and 2024. 

These rising arrears reflect both tenant financial distress and the growing strain on housing associations and local authorities to sustain service levels amidst shrinking budgets. 

The regional impact 

Arrears are not distributed evenly across the country: 

• Local authorities in London are facing the highest levels, with an average of £10.1 million owed per council. 
• In Yorkshire and the Humber, the average is £4.8 million. 
• Councils in the South East and East of England reported the lowest levels, each under £1 million. 

Full regional breakdowns are available in the Rental Arrears Index report. 

Sector-wide stress 

The pressure extends beyond local authorities. According to The Regulator of Social Housing reported, rent arrears across housing associations reached a record £798 million in 2023, an 8.4% year-on-year increase, the highest annual rise since before the pandemic. This equates to around 5.3% of housing association tenants falling behind on rent. 

Between 2015 and 2018, arrears remained steady between £500–£600 million but have climbed sharply since, underscoring the worsening affordability crisis in the sector.  

Why predictive insights matter 

The benefits of predictive technology in income management are clear:  

• Proactive engagement: Identify risk earlier and offer tailored support.  
• Improved tenant outcomes: Reduce financial stress and maintain housing stability.  
• Operational efficiency: Free up officer time for complex cases.  

For housing providers, this means fewer arrears, better cash flow, and stronger tenant relationships.  

But there’s a catch: before AI can deliver on its promise, organisations need to address a fundamental challenge - data fragmentation. 

Laying the groundwork: Centralised, connected data 

AI thrives on data. Yet, in many housing organisations, income-related information is scattered across multiple systems. From rent accounts to benefits records and CRM platforms. This fragmentation makes it difficult to get a complete picture of a tenant’s financial situation.  

Modern Income Management solutions are starting to tackle this issue by:  

1. Bringing data together into a single, accessible view.  
2. Automating routine tasks like payment reminders or case updates.  
3. Highlighting trends that may indicate emerging arrears risk.  

These capabilities lay the foundation for more intelligent, responsive Income Management, even if full AI-driven prediction is still on the horizon. 

The reality today: Where are we now? 

While AI-powered arrears prediction is an exciting prospect, it’s important to be realistic. Most Income Management systems today, including Income Management Evo, are focused on data centralisation, workflow automation, and reporting rather than advanced predictive analytics.  

That doesn’t mean progress isn’t happening. By consolidating income data and streamlining processes, solutions like Income Management Evo are creating the conditions for AI to add real value in the future.  

Think of it as building the foundations:  

• Step 1: Centralise and clean your data.  
• Step 2: Automate repetitive tasks to free up officer time.  
• Step 3: Layer on predictive insights as the technology matures.  

Looking ahead: The future of Income Management 

The direction of travel is clear: smarter, more connected tools that help housing providers stay ahead of the curve. As AI capabilities evolve, we can expect to see:  

• Early-warning dashboards that flag high-risk tenants.  
• Automated prioritisation of cases based on risk scores.  
• Personalised engagement strategies driven by data insights.  

For now, the focus should be on readiness. Housing providers that invest in modern, integrated income management systems today will be best placed to take advantage of AI tomorrow. 

Related: AI-enhanced rent collection: Protecting vulnerable tenants without sacrificing revenue

How Access PaySuite is supporting this shift 

At Access PaySuite, we understand the challenges income teams face and we’re committed to helping organisations move from reactive arrears chasing to proactive tenant engagement.  

Our Income Management Evo solution is designed to:  

• Centralise income data for a single source of truth.  
• Automate workflows to reduce manual effort.  
• Provide actionable insights through intuitive dashboards and reporting.  

While full AI-driven arrears prediction is still on the horizon, Income Management Evo is laying the groundwork for smarter, more connected income management.  

Ready to take the next step? 

Discover how Access PaySuite Income Management Evo can help your organisation reduce arrears, improve tenant outcomes, and prepare for the future of AI-driven income management.