SUMMER 2025 DIGITAL - Flipbook - Page 36
GPSJ
LOCAL AUTHORITY & COUNCIL
Preventing arrears and
sustaining tenancies: The AI
advantage in social housing
By Alex Common, divisional director, product and engineering at Access PaySuite,
part of the Access Group.
Social housing providers across the UK are facing an unprecedented crisis. Rental arrears soared by more
than 70% between 2019 and 2024, with the average owed per each local authority standing at a staggering
£3.1 million. In the same time period, the average number of social housing units in arrears per local authority
rose by 17%.
And the pressure extends beyond
local authorities: last March,
the Regulator of Social Housing
(RSH) recorded an 8.4% rise
in rental arrears reported by
housing associations - hitting a
record high of £800 million - the
highest single year jump since
before the COVID-19 pandemic.
These are not just 昀椀nancial
statistics - they re昀氀ect the harsh
reality confronting millions of
social renters who are struggling
to make ends meet.
What is particularly concerning
is that 70% of social renters
report di昀케culty paying their rent.
Many of these tenants are forced
to make heartbreaking decisions
- choosing between heating their
homes, feeding their families,
or paying rent. This is not just a
problem of rent collection. It is a
crisis of wellbeing, social stability
and fairness.
The pressure on housing
providers is immense. They are
caught between safeguarding
their own 昀椀nancial viability and
supporting vulnerable tenants in
distress. The traditional manual
systems that have long been
used to collect rent and manage
arrears simply cannot keep pace
with this growing complexity.
Missing a single rent payment
can trigger a chain of problems
for both tenants and landlords,
and it’s clear that the time for
36
reactive management is over.
What social housing desperately
needs is a shift towards
proactive, preventative solutions.
Why old systems are failing
prevented. The relationship
between landlord and tenant also
su昀昀ers, while the risk of tenancy
failure increases.
Simply put, these systems are
no longer 昀椀t for purpose.
Manual rent collection processes
were designed for a very
di昀昀erent time. They rely on static
schedules and trends, manual
oversight, generic reminders and
largely reactive approaches that
come into play only after arrears
have already piled up.
These systems also do not
accommodate the reality of
tenants’ lives - which are often
unpredictable and can be prone
with sudden 昀椀nancial shocks.
It’s known that rental arrears
may 昀氀uctuate throughout the
year due to changes in bene昀椀ts,
the cost of living crises or other
economic factors, yet, traditional
approaches often fail to adapt or
respond early enough.
Instead, they wait until a tenant
has missed payments multiple
times before stepping in, which
by then often feels punitive rather
than supportive. Ultimately, this
outdated approach puts housing
providers on the back foot, and
places enormous pressure on
teams.
Frontline sta昀昀 become
overwhelmed dealing with high
volumes of rental arrears cases,
many of which could have been
Arti昀椀cial intelligence (AI) o昀昀ers a
much-needed breakthrough. The
power of AI lies in its ability to
analyse vast amounts of data and
identify early signs of 昀椀nancial
strain long before rental arrears
accumulate and crisis unfolds.
It gives local governments a
level of insight that was previously
out of reach. Achieving this depth
of analytical understanding for
a single individual would have
required an immeasurable
investment of time and resources
- something human interaction
alone could never deliver.
AI-enhanced systems - such
as our very own AI-powered
income management platform
Access Evo, which we’re
developing in active collaboration
with the market - will allow
housing providers to bring
together live payment data,
tenant engagement signals and
bene昀椀ts status in one place.
Sta昀昀 will then be able to focus
their e昀昀orts on households
that may need early outreach,
without having to chase data
across disconnected systems.
GOVERNMENT AND PUBLIC SECTOR JOURNAL SUMMER 2025
The AI advantage
Ultimately, this will help housing
teams translate insight into early,
tailored interventions, delivered at
scale.
Tenants will receive
communications that feel relevant
and helpful, rather than easilyavoidable generic reminders.
The e昀昀ect of this will be twofold:
tenant engagement will be
enhanced while rent collection
rates will improve, creating
a positive cycle of trust and
sustainability.
Balancing tenant wellbeing
and 昀椀nancial resilience
Too often, rent arrears
management and tenant
wellbeing are treated as being
in con昀氀ict, rather than mutually
reinforcing. At this moment in
time, housing providers feel
forced to choose between
chasing payments and
supporting vulnerable tenants,
but AI is changing this dynamic.
With AI-driven systems,
providers can maintain a clear
focus on long-term tenancy
sustainability. Early intervention
reduces the stress and stigma
for tenants who might otherwise
spiral into arrears. This
fosters healthier, more stable
communities and prevents the
costly cycle of eviction and
rehousing.
From a 昀椀nancial perspective,
