Trevor Hampton, director of housing product solutions at Northgate Public Services explores how a more robust approach to ‘predict and prevent’ could help stave off a potential avalanche of evictions in the wake of coronavirus.
A poll at the start of 2020 found that we are all on average just two and a half pay checks away from becoming homeless. A startling fact that for some people, in the wake of coronavirus, could fast become a reality.
A recent report from Shelter said that around 320,000 adults have fallen into rent arrears since the start of the pandemic. A situation that is likely to be exacerbated now that the government’s extension to the emergency legislation preventing any new housing possession proceedings has ended (at the time of writing in early November).
But what if there was a scalable fix that could help housing providers predict which tenants in arrears would benefit most from high-impact crisis interventions? Not a future fix, but one that could easily be deployed now to quickly identify problems and signs of financial distress.
A balancing act
Housing providers have long grappled with the conundrum of keeping rental income coming in while staying true to their wider social purpose – not easy.
And now even less so, in a time of economic uncertainty and the worsening of profound social issues such as domestic abuse, mental health and income inequality.
A rise in missed rental payments in the wake of the pandemic means income managers are chasing more debt than ever. Understanding why someone is missing rent payments and what support could be given might make all the difference between sustaining a tenancy and avoiding court action or having to rehome a family in temporary accommodation or worse.
Having a 360-degree view of tenants has never been more needed to help keep people in their homes. It has also never been more possible.
A rich picture
The importance of data in housing is now well established and much of the heavy lifting has been done by housing providers themselves to become ‘data fit’. But this isn’t enough on its own to provide the full picture.
The next step is predictive analytics, where patterns in data are identified and the risks highlighted. This is the brain behind data’s brawn and will become a necessary tool in helping housing providers to take a more holistic and nuanced approach to decision-making.
This means the data already in housing management systems needs to be harnessed so that information such as historical rental payments can be enriched with other data to give a more rounded view of tenants and their needs.
Take the arrears list
An automated check can be run against the arrears data so tenants can be assessed and ranked into those most likely to pay and those less likely to do so. But the list should then be further segmented. What about those on the list who are elderly and have missed payments? They could be behind because they’re ill or perhaps unable to pay online.
Or if they are a single parent household with a good history of rent payments, could a sudden few missed payments be the result of a job loss or merely the consequence of their move to a new employer who pays on a different day of the month?
This cross-referencing of information will help the housing provider decide if more help and support is needed to keep someone in their home or a different approach is required.
Preventing eviction
Social housing has always been more than just a numbers game, but without all the information a tenant becomes just that, another number on the list.
Making better use of the available data creates the time and space for income managers to make the right decision for the tenant; it’s about using the technology to provide a more human response.
Above all, it enables housing providers to place tenants at the heart of their operations while at the same time taking steps to balance the books.
Trevor Hampton is the director of housing at Northgate Public Services.
