Stopping homelessness before it begins

Trevor Hampton explains why a predict and prevent strategy is vital for preventing people slipping into homelessness as unemployment surges due to the pandemic

According to new government figures on homelessness in England, 63,570 households between April and June 2020, approached their local council and were found to be homeless or at risk of becoming homeless.

The latest unemployment figures from the Office for National Statistics (ONS) reveal that a worrying 782,000 UK workers have lost their jobs since March due to the impact of the Covid-19 pandemic.  

As people’s working situations become more precarious, increasing numbers of people will struggle to pay their rent.  Although there is a temporary pause on evictions from 11 December to 11 January 2021, it’s never been more critical for housing providers to have the right tools and information to be able to provide the best support possible.

Identifying signs of distress
The figures are bleak. But one way to prevent a landslide of evictions, as a result of financial distress, is to give housing providers the ability to predict which tenants are at risk of falling behind on their rent payments so they can offer proactive and appropriate support.  

Having this holistic view of residents and a true insight into their individual needs is key for being able to help keep people in their homes.

Better understanding of resident’s needs
Social housing providers have always found the balance of keeping rental income coming in difficult, while fulfilling their wider social purpose. And with increasing social issues like domestic abuse, mental health and income inequality, frontline housing officers are increasingly needing to do more to protect their tenants who are impacted by the coronavirus pandemic.

These social issues combined with the rising unemployment levels suggest the number of missed rental payments is likely to soar, meaning income managers will find themselves chasing more debt than ever.

But if they can see exactly why a payment has been missed then there’s more chance of being able to put preventative measures in place to sustain a tenancy, avoid court action or having to put a family in temporary accommodation.

A 360-degree view
Data has been powering social housing for some time but information on its own is not enough to be able to make truly informed decisions.

With such great strides being taken in the use of machine learning in the business world, the public sector is increasingly looking at how data can be analysed from multiple sources to help spot trends and anticipate where risk of homelessness exists before it develops.

To make the biggest difference to a rental arrears list, we need predictive analytics, so patterns can be pinpointed, and risks can be highlighted.

Let’s imagine we run an automated check to get a good idea of who is most likely to pay or those who may be late with their rent this month. But what if the list could be further segmented.

Having the ability to dig a bit deeper into the information to get a clearer idea of each tenant’s situation. Perhaps we discover one family is a single parent household that has a long history of paying their rent on time but have missed a few payments recently.  

Now without the cross-referencing of information, we have no idea if the late payments are the result of a job loss or if the tenant has changed jobs and the new employer pays on a different day of the month.

The point is, the fact that someone has moved from being a good payer to a late payer often gets lost, but if we can drop this information into the hands of a housing officer we can eradicate a one size fits all approach to late payment and we can help providers to decide if more help and support is needed to keep someone in their home.

Looking ahead
Some organisations have already started using data analytics tools to overlay key information on households in order to get the right help in place earlier. It could be that offering household budgeting advice or putting a repayment plan in place or specialist guidance on finding a new job is all that is needed to get them back on track.

Steps such as these can help individuals and families avoid a crisis and stay in their homes which, in turn, can save public money by reducing the time and cost associated with property turnover.  

And in an era of greater personalisation, it’s important to take a closer look at engaging residents in a way that works best for them, whether that’s by telephone, email, text or social media.  If the contact is already there, it is much easier to intervene sooner and help people avoid becoming homeless.   

Data analysis allows for dialogues to start. It helps providers deliver a targeted approach better suited to the tenants needs and prevents a destructive cycle of rent arrears from happening. By enabling tailored and timely interventions we are in a much better position to prevent vulnerable people from losing their homes.

The right technology supports housing providers to focus on the individual and allows for a more holistic approach to tenant welfare, which ultimately creates more sustainable tenancies. If we want to create a social housing system fit for a post pandemic world, then we need to use technology to create a more human response.

Trevor Hampton is director of housing product solutions at Northgate Public Services.