In the face of challenging reforms, smart data could become housing associations’ greatest ally. Here’s how.

Cavan DoyleKnowledge is power. So as government policy places ever-more pressure on the social housing sector, finding out more about tenants’ individual circumstances could be the only way to allocate homes fairly and remain sustainable.

Britain’s housing crisis dominated headlines in 2015. The short supply of social housing, the much-contested bedroom tax, the alarming rise in homelessness and the struggles faced by renters demanded a resolution. New policies have been introduced, yet we’re far from solving the underlying issues. And for housing associations, it seems government reforms will only stretch limited resources even further.

First up, the Welfare Reform and Work Bill. Introduced to bring the rise in social housing rents back in line with the private rented sector, it will reduce rents in social housing in England by 1% a year for four years from 2016. Based on current forecasts, this will reduce average rents in the social housing sector by around 12% by 2020.

Feeling the sharp end of the cuts is Howard Sinclair, Chief Executive of homelessness charity and housing association St Mungo’s Broadway. Writing for the National Housing Federation, he states:

‘The overall impact of the rent cut on our finances is a loss of £4 million. […] As a result of the reduction in support and rental income, we know some of our supported housing schemes will very quickly cease to be financially viable and we will have no choice but to stop running them.’

Problematic policies

Housing Minister Brandon Lewis said the move to Pay to Stay would ‘ensure that high-income social tenants pay a fair rent that better reflects their ability to pay.’ In theory this sounds good; in practice it’s fraught with problems. The National Housing Association argues that the proposed scheme ‘would be very complex and costly to administer […] the added running costs would outweigh any benefit through increased income for many housing associations.’

Where it falls down, too, is in its failure to account for individual circumstances. Chartered Institute of Housing Chief Executive Terrie Alafat points to the problematic income threshold: ‘You cannot class a household with an income of £30,000 as ‘high income’. A single person with no children might seem relatively well off, but what about a couple who both earn £15,000 and have three children?’

The extended right-to-buy scheme will give 2.3 million housing association tenants the opportunity to buy with sizeable discounts, meaning extensive development would be needed to replace the already-dwindling stock of social housing.

Universal Credits, described as ‘the biggest change in the welfare system in a generation’, will also have a huge impact. While the move to a single monthly payment is designed to encourage financial responsibility, its reception has been less than positive. A 2012 survey commissioned by the National Housing Federation revealed 98% of housing associations were concerned about their tenants’ ability to cope with monthly budgeting, and 92% of tenants would prefer their housing benefit to be paid directly to their landlord.

Understanding tenants

The difficulty with so many reforms is their reliance on statistics and generalisations. Their impact at an individual level – on living arrangements of people, couples and families – is barely understood. Tenants’ stories, such as those shared by The Guardian in January 2016, show just how complicated the real issues are.

The obvious solution is to go back to the tenants themselves, and find out more about their individual circumstances. But before embarking on one-to-one meetings with each household, housing associations can use credit data to identify and prioritise the tenants who most need their help.

RE imageThe Rental Exchange was primarily designed to give renters a fairer deal by helping them build up their credit file. But beyond this, the database can help housing associations better understand their tenants, allowing organisations to prioritise the right people to help, and understand – and therefore manage – the impact of policy changes.

By understanding of tenants’ circumstances without the need for time-consuming audits, housing associations can manage housing stock more efficiently to help offset the reduction in rent income brought about by the Welfare Reform and Work Bill. Associations can manage resources, prioritise stock more fairly, and have more informed conversations with tenants.

It was announced in December 2015 that Pay to Stay would be voluntary for housing associations. The National Housing Federation has called for each association to be able to set their own income threshold, arguing that: ‘As independent social businesses, housing association boards should be free to manage their own revenue and assets.’ It makes sense, then, that housing associations making these decisions have all the facts to hand. Only with income data can you assess each individual case, and ensure that only those who can genuinely afford to pay more do so.

Analysis by Sheffield Hallam working with the Communities and Local Government Committee showed that between 9 and 20% of eligible households may be able to take up right to buy without financial help . Experian’s analysis backs this up, showing that 10% of households would have more than a 60% chance of being accepted for a mortgage . Again, with the right data, housing associations can identify tenants who are both eligible for right to buy and in a financial position to proceed.

In answer to the concerns over Universal Credits, Alternative Payment Arrangements (APAs) offer the security of Managed Payments, made directly to the housing association, for those struggling to keep up with rent. With the ability to quickly determine those tenants who may be eligible, associations can mitigate against loss of income.

Social housing providers face some tough challenges as they attempt to safeguard their tenants and navigate the income threats posed by new reforms. The good news is that by harnessing an existing resource and gaining access to individual tenant data, they at least have a means to understand and plan for risks, allocate resources better and give help to those who need it most.