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May 02, 2019


Universal credit and the power of data

There is still considerable uncertainty across the housing sector as many organisations wait to see what the impact of the full roll-out of universal credit will be for their organisation. Therefore, we wanted to speak to organisations all over the country to find out what they thought the impact would be and how they are attempting to mitigate the impact of universal credit.

As a result, we have spoken to over 30 organisations from across the UK as part of our ‘impact of universal credit research’ which took place in early 2018.

Universal credit impact is the ‘known unknown’

When it comes to the full roll-out of universal credit, many organisations are planning, preparing and testing for worse case (or as one interviewee described it, ‘black swan’) scenarios in their business plans. Unsurprisingly, over 75 per cent of respondents stated they are expecting significant or huge increases in the number of arrears cases, with rent arrears going up to 10-15 per cent and unprecedented increases in ‘bad debt’. Similarly, 82 per cent of respondents stated that they are expecting to experience a significant or huge increase in their workload – not just in income teams but also particularly across finance, ICT and customer services teams. Indeed, many of the organisations we have spoken to have undergone significant restructures, retraining, and increased investment in both headcount and digital technologies to deal with the expected increase in workload, with further changes due once the areas in which they operate in go to full service.

However, one executive we interviewed described the feeling in the sector best when he stated that the impact of universal credit is a ‘known unknown’. Many of the executives involved in our research have stated that a lack of visibility of timely, meaningful and relevant data makes it very difficult to know what the true impact will be with any degree of accuracy, or how long it will last.

Many have found the level of arrears experienced as part of live service to be less severe than they had feared, while still believing that when it comes to full roll-out, arrears will be much worse. One such example comes from Jackie Bishop, a neighbourhoods manager at SLH Group, who noted that although arrears increases experienced as part of live-service are not as bad as they predicted, the feedback that they are getting from external partners forecast ‘dramatic week-on-week increases in cases’. Amid this uncertainty, most organisations continue to predict that universal credit is going to have a significant impact (and perhaps the biggest impact in recent years). The question is: how do you respond to a problem when you don’t know how bad it will be?

A key issue that is repeatedly cited is that tenants don’t want to know about universal credit until it affects them. This makes preparing for and predicting the impacts in advance of the switch over to universal credit, at least, very difficult.

There also appear to be a lot of variables when it comes to the likelihood of those tenants receiving universal credit paying their rent on time (or not paying it at all), with key factors ranging from tenant vulnerabilities and employment history through to the range and availability of partner support agencies. Combining this with an expected increase in the number of arrears cases and previous payment histories being largely flipped on their heads, it seems there is a perfect storm brewing for generating a lot of ‘white noise’.

Putting the increased workload and team restructures aside, this makes it a lot harder for income teams to be able to know who is going to pay their rent on time, who is going to pay it a little bit later but without intervention and who needs a lot more attention and support. As resources become even more stretched, it is vitally important that these questions are answered to ensure efforts are not being wasted unnecessarily, while simultaneously making sure targeted help is given to those who need it most.

The power of using data

Many organisations highlighted the importance of data, intelligence, prediction and reporting in being able to navigate rent arrears. While organisations wait to see how their business are affected, they are turning to the data that they already have to provide insights and predictions of their new reality and where they need to focus their attention and efforts.

The most obvious place to start is separating out ‘true arrears’ from false ones. With stretched resources, organisations don’t have the ability to take a scattergun approach. Therefore, the key is predicting and identifying which tenants will eventually settle their rent arrears and make regular payments without the need for action and those that need more attention and support.

This might sound easy, but with one northern housing association estimating that it takes two or three cycles of universal credit payments before tenants start falling into a payment pattern even when they are receiving intensive UC support, this may not be as easy as it sounds. You also need to consider other factors, such as whether an arrangement has been met or broken. On top of this, the days of being able to analyse this data and manage arrears on a weekly basis have gone. With so many variables at play and the importance of addressing arrears issues as early as possible before they snowball, it is key that analysis happens on a daily basis.

We have established a data-science function here at Orchard that has enabled us to develop the predictive capability of our new arrears management solution, Income Analytics. This predicts and then removes technical arrears from case lists and enables housing providers to target resources on accounts in arrears that need their attention.

Working with leading experts from Newcastle University, we now have the capability to incorporate advanced techniques such as machine learning into our products, and we hope to use this in the future by developing new features in Income Analytics that deliver insights for both income teams and senior management.

Going digital

Income Analytics is a cloud-based, mobile-first solution, which is offered to customers as a subscription service. Our aim is to help organisations to assess where they are and where they want to be, mapping the digital journey, engaging with customers or staff, defining what success looks like, or looking at how organisations can push their digital services forward and evolve their offer for their tenants.

This new suite of transformation services reflects a fundamental change in our working philosophy. An effective digital transformation approach underpins any housing provider’s remit to deliver a value for money strategy, and we now have access to proven expertise from outside the sector that can accelerate the path to benefit for all parties.


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