As social housing rent arrears hit £1bn earlier this year, an innovative tech firm is using first-of-its-kind artificial intelligence (AI) to help housing associations predict when residents are likely to fall behind with their rent – up to six months in the future.
Pivigo’s Rent Arrears Prediction AI platform means social landlords can reduce the number of tenants struggling with debt and drive down lost rental income needed to run services and build new homes.
By predicting arrears early, staff can focus on positive prevention and support for tenants – including the most vulnerable – rather than focusing solely on recovering missed payments. According to the Chartered Institute of Housing’s #ShineALight campaign launched in 2020, around one in three social housing tenants in rent arrears are experiencing mental health problems.
The Pivigo platform is the first of its kind in social housing to predict rent arrears up to six months before they happen.
Alex Willard, CEO of Pivigo, said: “Our technology is giving social housing new-found abilities to see far over the horizon. We have trained our AI on tenancy data with multiple housing associations to develop an accurate and reliable model to predict future arrears and understand the likelihood of them becoming a long-term problem.
“We differentiate the high-risk cases from temporary ones, enabling social landlords to make better use of their resources to benefit both residents and the organisation.”
Using AI to predict who is most at risk of falling into arrears means income and support teams can contact the right tenants at the right time so they can avoid the stress and anxiety of being in debt.
It comes at a time when housing providers have seen a rise in rent arrears as the Covid-19 pandemic has affected residents struggling with furlough, reduced working hours and redundancy.
Pivigo, based in Sheffield, build and manage AI Services for social housing. This approach means that social landlords need little in-house IT expertise to benefit from AI, as the platform is cloud-based, deployed in 8 weeks and can be connected to existing housing management systems.
Alex added: “We want to make the benefits of AI accessible across the entire social housing sector, regardless of whether the landlord is big, small, tech-advanced, or on a budget.”