Pivigo has developed AI software for housing providers to predict when tenants are likely to fall behind with their rent, up to six months before it happens.
As well as looking into the future, Pivigo’s Rent Arrears Prediction platform distinguishes between high-risk and/or chronic arrears’ cases and temporary cases, enabling housing providers to focus their staff resources more effectively, as well as move away from enforcement activities, such as evictions, towards engaging with tenants around positive preventative measures.
Alex Willard, CEO, Pivigo, said, “Our technology gives housing providers a new ability to see far over the horizon. We’ve trained our AI platform with tenancy data from multiple housing providers to develop an accurate and reliable model to predict future arrears and understand the likelihood of those arrears becoming a long-term problem.
“Importantly, our software differentiates between high-risk cases and temporary cases, enabling housing providers to make smarter use of their resources.
“Our Rent Arrears Prediction platform is cloud-based, can be deployed in just eight weeks and integrated with the majority of housing management systems. We want to make the benefits of AI accessible across the entire social housing sector, regardless of whether the housing provider is large or small, technically advanced or on a budget.”
Pivigo’s ‘propensity to pay’ algorithm uses data from a wide variety of sources including tenant, household, property and rent information; weekly rent account balances; payment history; gross income and benefits; and repairs and compliance visits.
Pivigo said that other arrears management systems only issue alerts once a payment has been missed. By making tenant-specific predictions of arrears up to six months in advance, Pivigo’s AI provides actionable insights into tenants’ ‘propensity to pay’ and then suggests optimal repayment plans for long-term cases that have the best likelihood of being kept to.
