AI at the Core: How housing associations’ outdated systems cause issues for tenants and staff
At Occupi, we are looking to answer three main questions. What struggles do tenants face? What obstacles prevent housing associations from doing more to help people? And how can these issues be tackled in 2023?
These questions were posed and debated by a number of organisations and publications in 2022, including the UK Government’s 2022 Risk Report and Social Housing Residents Survey, the Better Social Housing Review’s 2022 Report, and Inside Housing’s Ten themes that should dominate the housing sector in 2023, to name just a few.
While the precise nature of the recommendations changes between each report, there are clear overriding themes: the cost-of-living crisis, overworked housing association staff, the cap on social housing rent increases, decarbonisation commitments, necessary but expensive investments in technology, and improving tenant wellbeing. Unsurprisingly, these are the same themes we’ve been hearing from tenants, housing directors and sector experts for months now.
With these points in mind, Occupi wanted to reevaluate our mission to ensure that we’re meeting the needs of the sector and aligning with our own core values. Our SMART technology is always learning and adapting, and we need to make sure that we do the same as an organisation.
As such, we are now investigating what it means to be SMART in the social housing sector, exploring how each of our five values relate to the issues faced by the industry, the underlying causes of these issues, and how Occupi is a step towards solving them.
A: AI at the Core
The third of Occupi’s five values is AI at the Core. From our many discussions with sector leaders and research groups with housing association employees, we’ve come to understand the major issues facing income teams today. Foremost of which is having unmanageably large caseloads with not enough time to complete them.
The causes of these issues are numerous, spanning from the cost-of-living crisis to decarbonisation commitments that are limiting how many new employees housing associations can hire. These are not causes that can be easily resolved. However, one major cause of these issues that can be easily resolved is the outdated systems used to create and manage income teams’ caseloads.
In most housing associations, the income team’s caseloads are organised in rudimentary ways based primarily on manual inputs. Most commonly, just one data point (the total debt for each tenant) is used to create caseloads, meaning that regardless of the cause or severity of a tenant’s debt, they will be included on an income officer’s caseload.
The problem is there are cases where a person’s debt is caused by them receiving their income days or weeks after their rent is due. For example, say that a tenant’s rent is due on the 10th of each month, however their income and benefits payments aren’t received until the 25th. In this situation, the tenant will be marked as being in arrears for 15 days each month. Cases like these are often referred to as ‘technical arrears’, and they clutter income teams’ caseloads with hundreds of non-action cases. Research has found that between 30% and 40% of caseloads are composed of these so-called technical arrears cases.
By employing AI technology that can instantly assess an officer’s caseload and remove all the technical arrears cases, Occupi is able to reduce an income officer’s workload substantially. By placing AI at the core of income and financial inclusion teams’ operations, housing associations can save time, manage their arrears and give proper support to their tenants. Occupi’s AI never sleeps and continues to learn, giving income teams the time to do what they do best: help people.