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Housing association tests AI and machine learning to cut costs

Image courtesy of Incommunities
A Yorkshire-based housing association is to trial the use of AI to reduce costs and improve efficiency.

Jointly developed by the University of Bradford and the housing association, Incommunities, the two-year project will use machine learning to predict things such as boiler checks, general maintenance, and housing repairs, and could also be used to help tenants who might fall into debt.

One example of aspects of cost that the project could tackle is the number of ‘no access’ compliance safety check visits, where tenants are not at home when gas engineers call. Machine learning will use data to reduce the number of no-access visits, improving customer service, safety and making efficiency savings.

A report into the project states: “This will digitally transform the operations and decision-making processes across the organisation to the benefit of the company and enhance the quality of service for customers. Incommunities believes that this project will bring about real benefits in their day-to-day management and operations, play a crucial role in supporting their customers, and overall reduce operational costs.”

Ethical culture key to project

Professor Sankar Sivarajah, head of the School of Management at Bradford University and principal investigator on the project, said: “One of the fundamental aims of this project is to embed an ethical data-driven business culture by adopting an AI-based innovation strategy for Incommunities.

“Using AI and machine learning can help us predict and prioritise our services more effectively, reduce costs, and improve efficiencies across the business.”

Jason Baines, Incommunities

“Incommunities will address business challenges leading to significant productivity gains by adopting an ethical and responsible data-driven AI strategy for effective operational decision-making across the organisation.

“Our project team, which includes Dr Takao Maruyama and Professor Zahir Irani, with the support of a Knowledge Transfer Partnership associate, will help build internal capacity and capability for Incommunities in embedding digital culture transformation and technical expertise in optimisation models, and predictive and prescriptive analytics.”

Jason Baines, director of ICT and business intelligence at Incommunities, said: “We are committed to ensuring customers are at the heart of our business and that the services we deliver reflect their needs. Using AI and machine learning can help us predict and prioritise our services more effectively, reduce costs, and improve efficiencies across the business.”

The project has funding of £179,165 for two years from UK Research and Innovation.

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