New bespoke AI system for Central Arrears Unit after recruitment issues

After the Central Arrears Unit faced issues with recruitment, a new bespoke AI database has been introduced to streamline workflows and free up time.

The Minister for Justice, Trade and Industry, Nigel Feetham, described how the Central Arrears Unit had opened a handful of vacancies but after a recruitment process found just one eligible candidate.

This mean that jobs were left unfilled and created a resourcing issue within the department.

Mr Feetham said that this was not the outcome had the unit had hoped for.

“There was a resource issue and the resources were not there, at least not the human resources,” Mr Feetham said.

He added that this resourcing issue was expected due to the technical work the Central Arrears Unit undertakes.

Mr Feetham said the methodology of the Central Arrears Unit was looked into and it “became obvious that the system that was being used is actually an outdated system”.

He said that it was an area that could benefit from technology and AI.

“When people talk about AI replacing jobs, this is an example where you’re not actually replacing jobs,” Mr Feetham said.

“You haven’t been able to find the people to do it, at least in sufficient numbers.”

Mr Feetham said staff have been given extra tools to carry out their jobs.

On Friday, Mr Feetham was joined by the Central Arrears Unit and the Tax Office at his boardroom for a demonstration led by IT Development Manager Karon Cano, who developed the model in house alongside Steven Fernandez.

Mr Cano described how previously Central Arrears Unit staff would manually extract data into an excel spread sheet which would be used to decide what senior staff needed to focus their time on.

The new system will automate this process and staff will be able to see detail on the arrears.

Mr Cano said that this is saving one member of staff at least an hour’s work. The data will be synchronised meaning that staff will get the latest information, accurate to the day.

He described how staff will be able to work on accurate data and it will reduce manual entry errors.

Mr Cano showed the system with mock data, showing the various functions and possible searches that can be exacted.

He showed that requests can be made through an AI chatbot, with no external data sources, which can provide, for example, to list of priority debts.

Mr Feetham described how this is a powerful tool to manage debt and help companies come out of arrears and flag issues quickly before they grow.