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SBRI: developing a data enabled public sector audit approach

Registration is closed
Funding details
Registration opens
19 Nov 2018, 00:00
Registration closes
09 Jan 2019, 00:00
09 Jan 2019, 00:00
A share of £1.25 million, including VAT; phase 1 up to £50,000 project costs per organisation, phase 2 up to £500,000 per organisation
GovTech Catalyst

This is a Small Business Research Initiative (SBRI) competition with funding provided by the GovTech Catalyst.

The competition is sponsored by the Northern Ireland Audit Office (NIAO), working in collaboration with Audit Scotland and the Wales Audit Office.

A briefing event will be held in Belfast on 22nd November: click here to register for a place.


The NIAO is responsible for the audit of public sector bodies and undertakes financial and value for money audit.

The NIAO plans to develop a data enabled public sector audit approach which makes use of analytics techniques and machine learning. The aim is to improve the efficiency and effectiveness of audit by increasing coverage and adding value to clients.

The competition looks at 2 main areas:

  • Financial audit analytics, which is analysing and automating audit testing of whole populations and identifying anomalies.
  • Value for money analytics, which is analysing data to inform a thematic report.

This is a first phase of a 2 phase competition. We expect phase 1 projects to range in size total costs of up to £50,000, including VAT, for each organisation. Projects are expected to start by 29 April 2019, end by 22 July and last up to 12 weeks.

A total of £1,000,000, including VAT, is allocated to phase 2. This will fund 2 projects up to £500,000 including VAT each. Funding will be used to develop a prototype for 2 of the solutions identified during phase 1 over 12 months.


The aim of this competition is to develop a holistic data enabled audit approach capable of capturing, extracting, cleansing, formatting, interpreting, analysing and presenting data from a range of sources.

In phase 1 you must address at least one of the 2 points below:

  • Financial audit analytics. This involves analysing and audit testing whole financial transaction populations and identifying high risk transactions, anomalies and potential irregularities for further human investigation, possibly using machine learning. A solution could include the use of visualisations and automation. It could also explore the possibility of comparing data over time with other organisations and publically available data to identify trends and anomalies. All applicants must demonstrate that their final solutions will be capable of extracting, cleansing and validating information from different financial management systems.
  • Value for money analytics, which is analysing management information and publicly available data to provide evidence to support findings and recommendations in a wide variety of thematic reports. A selection of these studies and the range of topics they cover can be viewed on the Northern Ireland Audit office website.

In phase 1 testing will focus on Northern Ireland data.

If you reach phase 2 you will further develop the R&D undertaken during phase 1 with a view to producing a prototype. You will also use data supplied from other sources including our partner UK audit agencies.