On 1–3 September 2025, the 9th meeting of the INTOSAI Working Group on Big Data (WGBD) was held in Harbin, People’s Republic of China.

The event was hosted by the National Audit Office of China. The meeting brought together representatives of Supreme Audit Institutions (SAIs) from 22 countries and regions, as well as the English-speaking subgroup of the African Organization of Supreme Audit Institutions (AFROSAI-E). The Accounts Chamber of the Russian Federation participated at the expert level.

The key topic on the agenda was the use of big data and artificial intelligence technologies to improve the quality and efficiency of public auditing.

In their opening remarks, Mr. Hou Kai, Auditor General of China; Ms. Nancy Gathungu, Auditor General of Kenya; and Mr. Gene Dodaro, Comptroller General of the United States, addressed the participants. They emphasized that the integration of big data and AI technologies is transforming approaches to public auditing — shifting from sample-based checks to continuous analysis of large datasets. The WGBD includes 51 SAIs and is advancing initiatives to develop methodologies and guidance in the field of digital auditing.

Ms. Tatiana Pavlova, Chief Consultant of the Research and Methodology Department of the Accounts Chamber of the Russian Federation, presented a project on the use of econometric and machine-learning methods in public auditing. She demonstrated an algorithm for targeted allocation of resources based on the identification of causal relationships and clustering of effects across the regions of the Russian Federation. This approach makes it possible to assess the effectiveness of investments, model social returns, and make decisions grounded in identified cause-and-effect patterns.

The methodology attracted interest from international participants and was noted as an example of the practical application of data analytics in public auditing.