From the desk of ASOSAI Secretary General

Strengthening Research and Application of Artificial Intelligence and Machine Learning to Improve Audit Efficiency and Quality

With the rapid development of information technology, Artificial Intelligence(AI) and Machine Learning have emerged as pivotal driving forces in a new wave of scientific and technological revolution and industrial transformation, that will stimulate various industries to evolve towards digitalization, intelligence and automation, and reshape our ways of work and life in many aspects. At present, many countries regard AI and Machine Learning as major strategic resources to enhance national competitiveness. In the context of technological revolution, audit institutions mandated with economic oversight function need to keep abreast with the times, watch closely the development of AI and other technologies, spare no effort in envisaging the application of these technologies to promote intelligent and smart audits, and carry out explorations when conditions allow. At the 61st Governing Board Meeting of ASOSAI, “The Use of Artificial Intelligence in Audits” was chosen the topic of the 14th ASOSAI Research Project, indicating SAIs in Asia have been aware of the development trend.

In the era of big data, traditional audit techniques have struggled to keep pace with the rapid changes and complexities of big data. Continuous progress in technologies including AI, Machine Learning, Natural Language Processing (NLP) are creating new opportunities for public sector audits. Featuring efficiency, accuracy, self-learning and high stability, the emerging technologies free auditors from such repetitive, time-consuming and laborious tasks as data collection and data cleaning, and help auditors quickly extract key information from massive data for further analyses and explorations. Based on sufficient practices, some intelligent audit systems can also be developed to automatically identify abnormalities through data analysis of financial information and transactions, and even perceive risks through ongoing self-learning from data and models, further improving audit efficiency and quality while extending its scope and depth.

However, factors including data quality, security risk, costs and capacity of auditors will pose challenges to the effectiveness of technologies regarding AI and Machine Learning in public sector audits. Above all, regardless of technological development, all countries need to fulfill audit responsibilities and conduct audits in a well-organized manner based on respective actual progress of technological development.

By sharing research outcomes and practices of SAIs in the fields of AI, Machine Learning and other technologies, this issue of Asian Journal of Government Audit guides and inspires SAIs to attach importance to new techniques to facilitate audit experience exchange, knowledge sharing and capacity enhancement.

With joint and unremitting endeavors, SAIs in Asia will gain more insights and make more adequate preparations for the application of AI and Machine Learning. On this basis, they will further improve audit efficiency and quality, contributing to comprehensive and sustainable economic and social development.