Data analytics to bring about benefits in public audit

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At the request of Deputy Auditor General Ha Thi My Dzung, in order to solve difficulties in accessing and collecting public audit data, SAV’s Working Group on Information Technology (IT) Application should proceed with specific and right-purpose steps through the clear, thorough and effective methods.

In the four stages associated with the public audit process, data analytics has clearly shown significant benefits.

Data analytics plays an important role 

Data analytics is the application of scientific methods of data science to gain insights from collected data. According to SAV's research, data analytics includes: sequence of steps in data collection, data processing, data analytics, evaluation and reporting of the results of the analysis.
According to Mr. Le Anh Vu, Head of Division of IT audit, Specialized Audit Department No. VII, data analytics in public audit commences with identifying and collecting different data sources for an audit of public assets and finances. Through different data analytics techniques, state auditors will gain insights into audited entities such as public financial data, public policy, public service, etc. These are considered as a basis for making assessments of audit risk and materiality, determining audit content, selecting audit samples or giving audit opinions. “Collecting data without detailed analysis will cause an intensive waste of resources. Auditors have to go into each core part of data analytics process so as to define key issues, then select items for testing and provide audit opinions.” emphasized Deputy General Auditor Ha Thi My Dzung.

According to Mr. Vu, data analytics clearly shows significant benefits in the four stages of a public audit. In the planning stage, it can help state auditors to have both the overview and detailed description of the audited entity, reduce bias, thereby improve the quality of risk assessment, identify key issues and decide detailed audit sampling, which is also an important basis for optimal allocation of audit resources. In the implementation stage, individual audit findings can be evaluated on a system-wide basis of audited entity by analyzing big data in order to detect all similar errors. During the preparation and issuance of an audit report, data analytics helps to improve the quality of presentation and visualization in the audit report preparation process. As a result, it generates more interesting contents as well as more useful suggestions for stakeholders. In the stage of following audit recommendations and conclusions, data analytics can be applied to current data of the audited entities and compared with the results of data analytics during the audit so as to evaluate the implementation of audit recommendations and conclusions.  
INTOSAI’s Guidelines on Data analytics
Up to the present, International Organization of Supreme Audit Institutions (INTOSAI) has developed two guidelines for data analytics in auditing acivities. Specially, these include Data analytics Guidelines issued in 2019 (Guidelines 2019) whose aim is to provide general guidance on conducting data analytics in audit activities and Guidelines on applying data analytics in audit activities. issued in 2020 (Guidelines 2020).
With reference to to INTOSAI’s guidelines, in order to analyze the data, auditors should have a mathematically inclined mind, understand algorithms, know programming, understand how data is exchanged across IT systems and how it is presented in a comprehensible way as these are the key skills determining the orientation for personnel training of SAIs.
Accordingly, Deputy Auditor General Ha Thi My Dzung said that SAV shall have to proceed with specific and right-purpose steps by using clearer, more thorough and effective methods during the data collection phase./.

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