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The Impact of Artificial Intelligence, Data-analytics and Automation on the Work of Audit Institutions


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Tytti Yli-Viikari
(Auditor General of Finland)
Presentation 7.2.2020 Speyer

Published in: Data & Analytics
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The Impact of Artificial Intelligence, Data-analytics and Automation on the Work of Audit Institutions

  1. 1. The Impact of Artificial Intelligence, Data- analytics and Automation on the Work of Audit Institutions Ms Tytti Yli-Viikari Auditor General of Finland 7.2.2020 Speyer National Audit Office of Finland
  2. 2. Change Drivers External change drivers: • Unpredictable global policy • Ongoing and upcoming major changes to the structures and operating models of public sector • More complex operating environment and an increased need to deal with difficult systemic phenomena • New industry-changing technologies and digitalization impact public sector and auditing • Decision-makers faced with large amounts of information of varied quality and reliability Internal change drivers: • Our limited resources are challenged by growing stakeholder expectations: a pressure to increase productivity and effectiveness • Our aging personnel with long careers are retiring little by little: a pressure to attract new talents of next generation - with different competence and value bases and diverse expectations • Expertise sharing, project and teamwork skills needed
  3. 3. Main Emerging Issues as seen by the EUROSAI • Digitalization, technology development, AI and data • Environment and climate, sustainability • Societal changes, aging population, migration • Changes in politics and media, truth and validity • Building partnerships and increasing co-operation • Changes in audit work generally “Which are the most important emerging issues for SAI work in the 2020’s?” – 190 answers from the September 2018 EUROSAI survey
  4. 4. Skills Track for Future Audit Professionals Changes in the working methods and in the stakeholder expectations link to the required competences and skills: • Timely, accessible and relevant audit information: foresight skills, flexible planning skills, project skills • Together we are more: team-working skills and multi-policy, multi- methodology know-how • Shared knowledge-base and open access to information both internally and with partners: communication, visualization and service design skills • Shared leadership and coaching: leadership skills • Standards and guidelines are to be updated as the rapidly changing audit practices integrate new technologies and methods -> methodology change
  5. 5. AI Pilot Project in NAOF : Risk Detector Helps to identify potential risky procurements Makes the impossible possible Ensures the quality of the audit work Gives the overall picture to the auditors
  6. 6. Auditors are manually working on large datasets Struggling with finding the potential procurement risk cases Auditors have to recognize the potential risk areas based on their own expertise and judgement Current situation CHALLENGES
  7. 7. Introducing Risk Detector Advising auditors on risky procurements • Guides auditors in planning and targeting their work • Identifies potential risk cases: what procurements auditors should focus on? THE TOOL MAIN TARGET GROUP • Especially for accounting unit level audits FINANCIAL AUDITORS
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  9. 9. The AI part: Network out of purchaser-supplier relations • The whole of relations between purchasers and suppliers constitutes a bipartite network • Similar to: Tinder, Netflix • Visualization: Cutting edge meets classic
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  11. 11. The process Enrich the dataset with other public data. Also some experiments with Python, Tableau and Power BI Data understanding Understand the problem we are trying to solve, tool requirements and functionalities Business understanding / UX design
  12. 12. As an end user tool, UX was an important part of the design process. NAOF’s brand guide was used in the layout design. UX/UI design The visualizations were co-designed together with the auditors. Commitment was strong on both sides. Co-design with end-users
  13. 13. After thorough research into graph theories, a focus on visualizing the buyer- supplier network was chosen. Modeling and evaluation After some experiments with Angular, Tableau was eventually chosen as front-end tool. Azure is running in the background. Deployment
  14. 14. Open data and pilot architecture
  15. 15. Public procurement data 2018 4 070 719 411 € 62 buyers 24 789 suppliers 614 010 invoices (2018)
  16. 16. Change Leadership The Change Curve, adapted to organizational change from 1969 Elisabeth Kubler-Ross illustration. Source:
  17. 17. ISSAI 12 : Value and Benefits of SAIs • Capability to react to changes in the external environment while having a solid vision on the audit strategy • Managing the expectation gap in the role of the external advisor (vs standards) • Timely reporting is key and visualization a must • An active dialogue between the auditor and the auditee leads to better audit impact
  18. 18. The Impact of Technological and Scientific Developments on Audit • The ICT-systems within the administrations are an integral part of auditing practice ; better understanding of the essential control points and an overall vision of the process is needed. • The change will require high ICT skills from auditors and a clear vision on what to focus the audit on. • Automation of audit can lead to an improved whole-of-government analysis. • Big audit firms and SAIs are integrating AI and foresight methodologies to audit practice and radically broadening the competence of their personnel. • Analyzing policy coherence and complex policy-making systems require multi- professional teams and perspectives.
  19. 19. Thank you for your attention.