23 luglio

9.00 Registration – Morning coffee

10.00 Welcome speech
Paolo Maria Mancarella, Rector, University of Pisa

Alessandro Balestrino, Director, Dept. of Political Science, University of Pisa

Silvio Bianchi Martini, Director, Dept. of economics

10.15 Opening remarks
Danièle Lamarque, ECA, Member for Audit Quality Control

10.45 Introduction to the School: objectives and methodology. Participants’ presentation
Gilberto Moggia, ECA

11.00 Making sense of data – data, information, knowledge (Extracting value from data – 1.A)
Dino Pedreschi, University of Pisa, Department of Computer Science & Pisa KDD Lab – Knowledge Discovery and Data Mining Laboratory

12.00 – Lunch [90 minutes]

13.30 Opening lecture
Supreme Audit Institutions and Governance: Opportunities for Data-Driven Oversight, Insight and Foresight
Gavin Ugale, OECD ( Public Sector Integrity), Policy Analyst and Portfolio Manager

15.15 Big data – security and privacy – the IT perspective (Extracting value from data – 1.B)
Gianluca Dini, University of Pisa – Department of Information Engineering

16.30 Public administrations’ work with data – the perspective of administrative law (Extracting value from data – 1.C)
Fabiana di Porto, University of Salento – Department of administrative law

24 luglio

8.30 Morning coffee

9.00 Data, analytics and auditing: concepts and definitions (Data analytics for auditing – 2.A)

11.00 Data analytics for auditing: methods and techniques (Data analytics for auditing – 2.B)

12.30 – Lunch [90 minutes]

14.00 The big data value chain in the auditing process (Data analytics for auditing – 2.C)

25 luglio

8.30 Morning coffee

9.00 The use of big data within the official statistics community: definitions, data-sources, and main challenges (Statistical methods and techniques for data analysis – 3.A)

10.00 Statistical techniques for data analysis (Statistical methods and techniques for data analysis – 3.B)

11.45 Big data and statistics – Eurostat’s experience (Statistical methods and techniques for data analysis – 3.C)

12.30 – Lunch [90 minutes]

14.00 Data driven audit – case studies & field experiences (Data driven audit – 4.A)

After the lecture, participants will briefly present their cases or field experiences (max. 20 minutes each); the presentations will be followed by a common discussion, facilitated by scholars and experts.

Potential topics:

  • Audit risks and data analysis
  • Using big data for audits
  • How to combine information from various data sources to gain additional insights
  • Techniques to identify abnormal patterns in the data
  • Data analysis and fraud detection

26 luglio

8.30 Morning coffee

9.00 IT methods and techniques for data analysis (IT methods and techniques for data analysis – 5.A)

10.00 Machine learning and predictive analysis (IT methods and techniques for data analysis – 5.B)

11.00 Text analysis (IT methods and techniques for data analysis – 5.C)

12.30 – Lunch [90 minutes]

14.00 Data driven audit – case studies & field experiences (Data driven audit – 4.B)

This part of the course is open for contributions by participants. Their short presentations of case or field experiences (max. 20 minutes each) will be followed by a common discussion, facilitated by scholars and experts.

Potential topics:

  • Is auditing only about the past? Continuous auditing and monitoring
  • Is auditing only about the past? Is predictive auditing possible?
  • Mapping and visualizing data across systems to produce audit evidences
  • Text mining for auditing

27 luglio

8.30 Morning coffee

9.00 Data driven audit – case studies & field experiences – follow-up of the group work (Data driven audit – 4.C)

10.45 Data mining and analytics – What implications for the audit profession? Round table (Data mining and analytics – implications for the audit profession – 6) Round table

12.30 – Lunch [90 minutes]

13.30-15 Final individual and group assessment – Final comments and conclusions

< View General informations