64th ISI World Statistics Congress - Ottawa, Canada

64th ISI World Statistics Congress - Ottawa, Canada

Data science in official statistical production: insights from central banks


Bruno Tissot


  • GP
    Mrs Gloria Pena

  • MR
    Mr Martin Rebolledo
  • Machine Learning for detecting social housing in the Household Price Index

  • AM
    Mr Alejandro Morales
  • Business sector classification and beyond using machine learning

  • AW
    Anggraini Widjanarti
  • An Alternative Approach for Getting Investment Direction with the Combination of Unstructured and Structured Data

  • AD
    Dr Andrea Del Monaco
  • Stacking machine-learning models for anomaly detection: comparing AnaCredit to other banking datasets

  • Category: International Statistical Institute


    The aim of this session is to focus specifically on how data science can contribute (and have contributed) to the statistics production process at central banks. Some topics include (but not limited to): (1) the automation and optimisation of statistics production processes (including dissemination and reporting), (2) the use of novel techniques in the areas of cluster analysis, outlier identification and treatment, as well as survey-level imputation, (3) the development of open-source data management platforms and its integration with existing internal systems , (4) internally-developed business intelligence (front-end) solutions for internal and external stakeholders, and (5) the sourcing, processing and dissemination of statistics using non-traditional sources of data. Lastly, central bank representatives will showcase what has been done in their respective areas on the topic. There is in particular interest in the toolchains and workflows used by central bank data scientists to enhance the sourcing, compilation, and dissemination process. The interactions with the information technology department regarding architectural designs (tech stack), the introduction of new technology, and cybersecurity considerations (and the associated challenges/opportunities) would also be analysed.