About this learning event

In an increasingly complex and sophisticated financial landscape, the supervisory role heavily relies on timely access to data. However, data wrangling, constructing models, and analyzing results form only one aspect of bank surveillance. The other equally important aspect in macroprudential supervision and policymaking involves communicating the results to the central bank’s board, financial institutions, and the wider public. When drafting reports or presenting stress-test results, it is highly important to visually present the data through meaningful figures, interactive dashboards, and infographics. At this webinar, we will discuss how to find meaningful relationships within large data series and use data visualization tools to communicate findings effectively.

What will you learn

During this webinar, we will discuss following topics:

• What are the main types of data visualizations and when to use them;
• How to avoid common pitfalls when creating graphs;
• Striking the right balance between visual innovation and clarity;
• How to use cases applied to Central Banking and policy analysis;
• Dashboards creation and the role of interactivity in conveying structured messaged;
• How to use data to tell a meaningful story in the field of economics and finance.

Who should attend

This webinar is designed for participants from all areas of central banking, regulatory bodies, and finance and line ministries, who wish to gain new insights and ideas about how to bring their data to life.

Faculty

The learning initiative/event will be delivered by/ under the guidance of:

• Alexandru Monahov, Expert 
• Mikhail Oet, Associate Teaching Professor and Faculty Lead, Northeastern University
• Torsten Wezel, Economist, International Monetary Fund
• Knarik Ayvazyan, Economist, International Monetary Fund

Practical information

This webinar will be held on April 25, 13:30-15:00 CET, via Zoom. Participants will receive Zoom link one day before the webinar. Application deadline is April 23. 

Partners

This learning initiative was supported by: