Unlocking the potential of data through data science: A view from central banks

Data science offers significant potential for leveraging traditional and emerging data sources, improving statistical processes and enabling complex data analysis in central banking. It also facilitates secure sharing of granular datasets while protecting sensitive information. There are various challenges, however, including the need for robust IT infrastructure, organisational barriers and limited quality of secondary sources, which constrain their use for official purposes. Fortunately, central banks are well equipped to address these issues, not least because of their expertise as both data producers and users. Looking ahead, enhancing data management, promoting interoperability, investing in modern data platforms and fostering structured exchanges of experiences across stakeholders can be essential to unlock the full potential of data in today’s modern societies and effectively support central banks’ public mandates. This paper examines how central banks can harness data science to improve data management, overcome organisational and technical challenges, and implement strategies that unlock the full potential of data for policy and operational purposes. This article is also included in The Business & Management Collection which can be accessed at https://hstalks.com/business/.