2016/11/11

The Central Banking Big Data Focus Report is a joint initiative of the Central Banking Journal and BearingPoint. The report builds upon the results of the recent IFC survey and takes a closer look at how central banks actually handle the challenge of data collection and analytics with regard to technical platforms and standards, resources and data governance.

As first initiative, Central Banking convened a panel of experts to discuss the big questions about big data, how and where it can add value to central banking in the near term, and balancing the pros against the cons.

The Central Banking Big Data Focus Report investigates the concrete action plans of central banks regarding data management challenges in light of FinTech/RegTech developments and the objective of transparent and effective risk-based supervision but also plans for central banks statistics for “going beyond the aggregates” especially for the micro-granular data handling. Finally, central banks are evaluated how the BCBS 239 principle in an adapted version would apply to them today.

The focus report will draw on views from central bankers, industry experts, academics and observers to look at:

  • Financial stability and supervisory applications
  • Direct uses in economics and modelling
  • Who should ‘own’ big data?
  • Resourcing and budgets
  • Future developments
  • Operational challenges – gathering, structuring, storing and processing data

The Central Banking Big Data Focus Report aims at giving a clear picture of where central banks stand today with supervisory data management and defining fields of action.

The report sets out the results of a survey of how central banks view big data and data governance in their institutions. The survey was conducted by Central Banking Publications, in association with BearingPoint, in August and September 2016. The work has only been possible with the support and cooperation of the central bankers who agreed to take part. They did so on the condition that neither their names nor those of their central banks would be mentioned in the report.

Summary of key findings

  • Central banks have an active interest in big data. This is manifested in improving processing technology, adapting institutional strategies and increasing staff awareness of the area.
  • Central banks typically see big data as unstructured data that is sourced externally, though this view is not universally held.
  • Overwhelmingly, central banks develop their own data platforms to handle regulatory data collection, a role that has taken on greater significance since the financial crisis as central banks have expanded their involvement in financial stability.
  • Big data is predominantly regarded as useful for research, but significant minorities see immediate involvement in policy-making, or scope for this.
  • Lack of support from policy-makers is seen as the most significant challenge to increase use of big data.
  • Central banks do not in the main have a dedicated budget for the handling of data (including big data), though many are seeking one.
  • A little over 80% of respondents said they do not have any intra-departmental or divisional bodies dedicated to big data.
  • More broadly, central bankers have concerns over the arrangements in place for managing data in their institutions. Many are looking to improve data governance.
  • Over three-quarters of respondents indicated they had a shared internal platform, typically in the form of reporting frameworks and data warehouses.
  • Central banks generally source their own big data sets, though a significant minority increasingly look elsewhere for these. Overwhelmingly, they process these themselves and there is no indication of a desire for this to change.
  • Monetary policy is seen as standing to benefit most from big data, though it is expected to have a significant impact on macro-prudential policy as well.
  • Support from the executive-level and policy-makers divided respondents: 35% saw it as top priority for investment within the central bank, 38% saw it as the lowest.
  • Central banks have developed their own data platforms to deal with regulatory data analytics, often used in conjunction with other options. Excel remains popular.
  • Central bankers broadly welcome the idea of self-assessment of data management using an adapted version of the Basel Committee’s BCBS 239 principles for supervisory data aggregation.
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