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Violetta Damia

28 April 2017
In May 2016 the Governing Council adopted the AnaCredit Regulation ECB/2016/13) providing the legal basis for the European System of Central Banks (ESCB) to collect granular information on loans from banks to corporates and other legal persons based on a core set of harmonised concepts and definitions. Starting with reference data from September 2018, credit institutions in the euro area, and possibly elsewhere in the EU, will report to the ECB via the national central banks (NCBs) individual credit exposures falling within the reporting scope. The reporting framework is the outcome of in-depth discussions within the ESCB involving several rounds of consultations with users, the industry and other stakeholders. As set out in the Regulation, AnaCredit will, already in Stage 1, significantly enhance the value for analysis on credit and credit risk in the euro area by providing detailed, timely and harmonised information on individual exposures to legal entities as counterparts. The new data will be useful for several key tasks of the ESCB for a better analysis of credit distribution to the economy, e.g. for monetary policy analysis and operation (risk and collateral management), financial stability, economic research and statistics. The scope of the project might be further expanded in future stages to cover additional lenders, borrowers and instruments. The purpose of this paper is to reflect and illustrate the methodological work and process leading to the definition of the AnaCredit requirements that were eventually included in the Regulation.
JEL Code
E58 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Central Banks and Their Policies
G21 : Financial Economics→Financial Institutions and Services→Banks, Depository Institutions, Micro Finance Institutions, Mortgages
E51 : Macroeconomics and Monetary Economics→Monetary Policy, Central Banking, and the Supply of Money and Credit→Money Supply, Credit, Money Multipliers
C81 : Mathematical and Quantitative Methods→Data Collection and Data Estimation Methodology, Computer Programs→Methodology for Collecting, Estimating, and Organizing Microeconomic Data, Data Access
E44 : Macroeconomics and Monetary Economics→Money and Interest Rates→Financial Markets and the Macroeconomy
17 November 2006
Quality is a subjective notion and encompasses all aspects of how well a product meets users’ needs. It is inherently a multi-faceted concept that cannot be easily defined; any chosen definition is likely to change over time as new aspects gain importance following the evolving users’ needs. The purpose of this paper is threefold; (1) to present a number of quantitative quality indicators, (2) to apply them to measure the quality of balance of payments (b.o.p.) data at the euro area level, and (3) to identify various aspects of data quality that may be enhanced, together with their interrelations with other quality dimensions. The indicators used are compatible with the IMF Data Quality Assessment Framework (DQAF), as defined for b.o.p. statistics, focusing mainly on revisions and consistency. The results obtained from such quantitative indicators may help compilers to set priorities in order to improve the quality of the euro area data still further in dimensions such as accuracy, reliability and serviceability. Additionally, this assessment may help users to understand better the quality of the data, to anticipate the possible size and direction of the forthcoming revisions, and to evaluate the impact of using different datasets in their analysis.