Violetta Damia, Vitaliana Rondonotti

1. Use of credit register data for statistical purposes:advantages and preconditions, current and potential future uses Violetta Damia, Vitaliana Rondonotti European Conference on Quality in Official Statistics Helsinki, 4-6 May 2010

2. Contents • Background • Credit register’s data: scope and coverage • Central Credit Register data: advantages and drawbacks • Preconditions and current limitations for the statistical use of Central Credit Register data • Conclusions and way forward

3. Background Increase in ESCB data needs, in particular for: • Enhanced data content(coverage, level of details) • Higher frequency and improved timeliness • Higher flexibility while maintaining: • Comprehensive, harmonised and consistent statistics • Minimumreporting burden • High quality data • Use of granular and flexible datasets maintained in micro-databases and registers, where appropriate • In particular possible use of credit registers for statistical purposes

4. Credit register’s data: scope and coverage (1/2) Credit Registers: granular databases on loan information Central Credit Registers (CCR): generally maintained by National Central Banks, collect information mainly from supervised institutions, to support: • bank supervisors forcredit riskassessment of supervised financial institutions • financial institutions for credit risk evaluationof transactions • economic analysis And, on a case by case, CCR are used for research and statistics

5. Credit register’s data: scope and coverage(2/2) Credit Registers: granular databases on loan information Private Credit Bureaus (PCB):collect information from different data sources (lenders, firms, households, etc.) to support lenders in the assessment ofcredit conditions for small and medium-size enterprises (also modelling consumer behaviours, orassessment of default probability by type of loans)

6. Central credit register’s data: advantages Advantages: • granular information – wide coverage • data updated, revised and checked on a regular basis • number of attributes of interest • possible links with other sources (identifiers) • for euro area/EU statistics, availability of CCR data in a significant number of countries (BE, DE, ES, FR, IT, AT, PT, SI, SK, BG, CZ, LT, LV, RO)

7. Central credit register’s data: drawbacks Drawbacks: • data collected mainly for supervisory purposes, therefore: • differences in coverage, content, definitions and methodologies and lack of certain breakdowns • (often high) thresholds • for statistical purposes, no direct data influence/responsibility • for euro area/EU statistics, additional lack of harmonisation cross-country and lack of CCR data in some countries • data confidentiality

8. Preconditions and current limitations for the statistical use of Central Credit Register’s data (1/2)

9. Preconditions and current limitations for the statistical use of Central Credit Register’s data (2/2)

10. Conclusions and way forward (1/2) Some examples of statistical use of Central Credit Registers’ data: • compile/check Monetary and Financial Statistics and support compilation of certain statistical breakdowns • build up and maintain list of attributes to support national and euro area sampling

11. Conclusions and way forward (2/2) For a wider statistical use: • Need to overcome the shortcomings identified in scope, coverage, definitions, reporting framework, interoperability, links with other sources • Assessment of merits and costs for statistical use • Development of coherent and integrated system(s) to create statistical databases to meet various needs ensuring coverage, punctuality and timeliness, consistency and harmonisation, reliability.