1. Microdata in ESCB banking statistics
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Ioannis Ganoulis
Statistics Development & Coordination
European Central Bank, DG-S
Microdata in ESCB banking statistics
Round table discussion – exchange and use of microdata in foreign trade, migration and banking statistics
World Statistics Day Budapest, 21 October 2015
Communicating the meaning of indicators to decision makers, media and general public

2. Micro- or granular data?
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What is granular data?
Micro- or granular data?
Micro data refers to the individual statistical or reporting unit
Granular data (e.g. information contract by contract, or counterparty by counterparty)
ESCB’s focus lies lately on granular data
Granular data closer to operations
Operational
system
Main statistical
aggregates
Microdata in ESCB banking statistics
Communicating the meaning of indicators to decision makers, media and general public

3. Pros and cons of granular data (and for whom)
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What is microdata?
Pros and cons of granular data (and for whom)
Cons
detailed knowledge of various instruments and contracts is needed (producers)
data at various levels of granularity could exploit very different properties (producers)
confidentiality issues (producers, reporting agents)
in an ESCB content: could result in additional burden for NCBs (producers)
Pros
Potentially very rich information source (users, producers)
distributional information
other microfoundations of aggregates
Could significantly decrease the reporting burden (producers, reporting agents)
Allows for producing tailor-made statistics (users, producers)
Integrated data models could help in overcoming the silo-mentality (users, producers)
Microdata in ESCB banking statistics
Communicating the meaning of indicators to decision makers, media and general public

4. Examples of ESCB Projects relating to granular data
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ESCB activites relating to granular data collection
Examples of ESCB Projects relating to granular data
Centralised Securities Database (CSDB)
Securities Holdings Statistics (SHS)
Analytical Credit dataset (AnaCredit)
Supporting reporting agents in the production of statistics
Banks’ Integrated Reporting Dictionary (BIRD) – not reporting!
Microdata in ESCB banking statistics
Communicating the meaning of indicators to decision makers, media and general public

5. Reporting data warehouse
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Innovation on the inputs side
The Role of BIRD
Banks
NCB/NSAs
ECB
(Operational System)
Primary Data
Reporting data warehouse
Primary Reports (ERF)
Secondary Reports
Transformations by banks
Transformations by banks
Transformations by NCBs/ NSAs
Transformations defined by banks and authorities in close collaboration
Transformations defined by banks
BIRD
Microdata in ESCB banking statistics

6. ECB-UNRESTRICTED
Discussion points
The move towards more granular data brings potentially benefits for reporting agents, producers and users, but also significant challenges
Are Central Banks (and Statistical Institutes) ready to move to the industrial scale production that is needed?
What kind of competences, IT infrastructure, international standards and legal framework will be needed in the future to deal with large scale, detailed information that the move to granular data is bringing?
Microdata in ESCB banking statistics
Communicating the meaning of indicators to decision makers, media and general public

7. Background ECB-UNRESTRICTED
Microdata in ESCB banking statistics
Communicating the meaning of indicators to decision makers, media and general public

8. Centralised Securities Database (CSDB)
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Centralised Securities Database (CSDB)
Reference information on individual securities relevant for ESCB purposes
Up-to-date, complete, accurate, consistent security-by-security information
Allows compilers to base their interactions with reporting agents on the most granular level in the field of securities statistics
Multi-purpose system supporting the production of various central banking statistics (insurance companies, investment funds, financial vehicle corporations, securities issuance)
The ECB is preparing the CSDB to handle the Legal Entity Identifier (LEI).
Microdata in ESCB banking statistics

9. Securities Holdings Statistics (SHS)
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Securities Holdings Statistics (SHS)
Statistical dataset on securities holdings, developed since 2009
Collection of security-by-security data either directly or via custodian reporting
Interoperability with the CSDB
Two main components for different analytical purposes
Sectoral data
Holdings of euro area residents broken down by the country and sector of the holder (collected via direct reporting)
Securities issued by euro area residents held by non-euro area residents (collected with the help of custodians)
Reporting Banking Groups (RBGs) data (direct reporting)
Microdata in ESCB banking statistics
Communicating the meaning of indicators to decision makers, media and general public

10. ECB-UNRESTRICTED
Analytical credit datasets (AnaCredit) as an important building block of an integrated approach
AnaCredit will cover the need for granular data on credit and credit risk (mainly loans), whose current availability, e.g. from Central Credit Registers, is rather incomplete and heterogeneous across EU countries
It will bring increased coverage, and especially harmonisation in underlying concepts and definitions  standardisation
Multipurpose; should support a wide range of users
Monetary policy analysis and operations
Risk control and collateral management
Financial stability
Micro/macro supervision
Economic analysis and research
Statistical production
Microdata in ESCB banking statistics

11. Banks’ Integrated Reporting Dictionary (BIRD)
The BIRD proposes a standardised model for organising the banks’ internal data warehouses in an integrated way
It also covers transformations to obtain reports that banks need to transmit
The BIRD consists of documentation, it is not an IT tool
Top FAQs
The application of the BIRD by the banks is strictly voluntary
Responsibility for the correctness of the data remains with the banks
The BIRD implies no additional reporting requirements
Microdata in ESCB banking statistics