Jean-Marc IsraëlHead of DivisionMonetary and Financial Statistics
AnaCredit and RIAD
BIS-BI-ECB Regional Seminar 2017
Bali, Indonesia20–21 March 2017
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2 Register of Institutions and Affiliates Database (RIAD)
Analytical Credit Dataset (AnaCredit)
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Phase B – May 2010Sovereign debt crisis and again banking crisis
Financial crisis – new tasks and new data needs
Phase A - post Lehman Brothers – Sept 2008banks’ rescue, government guarantees
EU Financial SupervisionESAs/ESRB - Nov 2010
Phase C - May 2012Banking Union announced
ECB’s banking supervision – Nov 2014
2008 2009 2010 2011 2012 2013 2014
Single Resolution Mechanism – Jan 2015
2015
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How exposed are euro area investors?
Who holds GR, IE, PT government debt?
How big are EU financial inter-
linkages?
How healthy are euro area banks?
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IntegrationLong-term harmonisation
managing different areas of statistical and supervision information as parts of a single system
of practices, methodologies and processes currently followed for data production
The ESCB response: holistic approach to data reporting
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AnaCredit – granular data on credit to support ESCB tasks
AnaCredit will cover the need for granular data on credit and credit risk, 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
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AnaCredit - multiple ESCB tasks
Supporting 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
… for multiple analyses and purposes• Access to credit • Credit supply constraints• Financial constraints• Analyses of collateral issues• Stress-tests• Off-site and on-site supervision• Exposures to sectoral risks• Credit risk analysis• Risk control measures• Cross-border credit risk• Transmission channels of MP• New statistics
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ECB’s monetary policy requires a vast amount of data
Market policy decisions affect economic activity and inflation through several
channels the ‘transmission mechanism’ of monetary policy
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AnaCredit uses – Example of Monetary policy
• impact depends on the nature of the business and the size of the enterprise
• currently, only broad quantification of the effects of market policy available
AnaCredit will help identify and asses developments in credit demand and supply
AnaCredit data is crucial to assess the extent to which b/s conditions of banks or debtor are influencing credit expansion
Help assess implication for price stability and identify adequate policy actions
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Pros of collecting granular information
Aggregated data
• individual institutions combine their positions and transactions into a limited set of statistics/indicators
• well established, broad coverage, relatively limited costs of reporting
• long lead time (years) to address ever changing policy needs
Surveys
• limited coverage, low comparability
• often run ad hoc to address urgent needs,no/limited time series
• expensive, for both reporting agents and central banks
Granular data
• instrument-by-instrument and counterparty-by-counterparty
• more informative: more sophisticated analysis, address heterogeneity
• flexible: meet ever-changing user needs in a timely manner
• cost-effective: high set-up costs more than offset by running savings in the medium-term, also for banks!
Aggregated data can be derived from granular data
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• Currently: exchange of data under a Memorandum of Understanding (MoU), at a borrower level, where indebtedness is above €25,000
Purpose: allow reporting institutions to have a wider picture of indebtedness of their current and potential borrowers, and also for supervisory purposes
• Task Force on Analytical Credit Datasets, incl. National Central Banks with no granular credit data
Work re. harmonisation of concepts, definitions and identifiers
88 attributes standardised
Establish a long term framework
legal: solution for data sharing / access rights / confidentiality
organisational: IT, incl. cost aspects, and
procedural issues
Aim: to collect granular credit and credit risk data to be shared, incl.attributes on lenders, borrowers, credits and related methodological aspects
AnaCredit: why to move towards more granular data?
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• AnaCredit uses – Towards better understanding of the EU banking sector
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Non-Performing Exposure ratio is particularly high (10%) in the case of non-financial corporations
NPE ratios vary depending on the size of the banks
Source: EBA 2015 EU-wide Transparency Exercise Report
… data show that smaller banks struggle with higher levels of non-performing loans, 18% of total loans, compared to 9% of total loans in medium banks and 4% of total loans in large banks
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Covering the whole range of enterprises (thanks to the threshold of € 25,000),
Leveraging on granular data typically produced by banks for their internal risk management processes
AnaCredit uses – More data on SMEs
AnaCredit will close existing data gaps on SMEs
• Enable identification and assessment of developments in credit demand and credit supply across all SMEs in the euro area in a timely manner
• Enhance monitoring of credit developments at the borrower-lender level
• Help assess the credit risk that banks associate with firms
• Assist in assessing the effectiveness of measures to improve SMEs access to credit (Do capital reliefs for banks make it easier for SMEs to get credit?)
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• Multipurpose• Monetary policy, macroprudential supervision,
risk management, research, and statistics Purpose
• ECB regulation• ECB and participating countries• NCBs to collect information from Reporting agents• Shared platform – state-of-the-art IT solution
Sourcing / Governance
• Granular information (individual, micro)• Credit and credit risk data• Harmonised concepts and definitions
Content
• Euro area countries• Other EU countries also invited to participate
Participants
Analytical Credit Dataset - AnaCredit
Important building block of an integrated approach
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Overall benefits
– Cross-country harmonised information on credit instruments/attributes
– Enhancement of the credit institutions' assessment on the creditworthiness,
in particular of cross-border potential borrowers, also via ‘feedback loops’
– Overall minimisation of reporting burden (after set-up)
use of granular credit and credit risk information to enhance existing statistics or
produce new ones
stability of requirements over time, notably avoid running ad hoc surveys
AnaCredit – benefits & costs for NCBs & reporting agents
Cost considerations
• High investment for both NCBs and reporting agents, mainly due to accounting and
risk-based data, high volumes and required data quality management
• Medium to neutral running costs, thanks to e.g. less ad hoc requests,
possible discontinuation, in part or in full, of existing aggregated reporting
• Net benefits reached when AnaCredit allows discontinuing existing CCRs
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External use of AnaCredit
• The ECB will not offer credit scorings regarding e.g. individual SMEs
• In general, no granular (loan-/borrower-/lender level) information will be disclosed
(whether anonymised, or not)
• The ECB will not distort competition in the market of credit information
• AnaCredit will set standards on a number of important variables/dimensions
market-led initiatives could build upon these
• Methodological support could be provided to such initiatives
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Develop a shared ‘platform’ to
– serve multiple purposes with core set of data; according to harmonised concepts and definitions
– pull, store, process and disseminate shared analytical credit data on an EU-wide scale, protecting confidentiality as necessary
Allowing the
– availability of comparable key granular credit and credit risk data to a wide range of users for policy-relevant and analytical purposes
– set-up and maintenance of differentiated levels of access to data across the ESCB, depending on recognised uses
– connection with other ESCB applications (Business register; data on Securities) as well as serving Single Supervisory Mechanism, e.g. to credit exposures
AnaCredit – New IT application
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Eurosystem supports banks in the implementation of AnaCredit
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Preparing for implementation of AnaCredit
Cooperation with the banking industry within
Banks’ Integrated Reporting Dictionary (BIRD)
BIRD provides a representation of AnaCredit as set in the Regulation from the business point of view
Commercial banks participate on a voluntary basis
Cooperation via BIRD
To clarify AnaCredit requirements via documentation
To provide additional background and guidance
Concrete cases/examples
Manual
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The availability of granular credit and credit risk data is very important
for the post-crisis central banks’ policy making
Aggregate/survey data with insufficient accuracy and breakdowns;
a key issue is to allow rebuilding aggregates ex post!
Central bank’s non-standard monetary policy measures and the close link
between monetary and macroprudential policies increase the importance
of such data
• Conclusions (1/2)
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Setting-up granular data sources is costly;
but allows to drill-down from aggregates to identify distress in markets or
institutions, and better analyse developments
Accurately signal problems in the monetary policy transmission channel
In the case of SMEs, granular data on credit will facilitate evaluation of
financing conditions and assist policy-making
Data re-used for different purposes, including feedback loops to banks
• Conclusions (2/2)
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Contents
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2 Register of Institutions and Affiliates Database (RIAD)
Analytical Credit Dataset (AnaCredit)
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A register is key to identify
the reporting population(s) and stratify it/them
… and classify counterparts (by respondents)
(financial) groups structures
and its value added is even greater if it becomes multi-purposes, e.g.
• ‘Close links’ for monetary policy operations
• Banking and Insurance group structures for financial stability analysis
• Identification of Payment service institutions, and
• Supporting the ECB Banking Supervision
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Register of Institutions and Affiliates Database (RIAD)
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The ‘Register of Institutions and Affiliates Database‘ (RIAD) is
operated by ECB DG-Statistics and accessible to all ESCB members
designed to hold reference data of (financial) organisational units
ensuring that information on statistical reporting population is complete,
timely, accurate, and homogenously defined
The current system went live in May 2013 and serves business needs
• Statistics
• Market operations
• Financial stability
• Payment systems oversight, and
• Microprudential supervision
RIAD as reference dataset for institutions
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Currently RIAD is used to maintain four lists of financial institutions (https://www.ecb.europa.eu/stats/money/mfi/html/index.en.html)
− 9,000 Monetary Financial Institutions MFIsCredit Institutions and Money Market Funds
− 55,000 Investment Funds IFs
– 3,000 Financial Vehicle Corporations FVCs
– 3, 500 Insurance Corporations ICs
– 7,000 Payments Statistics Relevant Institutions PSRIs
RIAD management and service
RIAD provides simple lists management
And, far beyond, also offers all functions of an extended business register
RIAD will support the AnaCredit dataset in providing relevant information
on lenders and all their counterparts, borrowers or guarantors
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Comprehensive data model, incl. reference data on units plus relationships among them
Strict separation of the transactional and reporting aspect
Multiple source management
Historisation of data
Elaborate access management
• incl. the distinction of special roles and different levels of confidentiality
A functionality added (for SSM) is on handling different types of reporting
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RIAD Main features
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RIAD Main features: main stakeholders
Other initiatives Other initiatives
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RIAD allows processing of attributes describing relationships between units
which are the necessary building blocks to construct group structures
Operationally this is achieved via a ‘bottom-up approach’,
i.e. via individually loading the known / necessary members (‘nodes’) and
their ownership relationships (‘edges’) to construct a group (‘graph’)
In the medium-term it is expected to receive the underlying relationship
information from various sources, e.g. from
Statistics departments on institutional units
Supervisory authorities on supervised entities
Market operations departments on various relationships, or
Market and commercial sources
RIAD – Modelling of group structures
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Currently RIAD is generating two types of groups on basis of the available
ownership/control information
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RIAD – Group views
• Type “A” - based on “control”
• Type “B” - based on “pure ownership” (incl. 50% and less)
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RIAD – Lessons learned
According to experience gained, the challenge is to
Offer a model with a maximum of (technical) flexibility in mapping real phenomena to formal concepts
Organise an adequate governance to maintain and update the dataset servicing various user needs, avoiding inconsistencies and conflicts
Satisfy different views on group structures simultaneously
Identify and classify counterparties, which implies to
- monitor any corporate actions within the reporting population
- navigate through the sample over time, and
- synchronise publication of the authoritative lists
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Comprehensive data model, incl. reference data on units plus relationships among them
A. Identification – such as identifiers, address, etc.
B. Stratification – such as industrial activity, geographical allocation, etc.
C. Demographic developments – such as birth/closure date, split, merger, etc.
D. Relationships between units – such as ownership, control, management, etc.
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• Relationships in the data model
D. Relationship variables between units
1. Organisational relationships within an enterprise
Relationship between the legal unit and the enterprise that it operates.
2. Relationships between legal units forming an enterprise group
Link based on the concept of 'control'
Link based on the concept of 'capital share', 'voting rights'
3.Other relationships
Link between the 'originator' and 'FVC'
Link between the 'management company' of 'FVC / Investment Fund'
Link between the 'non-resident branch' and 'headquarter'
Link between the 'sub-fund' and 'umbrella fund'
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• RIAD High level architecture
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RIAD main features - System
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Thank you!
Questions?
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Questions?
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Credit Reporting Systems in Europe (indicative list)
Source: European Credit Research Institute
RESERVE: Some granular information on credit is already available