Application of Micro Data for Systemic Risk
Assessment and Policy Formulation
Workshop on Integrated Management of MicroDatabases: Deepening Business Intelligence
within Central Banks’ Statistical System
22 June 2013
Karen Lee
Bank Negara Malaysia
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Integrated Management of Micro Databases
Porto, Portugal
22 June 2013
Outline
1. Introduction
Importance of micro data for
systemic risk assessment
2. Types and sources of
micro data
Categories of micro data
3. The Malaysian experience
Methodology for systemic risk
assessment using micro data
4. Challenges
Challenges in applying micro data
for macro risk assessment
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Integrated Management of Micro Databases
Porto, Portugal
22 June 2013
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Importance of micro data for systemic risk
assessment and policy formulation
Conduct more in-depth risk assessments
•
Micro data may reveal trends that are superficially masked at the macro level
Timely identification of risks to financial stability
Formulate targeted policy measures to address risks
•
Macroprudential policy can be implemented to address risks in specific
segments, instead of broad brush policy
Measure effectiveness of policy measure
•
•
Continuous monitoring
If necessary, new measures may need to be introduced
Examples of potential risks to financial stability
High risk appetite
To meet investors’
expectation
especially in
periods of ample
liquidity
Excessive
exposure to real
estate
Excessive credit growth
• Leverage build-up in
household sector
• Build-up of financial
imbalances
Susceptible to
property market
correction
Build up of risks in asset
market
• Exposure via direct
investment in property &
financing to property
market players
Integrated Management of Micro Databases
Porto, Portugal
22 June 2013
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Micro data – what and where?
• Central Credit Reference
Information System (CCRIS)
– Outstanding financing
– Repayment pattern
– Application status
– Demographics
Credit-related
Financial
assets /
Income data
Types and
sources of micro
data for
household sector
assessment
• Liquid financial assets (deposits, unit
Behavioural
• Qualitative characteristics
• Willingness to repay
• Behaviour towards credit
trusts, equity)
• Illiquid financial assets (endowment
policies, pension funds)
• Individual income data
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Integrated Management of Micro Databases
Porto, Portugal
22 June 2013
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Methodology
What data is needed to
conduct assessment?
• Review existing data
• Identify new data needs
Where to source data from?
• Credit registry
• Public / private databases
• Surveys
• Proxies
Identify
Source
Continuous
assessment and
monitoring of data
needs / data gaps
• Relevancy of
existing data
Assess
and
monitor
Mutually
reinforcing
Match
Aggregate
Consolidate
assessment from
various databases
• Ideally at granular
level
Bottom-up approach
• Financial stability indicators
• Demography
• Sector
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Integrated Management of Micro Databases
Porto, Portugal
22 June 2013
Systemic risk assessment and policy formulation in the
household sector – How does micro data fit in?
The Malaysian Experience: Loan-to-value ratio for house financing
Systemic risk assessment and policy formulation
Step 1: Identification
of risk
Step 2: Assessment of
risk
• Granular analysis
• Thematic
• Specific areas of concern
Step 3: Escalation &
deliberation
• Policy options & trade offs
• Compensating measures
Step 4: Execution
& communication
• Monitoring of effectiveness
• Feedback
Credit-driven speculation in
property market
Application of micro data
1. IDENTIFY
Number of outstanding housing
loans for each individual borrower
2. SOURCE
Build up /
sources of risks
Financial fragility
Central Credit Reference Information
System (CCRIS)
3. MATCH
Impact to financial stability
Link individual borrowers with all
outstanding housing loan accounts
4. AGGREGATE
Policy formulation
Policy implementation
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Sum number of borrowers by each
multiple housing loan category
5. ASSESS & MONITOR
Continuous monitoring and
assessment of new data needs
Integrated Management of Micro Databases
Porto, Portugal
22 June 2013
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Growth in number of borrowers with multiple housing loans on declining
trend since implementation of targeted macroprudential measures
Financial Stability and Payment Systems Report 2012, Bank Negara Malaysia
Financial Stability in Malaysia
Macro Prudential Seminar, Yogyakarta
26 May 2011
Challenges
Infrastructure readiness
• Institutions may be at varying stages of infrastructure development
Legal framework may be necessary to facilitate sharing of information
Buy-in of relevant stakeholders
•
•
Some agencies may be reluctant to share “sensitive” information
Unwilling to meet high investment demands
Capacity development
•
•
Technical resources - ensure data quality
Analytical skills - data mining, interpretation and analytics
Conducting data analysis is like drinking fine wine. It is important
to swirl and sniff the wine, to unpack the complex bouquet and to
appreciate the experience. Gulping the wine doesn’t work
– Daniel B. Wright (2003)
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Integrated Management of Micro Databases
Porto, Portugal
22 June 2013
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Thank You
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Integrated Management of Micro Databases
Porto, Portugal
22 June 2013
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