Commentary
Most central banks reviewed risk management in past year
Other aspects evaluated varied by risk team structure and departmental staff strength
Cyber and geopolitical risks are managers’ top risks
Geopolitical risks seen rising fastest, but cyber is the biggest concern currently
Central banks keep ISO 31000 and COSO-ERM as main approaches
Principles tend to vary slightly by central banks’ risk management philosophies
Central banks typically employ detailed business continuity plans
But institutional risk appetite is less commonly included, especially in Europe
A third of central banks lack key risk indicators
Most of those with KRIs conduct monitoring and employ feedback loops
Direct system breaches are top cyber risk
Main threats vary by cyber security staffing and economic groupings
Over 60% of risk departments face staff and resource shortages
Teams that face hiring challenges generally have to make do with smaller risk departments
One-fifth of central banks lack defined risk tolerance and strategy
But majority of respondents apply risk management principles to policies and processes
Adoption of governance, risk and compliance systems still partial
Respondents mention main service providers and plans to upgrade
Decentralised risk teams less likely to have chief risk officers
CROs are also less common at Asia-Pacific and European central banks
Credit and counterparty risk gains relevance as most covered risk
But central banks’ top risks vary by geographical regions
Centralised risk teams tend to have more sub-units
Size of central banks with climate change risk unit steadies at 12%
Financial and op risk divisions maintain largest staff
Upper-middle income nations tend to have different staffing priorities
Share of economics departments with data unit rises
Web scraping and administrative data are top alternative sources for economists
Heterogeneous agents and non-linearities rare in main models
Semi-structural models continue to be dominant choice of main forecast model at central banks
Economists commonly use AI for data analysis
Lower-middle income countries, Africa and Asia-Pacific report lower use of AI
Economists least likely to research impact of AI
Inflation dynamics retains position at top of the rankings
Peer-reviewed journals still top gauge for research impact
Smaller teams more likely to consider conference presentations as assessment tool
Inflation and GDP growth forecast errors decrease further
Forecast errors used widely for key model adjustments
One in five main models has endogenous financial sector
Benchmark highlights array of methods central banks use to model financial sector, but 40% still do not model the financial side of the economy
Central banks published fewer working papers and articles in 2023
Middle income and low income central banks published less
Time series and semi-structural models widely applied
High income countries more likely to use AI than peers from other income levels
Economic growth and inflation remain most forecast indicators
But year-on-year data show rising priority for exchange rates
Policy analysis takes most of PhD economists’ time
Other tasks consume just a quarter of their official hours