Model risk
Complex op risk models open to high error, study finds
Measuring 1-in-1,000 year loss events ‘unrealistic’, researchers say
State Street, Goldman push VAR limits the most
Average of largest trading losses-to-VAR at State Street above 90% over past 12 months
State Street, UBS and TD Group incur VAR breaches
Backtesting exceptions cause TD Group's and State Street's market risk capital charge multipliers to climb
Risk Technology Awards 2019: Making machines more helpful
Machine learning can be too efficient; now, vendors are looking for ways to make it more accurate. Clive Davidson looks at the stories behind this year’s Risk Technology Awards
Model risk management transformation
Financial institutions have been maturing their approaches to MRM and – as models become more complex and pervasive, and regulatory expectations continue to increase – leading financial institutions seek faster and further movement. Ashutosh Nawani, head…
BoE probes banks on machine learning use
Risk Live: watchdog wants to know “how prevalent” ML models are, say execs
Model risk managers: banking’s future VIPs
Risk Live: Machine learning models are changing the risk profile of banks, says UBS CRO
Deutsche’s stress-testing models are surprisingly accurate
DB USA's projections precisely matched the Fed’s estimates for the second year in a row
US banks improve stress test projections
Gap between internal projections and the Fed's model outputs shrinks to 118 basis points
Keeping the robots honest
Human overseers are in short supply in an arena where losses can be crippling in minutes
Business lines must answer for ML biases – OCC’s Dugan
Banks cannot blame developers or vendors for faulty machine learning models, says regulator
Machine learning governance
The ability of machine learning models to read great quantities of unstructured data, spot patterns and translate it into actionable information is driving a significant uptake in the technology. David Asermely, SAS MRM global lead, highlights the need…
Model risk tiering: an exploration of industry practices and principles
This paper seeks to shed light on one critical area of such frameworks: model risk tiering, or the rating of risk inherent in the use of individual models, which can benefit a firm’s resource allocation and overall risk management capabilities.
US units of BBVA, BNPP, TD Bank post VAR breaches in Q1
TD Bank losses on one day exceeded VAR estimate by 195%
EU’s model study finds problems with bank VAR methods
Banks surveyed by the ECB had an average of 32 issues with their market risk models
ECB model review continues to eat at ABN Amro’s capital
Trim effects add €1.3 billion of RWAs in Q1
Not random, and not a forest: black-box ML turns white
Bayesian analysis can replace forest with a single, powerful tree, writes UBS’s Giuseppe Nuti
Models need longer datasets to handle economic cycles – research
Decades, not years, of credit losses required for accurate risk modelling, argues expert