Modelling
The great migration: CCPs ponder life after Span
As CME moves to a value-at-risk methodology, CCPs that license its model look on nervously
Q&A: CFTC’s Behnam on tackling market risk in climate change
Commissioner wants to see new derivatives products to help mitigate climate threat
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
Resampling ‘slashes’ credit risk VAR underestimates
Academics claim Vasicek model’s underestimation tendency can be slashed to near-zero
How AI could tear up risk modelling canon
BlackRock, MSCI, LFIS among firms looking to replace traditional, linear risk models
A tech-driven transformation
A panel of experts explores how greater collaboration between risk and finance teams can garner significant benefits and add value, how technological innovation is making the regulatory landscape more complicated to navigate and produce transformative…
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
ABA scenario analysis project could aid CCAR comparability
Scheme to agree on common risk drivers could help Fed benchmark risk exposures, says JP op risk expert
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
Fire sales turn a crash into a crisis, simulation shows
‘More realistic’ core-periphery model leads to wipeout of network if several nodal banks default
Libor replacement: a modelling framework for in-arrears term rates
Andrei Lyashenko and Fabio Mercurio expand rates modelling to the post-Libor world
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…