Modelling
One size does not fit all – Adapting to meet investment goals
Guillaume Arnaud, global head of quantitative investment strategies (QIS), and Sandrine Ungari, head of cross-asset quantitative research at Societe Generale, explore the benefits of QIS for investors, why flexibility is crucial for investors to meet…
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
A helping hand – Addressing industry concerns
The Basel Committee on Banking Supervision’s final revisions to the FRTB guidelines aim to address industry concerns around complexity and capital implications. A forum of industry leaders discusses whether the changes have been effective and how banks…
Turning the IMA into a competitive advantage
Following the clarification of the FRTB rules in January 2019, financial institutions are now working towards a 2022 implementation deadline, finalising how their trading books will operate under this demanding regulation. Eoin Ó Ceallacháin, head of…
A statistical technique to enhance application scorecard monitoring
Application scoring plays a critical role in determining the future quality of a lender’s book. It is therefore important to monitor the performance of an application scorecard to ensure it performs as expected.
Libor replacement: a modelling framework for in-arrears term rates
Andrei Lyashenko and Fabio Mercurio expand rates modelling to the post-Libor world
Getting risk models runway ready
Banks struggling with internal model requirements may soon opt for off-the-rack rather than bespoke
Cleaning noisy data ‘almost 70%’ of machine learning labour
Quants flag signal-to-noise ratio as key to reducing overfitting risk
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…
New applications in Asia’s financial crime analytics
Financial crime is a fast-growing problem for Asia‑Pacific financial services firms. Working with outmoded systems and patched-up processes to detect, monitor and eliminate potential threats, banks are spending millions on sophisticated new solutions to…