DB USA's projections precisely matched the Fed’s estimates for the second year in a row
Gap between internal projections and the Fed's model outputs shrinks to 118 basis points
Human overseers are in short supply in an arena where losses can be crippling in minutes
Banks cannot blame developers or vendors for faulty machine learning models, says regulator
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…
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.
TD Bank losses on one day exceeded VAR estimate by 195%
Banks surveyed by the ECB had an average of 32 issues with their market risk models
Trim effects add €1.3 billion of RWAs in Q1
Bayesian analysis can replace forest with a single, powerful tree, writes UBS’s Giuseppe Nuti
Decades, not years, of credit losses required for accurate risk modelling, argues expert
This paper's aim is twofold: to introduce a mathematical framework that is sufficiently general and sound to cover the main areas of model risk, and to illustrate how a practitioner can identify the relevant abstract concepts and put them to work.
Although most banks are progressing rapidly towards a certain standard in MRM practices, the rate of progress is uneven and so are the ambition levels. Management Solutions provides a summarised overview of the state of MRM evolution and how banks are…
Research finds two out of three methods for checking index prices as proxies don’t properly gauge tail risk
In this paper, the author's aim is to empirically analyze the numerical quantification of model risk, yielding exact buffers in currency amounts (for a given model uncertainty).
The final quarter of 2018 saw a record number of VAR breaches at the biggest US banks
Oxford-Man Institute director on why tomorrow’s models will gracefully admit defeat
ML model outputs open to “potential bias sitting in your datasets”, says RBS model risk head
Quant grads should be taught follies of LTCM, Gaussian copula and London Whale, writes UBS’s Gordon Lee