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In this week's blog post, we're sharing insights on our interview with David Asermely. David is a global Model Risk Management Lead at SAS driving strategic conversations with global institutions and influencing the SAS model risk management solution roadmap. He is passionate about translating data into actionable intelligence, and he focuses on combining the best technologies and design principles to improve modelling efficiency and quality. Based on that, we invited David Asermely to talk abo

Ruben Cohen is an operational risk consultant. He has been working in the financial industry for over 17 years, with most of the last 10 in operational risk analytics at Citi.
Prior to that, Ruben spent 10 years on the faculty of Mechanical Engineering & Materials Science at Rice University in Houston, specializing in Fluid Mechanics and Thermodynamics. He holds a Ph.D. in Mechanical Engineering from M.I.T. and has subsequently obtained an M.A. in Economics from McGill University.
Ruben is based

Operational risk management is currently on the end of a major shakeup. Ever since the announcement of Basel III banks have been working within a paradigm that pushes towards either TSA or AMA approaches (standardised and advanced approaches respectively). At the end of 2015, however, the Basel Committee shocked firms by announcing that they were doing away with this, and replacing it with the SMA – a new standardized approach that would be the norm for all banks. This is having huge ramificatio

Greta Roberts, CEO, Talent Analytics, Corp.

It’s exciting to watch advances in predictive and prescriptive employee solutions. Workday recently announced the release of an application enabling employers to “identify which employee is likely to quit, and what options need to be considered to retain that person”.

Workday is not the first to announce Flight Risk Scores of current employees. Many top Talent Management solutions have made similar announcements in the past several months. It’s a step

Errors in financial models that banks use on a daily basis could lead to tremendous financial and non-financial losses. It is crucial for banks to understand how they could minimize and manage model risk effectively. In addition, the OCC and the Federal Reserve have recently released new guidelines on model risk management, which will significantly modify their existing model risk management practices.

Andrew Hrdlicka answered a series of questions written by GFMI before the Model Risk Conference

The problems with risk models, a Bank of England speech on why financial models are broken and the general evolution of risk management.

Over the last few months, risk models have come under the spotlight as a potential reason why risk management, as an entire institutional function, is failing.

In general only a handful of businesses correctly capture Operational Risk Loss Data and of those that do, only a small number of risk units in these firms are modelling their risk data in a coherent manner. After a bit of research on the internet and in various other channels, it has become relatively apparent that there isn't a comprehensive list of potential models which can be uses for understanding Operational Risk. I would have expected an analyst somewhere at some point in time to have do