"Well presented and interesting sessions. Excellent introductions to operational risk management."
"The course if full of useful and up to date information for people new to operational risk."
• Framework characteristics
• Risk appetite definition
• Monitoring risk & control
• Risk & control assessment
• Key risk indicators
• Loss causal analysis
• Risk management standards
• Mitigation techniques
• Differing modelling approaches
• Model parameters & usage issues
• Lognormal distribution curve features
• Statistical modelling terminology
• Model construction from key risks
• Stress testing
• Motivating business units
• Meeting regulatory requirements
Fundamentals of Operational Risk
in Financial Services
14 July 2015 - Central London
This workshop is designed as an introductory or refresher course on current operational risk strategy and techniques being used across the financial services sector.
It will explore a wide range of methodologies and approaches being used to manage, control and mitigate this diverse group of risks. In just one day:
Now in their 10th year, over 1000 delegates have benefited from these two highly practical operational risk introductory / refresher workshops.
Whilst separately bookable, most delegates attend both workshops taking advantage of substantial savings available.
Unlike many other more theoretical events lead by advisors, these workshops will be led by Andrew Brand current Head of Operational Risk at Close Brothers.
Therefore, you can be assured his perspective and style of delivery will be entirely practical backed up by recent real-life experiences.
A Practical Introduction to
Operational Risk Modelling
in Financial Services
15 July 2015 - Central London
View the Operational Risk Modelling Course agenda.
This workshop will provide a general introduction to the issues and methodologies surrounding the question of operational risk quantification and modelling. It is not intended for statisticians or quantitative analysts.
It will examine the methods and terminology used in modelling risk, using scenario modelling and stress testing as an example of the application of the techniques.
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