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Enterprise Risk Management

 

"A Simplified Approach to Quantify Enterprise Risk" is the first in the Diamond Series of technical papers that focus on Enterprise Business Continuity.

 

Please e-mail your request for a free copy to hanwacker@thelshgroup.com, include your name, company, address, and phone number.

 

                         

             A Simplified Approach to Quantify Enterprise Risk

 

                 Written by L. S. Hanwacker, M.S.C.S., M.B.A.

                 October  2009

 

Enterprise Risk Management

Understanding and managing operational risks are essential to the future survival and prosperity of an enterprise. With the regulatory spotlight on operational risks, there has been ever-increasing attention devoted to the quantification of these risks. There is a wide array of statistical methods for measuring, modeling, and monitoring operational risk. Determining how all these statistical tools relate to one another and which to use is the challenge.  Unless, a risk manager is proficient at applying the myriad of statistical methodologies to assess operational risks, the task can be daunting. This presentation utilizes an Enterprise Risk Management (ERM) methodology that is directed at the time-starved executive or manager who must quantify potential risks and other business impacts, and then set appropriate budgets aligned with strategic and business continuity plans at the enterprise level.

 

Benefits

1.      How to win at creating an overall enterprise risk management methodology that works for your enterprise.

2.      How to quantify potential risks and other business impacts for ERM by applying a simplified statistical approach using key organizational input(s).

3.      How to get the support of the key organizations to make well-informed decisions for the development of a formal ERM strategy and plan.

 

Specifically Addresses:

  • Probability
  • Frequency & Subjectivve Probability
  • Covariance and Correlation
  • Measures of Variability
  • Business Risks
  • Statistical Testing
  • Probability Models