8002 – The Mathematical Foundations of Risk Management

Risk Management

The Professional Risk Managers’ International Association, also known as PRMIA, is a worldwide leader in providing solutions for risk management, with over 88,000 registered members in 210 different countries. PRMIA offers all the resources and programs risk managers need to enhance their skills and knowledge, as well as have them get recognized worldwide. They offer 2 different certifications: the Professional Risk Management certification and the Associate Professional Risk Management certification.

The Professional Risk Management certification, also known as the PRM, recognizes the risk manager’s skills and knowledge as the highest standard in the field. For candidates to receive this certification, they must pass 4 exams. The focus of this article is the second exam, the Mathematical Foundations of Risk Management exam, also known by its exam code, 8002 Exam.

 

Overview of EXAM II

 

EXAM II of the PRM certification is all about the knowledge and understanding of the mathematical foundations of risk management. It is essential for the risk manager to assess risks, which can go beyond the quantitative. Despite that, these risks are immeasurable unless they are quantifiable. This exam may feel like there is a heavy usage of mathematics, but it is in fact designed to test candidates with little to no mathematical background.

 

Coverage of EXAM II

 

According to the study guide PRMIA Exam has provided for the PRM exams, EXAM II will cover 7 different topics that relate to quantitative risk management. The following chapters are:

  1. Foundations
  2. Descriptive Statistics
  3. Calculus
  4. Linear Mathematics and Matrix Algebra
  5. Probability Theory
  6. Regression Analysis
  7. Numerical Methods

 

Foundationscovers the fundamental mathematical concepts. This includes the symbols used as well as the rules of arithmetic, equations, inequalities, functions and graphs.

Descriptive Statisticscovers the commonly used statistics that summarize the historical characteristics of financial data.

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