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PRMIA 8008 Exam Syllabus Topics:

PRMIA PRM Certification - Exam III: Risk Management Frameworks, Operational Risk, Credit Risk, Counterparty Risk, Market Risk, ALM, FTP - 2015 Edition Sample Questions:

Question 1

A bank extends a loan of $1m to a home buyer to buy a house currently worth $1.5m, with the house serving as the collateral. The volatility of returns (assumed normally distributed) on house prices in that neighborhood is assessed at 10% annually. The expected probability of default of the home buyer is 5%.
What is the probability that the bank will recover less than the principal advanced on this loan; assuming the probability of the home buyer's default is independent of the value of the house?

A. More than 1%
B. More than 5%
C. 0
D. Less than 1%

Question 2

Which of the following cannot be used as an internal credit rating model to assess an individual borrower:

A. Logit model
B. Distance to default model
C. Altman's Z-score
D. Probit model

Question 3

If a borrower has a default probability of 12% over one year, what is the probability of default over a month?

A. 12.00%
B. 2.00%
C. 1.00%
D. 1.06%

Question 4

Which of the following statements are true?
I. Retail Risk Based Pricing involves using borrower specific data to arrive at both credit adjudication and pricing decisions II. An integrated 'Risk Information Management Environment' includes two elements - people and processes III. A Logical Data Model (LDM) lays down the relationships between data elements that an organization stores IV. Reference Data and Metadata refer to the same thing

A. I, II and III
B. II and IV
C. All of the above
D. I and III

Question 5

When fitting a distribution in excess of a threshold as part of the body-tail distribution method described by the equation below, how is the parameter 'p' calculated.

Here, F(x) is the severity distribution. F(Tail) and F(Body) are the parametric distributions selected for the tail and the body, and T is the threshold in excess of which the tail is considered to begin.

A. p is a function of the reporting threshold and determined by the log-likelihood functional
B. If there are K observations up to the tail threshold, then p = k*n
C. p is a parameter estimated using either the sum of least squares or maximum likelihood estimation
D. If there are N observations, of which K are up to T, then p = k/N

Solutions: