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PRMIA 8010 Exam Syllabus Topics:

PRMIA Operational Risk Manager (ORM) Sample Questions:

1. Which of the following statements is true
I. If no loss data is available, good quality scenarios can be used to model operational risk II. Scenario data can be mixed with observed loss data for modeling severity and frequency estimates III. Severity estimates should not be created by fitting models to scenario generated loss data points alone IV. Scenario assessments should only be used as modifiers to ILD or ELD severity models.

A) I and II
B) All statements are true
C) III and IV
D) I

2. Which of the following is not a risk faced by a bank from holding a portfolio of residential mortgages?

A) The risk that mortgage interest rates will rise in the future
B) The risk that the homeowners will not be able to pay their mortgage when they are due
C) The risk that CDSspreads on the bank's debt will rise making funding more expensive
D) The risk that the homeowners will pay the mortgage off before they are due

3. What does a middle office do for a trading desk?

A) Reconciliations
B) Operations
C) Risk analysis
D) Transaction data entry

4. CreditRisk+, the actuarial model for calculating portfolio credit risk, is based upon:

A) the log-normal distribution
B) the exponential distribution
C) the normal distribution
D) the Poisson distribution

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 Nobservations, of which K are up to T, then p = k/N

Solutions: