CWDP-304 Practice Questions

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NEW QUESTION: 1
A customer recently visited one of your retail outlets. You created an opportunity for the customer for a large purchase.
The customer is now ready to complete the purchase.
You need to create a quote from the opportunity.
Solution: Convert the Opportunity to a quote.
Does the solution meet the goal?
A. No
B. Yes
Answer: B
Explanation:
References:
https://docs.microsoft.com/en-us/dynamics365/customer-engagement/developer/convert-opportunity-quotesales-order-invoice

NEW QUESTION: 2
Patient has right sacroiliac joint dysfunction and requires a right S2-S3 paravertebral facet joint] anesthetic nerve block.
A. 0
B. 1
C. 2
D. 3
Answer: C

NEW QUESTION: 3
Which of the following steps are required for computing the total loss distribution for a bank for operational risk once individual UoM level loss distributions have been computed from the underlhying frequency and severity curves:
I. Simulate number of losses based on the frequency distribution
II. Simulate the dollar value of the losses from the severity distribution III. Simulate random number from the copula used to model dependence between the UoMs IV. Compute dependent losses from aggregate distribution curves
A. III and IV
B. All of the above
C. None of the above
D. I and II
Answer: D
Explanation:
Explanation
A recap would be in order here: calculating operational risk capital is a multi-step process.
First, we fit curves to estimate the parameters to our chosen distribution types for frequency (eg, Poisson), and severity (eg, lognormal). Note that these curves are fitted at the UoM level - which is the lowest level of granularity at which modeling is carried out. Since there are many UoMs, there are are many frequency and severity distributions. However what we are interested in is the loss distribution for the entire bank from which the 99.9th percentile loss can be calculated. From the multiple frequency and severity distributions we have calculated, this becomes a two step process:
- Step 1: Calculate the aggregate loss distribution for each UoM. Each loss distribution is based upon and underlying frequency and severity distribution.
- Step 2: Combine the multiple loss distributions after considering the dependence between the different UoMs. The 'dependence' recognizes that the various UoMs are not completely independent, ie the loss distributions are not additive, and that there is a sort of diversification benefit in the sense that not all types of losses can occur at once and the joint probabilities of the different losses make the sum less than the sum of the parts.
Step 1 requires simulating a number, say n, of the number of losses that occur in a given year from a frequency distribution. Then n losses are picked from the severity distribution, and the total loss for the year is a summation of these losses. This becomes one data point. This process of simulating the number of losses and then identifying that number of losses is carried out a large number of times to get the aggregate loss distribution for a UoM.
Step 2 requires taking the different loss distributions from Step 1 and combining them considering the dependence between the events. The correlations between the losses are described by a 'copula', and combined together mathematically to get a single loss distribution for the entire bank. This allows the 99.9th percentile loss to be calculated.