Pegasystems PEGACPDS88V1 Exam - Topic 7 Question 37 Discussion

Actual exam question for Pegasystems's PEGACPDS88V1 exam

Question #: 37
Topic #: 7

U+ Insurance uses Pega Process AI and wants straight-through processing of claims with a low fraud risk. As a data scientist, you create a prediction that calculates the probability that a claim is fraudulent.

What type of prediction do you create to meet this requirement?

AA case management prediction.

BA text analytics prediction.

CA Customer Decision Hub prediction.

DA fraud detection prediction

Show Suggested Answer

Suggested Answer: A

to create a prediction that calculates the probability that a claim is fraudulent, you need to createa case management prediction. This type of prediction allows you to use predictive models built on external platforms such as H2O.ai and apply them to case types in Pega Process AI. You can then use the prediction outcome in a decision step to route claims based on their fraud risk.

https://academy.pega.com/challenge/creating-fraud-prediction/v3

by Vallie at Jul 07, 2025, 07:59 AM

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Alyce

2 months ago

Just to clarify, fraud detection predictions focus on identifying fraudulent claims.

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Amber

2 months ago

Really? I’m surprised that’s the best option.

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Hector

3 months ago

No way, it has to be a fraud detection prediction.

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Paris

3 months ago

I think a Customer Decision Hub prediction could work too.

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Renea

3 months ago

Definitely a fraud detection prediction!

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Charisse

3 months ago

I’m leaning towards A or D, but I’m not confident. I just remember that fraud detection is crucial for claims processing.

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Jennie

4 months ago

I feel like I’ve seen similar questions before, and they often focus on case management. But this seems more specific to fraud detection.

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Ling

4 months ago

I'm not entirely sure, but I remember something about Customer Decision Hub predictions being used for risk assessments. Could that be C?

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Rachael

4 months ago

I think the answer might be D, a fraud detection prediction, since it directly relates to identifying fraudulent claims.

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Celia

4 months ago

I'm a little confused. Is a text analytics prediction the same as a fraud detection prediction? Or is a Customer Decision Hub prediction the way to go here? I'll need to review the differences between these options.

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Elbert

4 months ago

Okay, I've got this. The question is asking for a prediction to detect fraud, so the correct answer has to be a fraud detection prediction. That's the type of model I would build to meet the requirement of straight-through processing with low fraud risk.

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Kallie

5 months ago

Hmm, I'm a bit unsure about this one. Is a fraud detection prediction the same as a Customer Decision Hub prediction? I'll need to think this through carefully.

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Fredric

5 months ago

I think this is a straightforward question. The requirement is to create a prediction that calculates the probability of a claim being fraudulent, so the answer is clearly a fraud detection prediction.

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Ma

6 months ago

Haha, a text analytics prediction? That's like trying to solve a math problem with a dictionary. Nah, fraud detection all the way, baby!

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Stefania

7 months ago

I'm not sure, but maybe a Customer Decision Hub prediction could also help with straight-through processing.

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Belen

7 months ago

For straight-through processing with low fraud risk, a fraud detection prediction is the clear choice. Gotta stay one step ahead of those fraud artists.

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