Pegasystems PEGACPDS88V1 Exam - Topic 1 Question 8 Discussion

Actual exam question for Pegasystems's PEGACPDS88V1 exam

Question #: 8
Topic #: 1

U+ Bank introduces a new credit card that has no historical customer behavior dat

a. U+ Bank wants to offer this credit card on the personalized web portal. Given the scenario, which rule type must you use?

ADecision table

BWhen rule

CAdaptive model

DPega machine learning model

Show Suggested Answer

Suggested Answer: C

Given the scenario where U+ Bank introduces a new credit card that has no historical customer behavior data and wants to offer this credit card on the personalized web portal, you must use anadaptive model.

by Kati at Apr 13, 2024, 05:54 PM

Limited Time Offer

25%

Off

Get Premium PEGACPDS88V1 Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

Submit Cancel

Edda

3 months ago

Really? I'm surprised they’d launch without any data insights.

upvoted 0 times

...

Brandee

3 months ago

Definitely a decision table, no doubt about it.

upvoted 0 times

...

Vilma

3 months ago

Wait, no historical data? That's risky!

upvoted 0 times

...

Ira

4 months ago

I disagree, I think an adaptive model fits better here.

upvoted 0 times

...

Maryann

4 months ago

Sounds like a decision table is the way to go!

upvoted 0 times

...

Erick

4 months ago

I wonder if a Pega machine learning model could be relevant, but without data, it seems tricky.

upvoted 0 times

...

Isabella

4 months ago

This feels similar to a practice question we did on adaptive models, but I can't recall if that's the right choice here.

upvoted 0 times

...

Wilda

4 months ago

I'm not entirely sure, but I remember something about when rules being useful for specific conditions.

upvoted 0 times

...

Huey

5 months ago

I think we might need to use a decision table since there's no historical data to base decisions on.

upvoted 0 times

...

Kanisha

5 months ago

I'm leaning towards the decision table approach. It seems like the most straightforward way to handle the lack of historical data and still provide personalized offers on the web portal.

upvoted 0 times

...

Julio

5 months ago

I think the Pega machine learning model could be a good option here. Without historical data, it might be able to learn and adapt to the new customer behavior over time.

upvoted 0 times

...

Desmond

5 months ago

Hmm, I'm not sure about this one. The question mentions a "personalized web portal," so maybe a When rule would be more appropriate to handle the personalization aspect.

upvoted 0 times

...

Marguerita

5 months ago

This seems like a straightforward question. Since the bank has no historical customer data, I think the best approach would be to use a decision table to determine the credit card offer.

upvoted 0 times

...

Eugene

5 months ago

I'm a little confused by this question. If there's no historical data, how can we use a decision table? Wouldn't an adaptive model be a better fit to handle the lack of data?

upvoted 0 times

...

Francisca

5 months ago

This question seems straightforward. I think the best approach is to carefully read through the options and select the one that most directly addresses the requirement of using articles as a different channel for social interactions.

upvoted 0 times

...

Sherrell

5 months ago

This seems straightforward to me. The list box on the top needs to be cleared, so "Clear Field" is the first step. Then "Dynamic Update" will update the list box on the bottom.

upvoted 0 times

...

Donette

5 months ago

The wording of these options is tricky, I need to read them closely to make sure I understand the nuances.

upvoted 0 times

...

Willow

2 years ago

I would go with A) Decision table because it allows for easy decision making based on conditions.

upvoted 0 times

...

Mertie

2 years ago

I think either C) Adaptive model or D) Pega machine learning model could work in this scenario.

upvoted 0 times

...

Daniela

2 years ago

I disagree, I believe the answer is D) Pega machine learning model.

upvoted 0 times

...

German

2 years ago

I think the answer is C) Adaptive model.

upvoted 0 times

...

Gracia

2 years ago

Pega machine learning? Really? Isn't that overkill for a simple credit card with no data? I think we're overthinking this. A good old-fashioned decision table is the way to go.

upvoted 0 times

...

Dottie

2 years ago

An adaptive model? That sounds fancy. I'm more of a Pega machine learning kind of guy. We could let the machine do all the heavy lifting and come up with the best personalized offers.

upvoted 0 times

...

Harrison

2 years ago

I'm not sure a when rule is the best fit here. Since we don't have any historical data, an adaptive model might be more appropriate. It can learn and adjust the personalized offers over time.

upvoted 0 times

...

Shenika

2 years ago

Hold on, what about a when rule? That could be a good option too. We can use it to define conditions and actions based on the new credit card's features.

upvoted 0 times

Melissa

2 years ago

I agree, decision tables could be a good option as well.

upvoted 0 times

...

Merilyn

2 years ago

But what about decision tables? They can also be helpful in this case.

upvoted 0 times

...

Edward

2 years ago

Yeah, a when rule can help define conditions and actions easily.

upvoted 0 times

...

Dalene

2 years ago

I think a when rule would be perfect for this situation.

upvoted 0 times

...

Lenna

2 years ago

I agree, a decision table seems like the most logical choice here. We can create a set of rules that determine the personalized offers based on the limited data we have.

upvoted 0 times

...

Tran

2 years ago

This is an interesting scenario. Since there is no historical customer behavior data, I think a decision table would be the best approach. It allows us to define specific rules based on the information we have about the new credit card.

upvoted 0 times

...