Pegasystems PEGAPCDC87V1 Dumps Questions Answers

Business Requirement: The need is to implement risk segmentation rules based on age and credit score.

Decision Table Integration: The decision table can be added to the decision strategy where it will evaluate the credit score and age, and then assign the appropriate risk segment.

Parameter Passing: The decision table within the strategy will use the credit score passed to it as a parameter to determine the segmentation.

References: Pega's methodology for incorporating decision tables into strategies for evaluating and segmenting customers based on specific criteria is well documented in the user guides .

 Requirement:

U+ wants to show a retention offer to customers likely to leave the bank based on historical interaction data.

 Model Types:

Entity Model: Used for recognizing entities within data.

Text Analytics Model: Used for analyzing text data.

Predictive Model: Used for making predictions based on historical data.

Adaptive Model: Used for real-time adaptation based on new data.

 Suitable Model:

For predicting customer churn (likelihood of leaving), a predictive model is best suited because it leverages historical data to make future predictions.

 Verification from Pega Documentation:

Pega documentation on leveraging predictive models for customer retention and churn analysis.

Scorecard Rule - A scorecard in Pega is used to calculate a score based on various customer attributes. To include a new attribute (customer income), the scorecard rule must be updated.

Steps to Update Scorecard:

Navigate to the scorecard rule in Dev Studio.

Add a new input for customer income.

Define the scoring logic for the new input.

Save the updated scorecard.

Decision Strategy - The decision strategy that uses this scorecard must also be updated to ensure it correctly utilizes the new score calculations.

Steps to Update Decision Strategy:

Locate the decision strategy in the Next-Best-Action Designer.

Ensure the updated scorecard is referenced correctly.

Adjust any logic or thresholds that depend on the scorecard output.

Test the strategy to ensure it works as expected with the updated scorecard.