Free PEGAPCDC87V1 Pegasystems Updates

To implement the change in the threshold value for the USD 2000 credit limit from “<175” to “<200”, as a Strategy Designer, you should change the cutoff value in the results tab of the scorecard decision component. This adjustment ensures that the decision logic used to automatically approve credit card limits reflects the new threshold, thereby updating the conditions under which customers qualify for the specified credit limit.

To ensure that Silver credit cards are not offered to customers under 27 years of age and that Platinum cards are offered only to customers who had a positive balance in the last year, you need to configure "Engagement policies" in the Next-Best-Action Designer. Engagement policies allow you to set criteria such as eligibility, applicability, and suitability for actions. For this scenario, you would set the eligibility criteria to ensure the age and balance conditions are met before the offers are presented.

 Introduction to Prioritize Component:

The Prioritize component in Pega Decisioning is used to order actions based on specific criteria.

This component evaluates the importance or priority of different actions to determine which should be executed first.

 Understanding Propensity:

Propensity is a prediction of the likelihood that a customer will respond positively to a particular action.

It is a key factor in decision-making processes as it reflects the customer's predicted behavior based on past interactions and other data.

 Role of Propensity in Prioritize Component:

The primary function of the Prioritize component is to rank actions.

This ranking is typically based on the propensity value, which is calculated using predictive models.

The action with the highest propensity is considered the top action because it has the highest predicted likelihood of a positive customer response.

 Verification from Pega Documentation:

According to Pega's guidelines on creating and understanding decision strategies, propensity is a standard and recommended metric for prioritizing actions within the Prioritize component.

Decision Table Processing: The decision table is configured to evaluate the customer's credit score and average balance to determine the risk segmentation.

Conditions Evaluation:

For a credit score of 240 and an average balance of 35,000:

The first condition checks if the credit score is >= 400 and < 600, and average balance is >= 30,000, which does not match.

The second condition checks if the credit score is >= 200 and < 400, and average balance is >= 20,000, which matches both the credit score (240) and the average balance (35,000).

Therefore, the correct result for these conditions is "Fair".

References: This is derived from typical Pega Decision Table configuration and logical evaluation as described in Pega documentation on using decision tables for such scenarios .