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| Section | Objectives |
|---|---|
| Decision Strategies and Configuration | - Real-time decisioning
|
| Customer Decision Hub Overview | - Next-Best-Action (NBA) Framework
|
| AI and Adaptive Analytics | - Adaptive models
|
| Customer Engagement and Channels | - Omnichannel delivery
|
| Reporting and Monitoring | - Performance tracking
|
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NEW QUESTION # 106
U+ Bank, a retail bank, is currently presenting a cashback offer on its website.
Currently, only the customers who satisfy the following engagement policy conditions receive the cashback offer:
While continuing cross-selling on the web, the bank now wants to present the cashback offer through a new channel, SMS. The bank also wants to update the suitability condition by lowering the threshold of the debt-to-income ratio from 48 to 45.
As a business user, what are the two tasks that you define to update the cashback offer? (Choose Two)
Answer: B,C
Explanation:
To update the cashback offer, you need to edit the engagement policy and the action details. Editing the engagement policy allows you to add a new channel (SMS) and update the suitability condition (lowering the debt-to-income ratio). Editing the action details allows you to specify the treatment for each channel (web and SMS). Verified Reference: [Pega Decisioning Consultant | Pega Academy]
NEW QUESTION # 107
A bank has been running traditional marketing campaigns for many years. One such campaign sends an offer email to qualified customers on day one. On day five, the bank presents a similar offer if the first email is ignored.
If you re-implement this requirement by using the always-on outbound customer engagement paradigm, how do you approach this scenario?
Answer: B
Explanation:
The always-on outbound customer engagement paradigm relies on AI to select the best action for each customer at any given time, based on their profile, context, and behavior. You do not need to create separate segments or schedules for different offers or timings. You can configure the primary schedule to run daily and let the AI choose the best action based on engagement policies, such as contact policies, eligibility rules, suitability rules, and arbitration. The AI will also learn from the customer responses and optimize the action selection over time.
NEW QUESTION # 108
l)+ Bank uses Pega Customer Decision Hub to approve credit card limit changes requested by customers automatically. A scorecard model determines the customer credit score. The automatic approval of credit card limits are processed based on the following criteria set by the bank.
The bank wants to change the threshold value for the USD2000 credit limit from <175 to <200. How do you implement this change?
Answer: D
Explanation:
The scorecard model determines the customer credit score based on various factors, such as income, expenses, assets, liabilities, etc. The scorecard model has a Results tab where you can define the cutoff values for different segments based on the credit score. To change the threshold value for the USD2000 credit limit from <175 to <200, you need to change the cutoff value in the Results tab of the scorecard model. Changing the cutoff value in the scorecard decision component, changing the condition in the strategy, or mapping the score value in the decision strategy will not affect the credit score calculation or segmentation.
NEW QUESTION # 109
The following decision strategy outputs the most profitable shoe a retailer can sell. The profit is the selling Prices of the shoe, minus the Cost to acquire the shoe.
The details of the shoes are provided in the following table:
The details of the shoes are provided in the following table:
To output the most profitable shoe, which component do you add in the blank space that is highlighted in red?
Answer: C
Explanation:
To output the most profitable shoe, you need to add a Prioritize component in the blank space. A Prioritize component allows you to rank actions based on one or more properties. In this case, you can rank the shoes based on the Profit property and select the highest ranked shoe as the output. Verified Reference: Pega Academy - Decisioning Consultant - Prioritizing actions
NEW QUESTION # 110
U+ Bank's marketing department currently promotes various home loan offers to qualified customers. Now, the bank does not want to show offers on a customer's account page if the customer has already received three home loan offers in the last two weeks.
What do you need to define to implement the business requirement?
Answer: D
Explanation:
A suppression policy allows you to define conditions that prevent customers from receiving an action or a group of actions. You can use a suppression policy to implement the requirement that customers do not see home loan offers on their account page if they have already received three home loan offers in the last two weeks. You can configure the suppression policy to suppress the home loan group based on the number of times the customer received any action from that group in the past 14 days. Applicability rules are used to determine whether an action is relevant for a customer based on their profile or context, not based on the number of times they received an action. Customer contact limits are used to limit the number of times a customer can be contacted per channel per time period, not based on the number of times they received an action. Volume constraints are used to limit the number of times an action is presented to customers across one or more channels, not based on the number of times they received an action. Verified References:
[Certified Pega Decisioning Consultant | Pega Academy], Suppression policies
NEW QUESTION # 111
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