Building customer risk segments using a decision table

2 Tasks

15 mins

Pega Platform '24.1 Visible to: All users

Beginner Pega Platform '24.1 English

Scenario

A financial institution already uses a customer's credit score to determine their suitability for a credit card.

The business now wants to implement rules that prevent high-risk customers from receiving credit card offers. These new rules require customers to be divided into risk segments that range from AAA to CCC. The risk segments are determined based on the customer's Relationship length in days, and by their credit score.

Only customers that belong to certain risk segments are suitable for a credit card.

Use the following credentials to log in to the exercise system:

Role	User name	Password
Decisioning Architect	DecisioningArchitect	rules

The risk segments are determined by two parameters:

• Relations of customer with the financial institution – Value available in the Relationship length in days property of the customer data model.
• Credit score – Score determined by the Determine Credit Score scorecard.

The following table describes the risk segmentation:

Condition	Risk Segment
If Relationship length days is greater than or equal to 550 and Credit score is greater than or equal to 800	AAA
If Relationship length days is greater than or equal to 500 and less than 550 and Credit score is greater than or equal to 800	AAA-
If Relationship length days is greater than or equal to 450 and less than 500 and Credit score is greater than or equal to 800	AA
If Relationship length days is greater than or equal to 400 and less than 450 and Credit score is greater than or equal to 750	AA-
If Relationship length days is greater than or equal to 350 and less than 400 and Credit score is greater than or equal to 700 and less than 750	BBB
If Relationship length days is greater than or equal to 300 and less than 350 and Credit score is greater than or equal to 600 and less than 700	BBB-
If Relationship length days is greater than or equal to 250 and less than 300 and Credit score is greater than or equal to 400 and less than 600	BB-
If Relationship length days is greater than 250 and Credit score is greater than or equal to 200 and less than 400	CCC
If Relationship length days and Credit score falls in any other range	CCC

Your assignment consists of the following tasks:

Task 1: Create a decision table

Create a decision table that implements the financial institution's risk segmentation requirement in accordance with the table above.

Task 2: Use the provided Data Transforms to test the Decision Table for different customers

Use provided Data Transforms and verify that Customer1 is ineligible for a credit card, while Customer2 is eligible. Use the information in the following table for verification:

Customer	Relationship length days	Credit Score	Risk Segmentation
Customer1	364	750	CCC
Customer2	475	800	AA

 

You must initiate your own Pega instance to complete this Challenge.

Initialization may take up to 5 minutes so please be patient.

• Log In

Detailed Tasks

1 Create a decision strategy to determine customer credit scores

1. On the exercise system landing page, click Launch Pega Infinity™ to log in to Pega Customer Decision Hub™.
2. Log in as a decisioning architect:
   1. In the User name field, enter DecisioningArchitect.
   2. In the Password field, enter rules.
3. In the header of Dev Studio, click Create > Decision > Decision Table to open the Create Decision Table landing page.
   
4. On the Create Decision Table page, in the Label field, enter Risk Segmentation.
5. In the Context section, in the Apply to field, select Sample-Data-Customer.
6. In the Add to ruleset field, verify that the system selects ExerciseArtifacts 01-01-01 by default.
7. In the upper right, click Create and open to open the rule form of the Decision Table.
8. Click the first cell in Conditions column to edit the decision table.
9. In the tool bar, click Insert column After to add another column.
   
10. In the Conditions column, click the first cell to select the first Property.
    
    1. In the Property field, enter or select .RelationshipLengthDays.
    2. In the Label field, enter RelationshipLengthDays.
    3. Select the Use Range check box.
    4. Select < from the End Range list.
    5. Click Save to return to the Table tab.
       
11. In the Conditions column, click the second cell, and then enter the following information:
    1. In the Property field, enter .CreditScore.
    2. In the Label field, enter Calculated Credit Score.
    3. Select the Use Range check box.
    4. Select < from the End Range list.
    5. Click Save to return to the Table tab.
       
12. Click the Results tab.
13. On the Results tab, expand Additional Allowed Results. When selected, each target property will be assigned the value specified.
    
14. In the Result field Enter AAA.
15. Click the Add icon to add the next result.
16. Repeat step 15-16 to add the results AAA-, AA, AA-, BBB, BBB-, BB-, and CCC.
17. Click Save.
18. On the Table tab, click Check Out.
19. In the if row, enter the following values:
    1. Relationship Length Days >= 550
    2. Credit Score: 800
    3. Return: AAA
       
20. Click the Insert Row After icon and add an else if row. Enter the following values in the else if row:
    1. Relationship Length Days range: 500 - 550
    2. Credit Score: 800
    3. Return: AAA-
       
21. Enter the following eligibility conditions and return values:
    
22. In the upper right, click Save to save the decision table.

2 Use the provided Data Transforms to test the Decision Table for different customers

1. In the upper right, click Actions > Run to run the Decision Table.
   1. In the run window, in the Test Page section, click pyDefault to choose the Data Transform.
      
   2. Expand the drop-down, scroll down and select Customer1.
   3. Click Reset Page to apply the changes.
   4. In the Result for Test1 section, confirm that Customer1 gets the CCC category and is ineligible for a Credit Card.
      
   5. Repeat steps 1a-1d for Customer2 and observe the test results.

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This Challenge is to practice what you learned in the following Module:

• Building customer risk segments using a decision table v1

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Available in the following mission:

• Credit Risk Decisioning v2