Creating a scorecard to calculate the credit score

2 Tasks

10 mins

Pega Platform '24.1

Visible to: All users

Beginner

Pega Platform '24.1

English

Scenario

A financial institution offers various credit cards to customers. Because of the limit for each card, credit cards are unsuitable for customers if their credit score is less than 600 due to the likelihood of default.

The credit score value is available in the data model, and external processes populate the value in a nightly batch. However, a credit score is not computed for every customer.

As a result, the business wants a scorecard that computes a customer's credit score if the score is not available.

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

Role	User name	Password
Decisioning Architect	DecisioningArchitect	rules

Your assignment consists of the following tasks:

Task 1: Create a scorecard, Determine Credit Score, with exact specifications

Customer Financial Vulnerability indicator

Assign a score of 0 if the customer is financially vulnerable. Otherwise, assign a score of 300.

Customer Annual Income

Split the values for yearly income into four ranges, and assign scores to each range as shown in the following table:

Condition	Score
<=7000	0
<=8000	100
<=10000	150
<=12000	200
Otherwise	300

Customer DebtToIncomeRatio

Split the values for Debt To Income Ratio into three ranges, and assign scores to the ranges as shown in the following table:

Condition	Score
<=20	300
<=30	200
<=40	100
Otherwise	50

Task 2: Configure the scorecard result to Not suitable and Suitable

The scorecard outputs Not Suitable if the credit score is less than 600 and Suitable if the score is equal to or higher than 600.

Task 3: Test the scorecard results

Verify the scorecards for customers Customer1 and Customer2.

 

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

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

• Log In

Challenge Walkthrough

Detailed Tasks

1 Create a scorecard Determine Credit Score with exact specifications

1. On the exercise system landing page, click Launch Pega Infinity™ to log in to Dev Studio.
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 > Scorecard to open the Create Scorecard landing page.
   
4. On the Create Scorecard landing page, in the Scorecard Record Configuration section, in the Label field, enter Determine Credit Score.
5. In the Context section, in the Apply to field select Sample-Data-Customer.
6. In the upper right, click Create and open to open the rule form of the scorecard.
7. On the rule form, on the Scorecard tab, in the Combiner function list, confirm that Sum is selected.
8. In the Predictor expression field, enter or select .IsFinanciallyVulnerable, and then define the condition with the following values:
   1. Condition = True and Score = 0
   2. Otherwise: Score = 300.
9. Click Add to add another predictor expression.
10. In the Predictor expression field, enter or select .AnnualIncome, and then define the condition with the values as shown in the following figure:
    
11. Click the Add icon to add another predictor expression.
12. In the Predictor expression field, enter or select .DebtToIncomeRatio, and then define the condition with the values as shown in the following figure:
    

2 Configure the scorecard result to Not suitable and Suitable

 

1. On the scorecard rule form, click the Results tab to see the results of the scorecard.
2. In the first row, in the Result field, enter Not Suitable.
3. In the Cutoff value field, enter 600.
4. In the second row, in the Result field, enter Suitable.
   
5. Click Save to save the changes.

Confirm your work

1. In the upper-right corner, click Actions > Run.
2. Expand the Run menu.
   
3. Select the Apply data transform checkbox.
4. In the Data transform field, enter or select Customer1.
5. In the upper right, click Run. The values of the properties are populated in the execution details after applying a data transform.
   
   Customer1 gets a score of 700, so it is suitable for a credit card.
6. Repeat the steps 4-7 for Customer2.
   
7. Customer2 gets a score of 550, so it is not suitable for a credit card.

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

• Using scorecards in decision strategies v1

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Available in the following mission:

• Credit Risk Decisioning v2