Types of scoring

Application Scoring

Application scoring quantifies the risks, associated with loan applications, by evaluating the social, demographic, financial, and other data collected at the time of the application.

It facilitates customer acquisition decisions. Used in application processing systems, application scoring helps to automate the whole process of loan origination.

Behavioral Scoring

Behavioral scoring quantifies the customer behavior to improve your credit portfolio management and customer management. Behavioral scoring helps you to better understand your customers, and, the better you understand your customers, the more effectively you can respond to their individual needs and increase your bottom line.

It facilitates customer management decisions. Used in credit management or portfolio processing systems, behavioral scoring helps to automatically segment and rate accounts, customers and portfolios thus allowing managing efficiently a particular borrower’s credit account as well as the entire credit portfolio.

Collection Scoring

Collection scoring quantifies the probability of recovery of the outstanding balance for those accounts in collections. Collection scorecard statistically estimates debtor’s willingness to pay and ability to pay and thus helps to define what actions should be done to increase collections.

It facilitates debt management decisions. Used in debt collection systems, collection scoring helps you improve your collection and recovery efficiency, reduce write-offs and decrease staff costs.

Fraud Scoring

Fraud scoring rank-order applicants according to the probability that an application may be fraudulent and thus alerts you of potentially fraudulent applications before you book an account.

It facilitates fraud detection and prevention helping you instantly decide which of the applications should be rejected or set aside for more in-depth evaluation due to high fraud probability. Used as addition to loan origination systems, fraud scoring helps lenders to increase their profits and enhance their customer service, by identifying potential fraud at the earliest point possible.


Judgmental vs. Statistical Scorecard

If you have no historical data you can create judgmental scorecard by selecting customer’s characteristics and corresponding weights based on experts opinion.
After several months, when you will have historical data about delinquencies, you can gradually switch from judgment to statistical scorecard.

Comparison of judgmental and statistical approach for loan applicant evaluation

Characteristics Judgement Credit Scoring
Payment to Income Ratio + 112
Marital Status + 37
Last Work Record + 105
Children + 62
Cards 0
Credit History + 262
Home Ownership + 35
Time At Branch + 45
Overall + 658
Decision Accept Accept
Odds of repayment unknown “24:1”

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