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Historical Data Preparation

Historical Data Preparation

1.  Historical data should include a set of characteristics and a target variable. All of scorecard development methods quantify the relationship between the characteristics (input columns) and “Good/Bad” performance (target column).

2.  Example of borrowers characteristics. Scorecard characteristics are similar to those used in subjective expert judgment.





3.  Those characteristics, whose usage is not reasonable, are excluded. For example: on the picture you can see that the “Good/ Bad” distribution does not depend on the Home Ownership characteristics.

4.  All borrowers should be marked in the target column as “Good” or “Bad” by a certain rule. For example: all the borrowers to pay in 30 days, are “Good”, but borrowers with a delay of more than 90 days are marked as “Bad”.



Exclusions

Certain types of accounts need to be excluded from the dataset. For example: bank workers or VIP clients records could be excluded from data set.





Data Cleansing

Borrowers portfolio data can contain the following anomalies that should be replaced or deleted:
  • Outliers - values that lie far outside the main volume
  • Data entry errors
  • Missing values







Plug&Score is the most easy-to-use and the fastest to integrate scoring system.

For more complex and versatile needs of larger credit institutions we recommend Scorto™:
Acquaintance with Scoring
What is scoring and why you need it
Scoring
Scorecard
Cut-off, odds and risk groups
What scoring can bring you
Profitability of Operational Decisions
Decreased Decision Time
Agility and Reduced Labor Costs
Types of Scoring
Judgmental vs. Statistical Scorecard
What you need to start using scoring
Scorecard Development
Scorecard Development Stages
Historical Data Preparation
Training & Validation Datasets
Binning
Characteristics Selection Using
Information Value
Logistic Regression for Scorecard Calculation
Automatic Variables Selection with Stepwise Methods
Basic Scorecard Quality Assessment
Reject Inference
Scorecard Scaling
Scorecard Validation
Gini & ROC Curve
Kolmogorov-Smirnov Curve
Risk Segments
Strategy Curve
Approval vs "Bad" Rate
"Good" and "Bad" distribution
Cumulative Event Rates
Chi-squared Scorecard Stability Test
Score Points Distribution
Scorecard Implementation & Deployment
Verifying Borrowers Characteristics Stability
Scorecard Correction (if required)
Setting Cut-off
Policy Rules Definition
Scorecard Deployment
Champion-Challenger Deployment Approach
Advanced How-to
How to Improve Scorecard Accuracy
How to Apply Reject Inference Methods