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Cumulative Event Rates

Shows the dependence between changes in rates of “Good” and “Bad” and changes in the score
An increase in the share of the “Good” outcomes, accompanied by a decrease in the number of “Bad” accounts, confirms that the Scorecard’s performance is logical.

A monotonous decrease in the share of the “Bad” borrowers in the upper score range speaks about the correctness of the Scorecard’s performance and its ability to differentiate “Bad” borrowers into the lower part of the working range.

Acceptable Cumulative Event Rates graph



Unacceptable Cumulative Event Rates graph





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