The Credit Model slide contains two elements to understand the scorecard.

![Score Card.png](VtY9q3BQhgxa)

The scorecard is displayed as a dataset. It contains as many rows as there are bins within each selected feature. And for each of these bins, a score is precomputed. For a given applicant, the score will be the sum of the points from each of the features. If data is missing for one of the features, it is handled in one of the bins of the feature so that a number of points are always assigned for all features.

![Score Card Performance.png](8qBvdnIHbVqX)

The chart shows the average credit event frequency per group of scores, all computed on a test dataset. Scores have been computed using the scorecard and binned to have reliable estimations of the credit event frequency within each bin. A robust scorecard will show a monotonic decrease in credit event likelihood as the score increases. One can also check that the observed odds are the ones configured to build the scorecard.


