Publication details
Lift-Based Quality Indexes for Credit Scoring Models as an Alternative to Gini and KS
| Authors | |
|---|---|
| Year of publication | 2012 |
| Type | Article in Periodical |
| Magazine / Source | Journal of Statistics: Advances in Theory and Applications |
| MU Faculty or unit | |
| Citation | |
| Web | http://scientificadvances.co.in/index.php?cmd=artical&j=4&su=89 |
| Field | Applied statistics, operation research |
| Keywords | Credit scoring;Quality indexes;Gini index;Lift;Lift Ratio;Integrated Relative Lift |
| Description | Assessment of risk associated with the granting of credits is very successfully supported by techniques of credit scoring. To measure the quality, in the sense of the predictive power, of the scoring models, it is possible to use quantitative indexes such as the Gini index (Gini), the K-S statistic (KS), the c-statistic, and lift. They are used for comparing several developed models at the moment of development as well as for monitoring the quality of the model after deployment into real business. The paper deals with the aforementioned quality indexes, their properties and relationships. The main contribution of the paper is the proposal and discussion of indexes and curves based on lift. The curve of ideal lift is defined; lift ratio (LR) is defined as analogous to Gini index. Integrated relative lift (IRL) is defined and discussed. Finally, the presented case study shows a case when LR and IRL are much more appropriate to use than Gini and KS. |