What is the difference between GINI and AUC curve interpretation?

we used to create GINI curve using lift created with help of percentage of good and bad for scorecard modelling. But what I have studied that ROC curve is created using Confusion matrix with Specificity (1- True Negative) as x axis and sensitivity( true positive) as Y axis.

So the result of GINI and ROC is same with one difference is that latter also take into consideration of concordance and discordance value ( TP, FP, FN, TN).

The direct conversion between Gini and AUROC is given by: $$Gini = 2\times AUROC - 1$$