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in the previous exercise yes aha banks may prefer one model over another depending on the minimum bad rate they are allowed to have or turning it around depending on their acceptance rate often banks just want to know what the best model is overall without having to make any assumption regarding acceptance rates or cutoff to illustrate this letamp;#39;s go back to our decision matrix metrics here we have learned about accuracy sensitivity and specificity we already discussed that classification accuracy includes all the tested elements in the denominator and as a result is tempting to use however classification accuracy is also a problematic measure in the credit scoring context as accuracy is generally maximized when a very high cutoff is chosen or in other words when all tested elements are classified as non defaults this is why one of the most popular methods to evaluate credit risk models is based on sensitivity and specificity this evaluation method itamp;#39;s called the receiv
