You are given a data set on fraud detection. Classification model achieved accuracy of 95%.Is it good?

Accuracy of 96% is good. But we may have to check the following items:

what was the dataset for the classification problem

Is Sensitivity and Specificity are acceptable

if there are only less negative cases, and all negative cases are not correctly classified, then it might be a problem

In-Addition it is related to fraud detection, hence needs to be careful here in prediction (i.e not wrongly predicting the fraud as non-fraud patient. We should check each possibility for prediction because if prediction is not done correctly the accuracy will be of no use and fraud detection is a very sensitive type of prediction so we should take care of classification.