This review reproduces tests and results presented by Pitt and Hill and discusses some other non- parametric techniques, such as Permutation Tests, which allow to analyze data with less restrictive assumptions. The focus of the review is on the statistical methodology rather than the underlying biological aspects and assumptions of the original work, which are not discussed. Although not expert in statistical methods for fraud detection, we do believe that permutation tests are promising in this context, as demonstrated by the results presented here. This review has been developed as a term project for a Graduate Level Course on Statistical Models at UC Berkeley.