Model for detecting anomalies and suspicious transactions on financial and non-financial entries

Abstract

Some conventional audit methods sometimes fall short in identifying subtle irregularities and emerging fraudulent schemes. Our proposal is therefore part of the aim of improving audit processes. At the end of the experiments on two sets of data, our model offers the best results compared to other models, particularly in terms of CPU execution time of the model and also in terms of performance in the detection of normal data with a better rate of false positives.