February 11, 2018
The PwC global economic crime survey of 2016 suggests that approximately 36% of organizations experienced economic crime. Therefore, there is definitely a need to solve the problem of credit card fraud detection. The task of fraud detection often boils down to outlier detection, in which a dataset is scanned through to find potential anomalies in the data. In the past, this was done by employees which checked all transactions manually. With the rise of machine learning, artificial intelligence, deep learning and other relevant fields of information technology, it becomes feasible to automate this process and to save some of the intensive amount of labor that is put into detecting credit card fraud.