Water Consumption Financial Fraud Detection: A Model Based on Rule Induction

Financial losses due to financial frauds are mounting, recognizing the problem of losses and the area of suspicion behavior is the challenge of the fraud detection. Several data mining algorithms have been developed to allow one to extract relevant knowledge from a large amount of data, like fraudulent financial statements and statistical information, help in detecting frauds and narrow the circle of doubt. Thus, the purpose of this paper is to know what are the famous mining methods that used in this field, what kind of techniques can be used effectively, applying them in a real-world dataset to extract respectable knowledge and discover new patterns from a large database, to support fraud detection in the water delivering service and improve business performance, focusing on a financial billing system for Gaza customer´s water consumptions, using a model based on rule induction.