Fraud has been causing rising challenges for businesses. Over 72% of businesses cite fraud as a growing concern, and about 63% of businesses report the same or higher levels of fraudulent losses over the past 12 months according to a report by Experian Global. The challenge is not just about preventing fraud, but figuring out how to predict it before it happens, so it can be prevented from happening at all. But before we make strategies to combat fraud, it’s important to understand the barriers associated with fraud detection strategies.
Effective fraud detection and financial control initiatives leverage advanced analytics and machine learning techniques to derive valuable and actionable information for managers. Today’s enterprises churn out humongous volumes of data but are still unable to use most of that data in its raw form. The task of acquiring, cleansing, shaping, and bending the raw operational data for analytics or other business purposes is known as data preparation.