As consumers are increasingly uploading their personal information online and carrying out business transactions via computers and smart-phones, fraud detection has become very crucial in today’s digital environment. The sole purpose of fraud detection is to protect online assets of enterprises and consumers. From accounts and transactions to batch analysis of user activity, fraud detection examines the patterns and behavior of the information being transferred through background server-based processes. Nowadays, enterprises tend to rely on fraud detection for information security and mitigating information theft, but every defense solution has its weak points. It is essential that enterprises look at four crucial aspects of fraud detection before its implementation. According to StartUp City, first and foremost is real-time fraud detection. For an enterprise fraud detection to be successful, the solution must possess the ability to process, analyze, and evaluate transactions, authorizations and decline decisions before fund movements in real-time. Without that, enterprises might as well open windows for cybercriminals to get away. Second on the lookup list is effective data analytics. This process plays a vital role in sniffing out suspicious consumer behaviors and fraudulent patterns. It is imperative that the data analytics output includes a consumer score that represents a consumer’s actual behavior and a transaction fraud score, to determine the fraudulent nature of a transaction.
All enterprise fraud detection solutions include many processes to manage and rectify every consumer’s fraud issues, which brings us to the third aspect of the lookup list: workflow. It is crucial that enterprises have a seamless, flexible workflow to automate and consolidate the remediation process for effective fraud detection. Each specific, be it action, data or process, is an integral part of managing any given fraud case and producing evidence for prosecution. Depending on the type of payment and the steps required for addressing the situation, a cohesive workflow reduces the overall fraud detection time and operational costs. Lastly, one must consider the efficiency of the rules engine. Rules are a predefined set of strategies a fraud detection solution follows in the occurrence of a suspicious event. The rules vary for different types of payment and transactions. However, the efficiency of the rule engine determines how well and how quickly an enterprise fraud detection solution can react to shut down the fraud. A rule engine that leverages information management and process documentation to refine fraud detection makes it auditable and the best fit for enterprise security.