Definition: Anti-fraud management is a set of IT practices and solutions designed to detect, prevent, and mitigate fraudulent activities in an organization. It involves the use of advanced technologies such as artificial intelligence, machine learning, and data analytics to identify and analyze patterns of fraudulent behavior. Source: Techopedia Source reference: https://www.techopedia.com/definition/24835/fraud-detection Additional information: Anti-fraud management systems are crucial in various sectors, including banking, insurance, e-commerce, and healthcare, where they help to protect sensitive data and financial transactions. These systems can detect anomalies in user behavior, identify suspicious transactions, and alert the relevant authorities for further investigation. They can also help to reduce the risk of identity theft and other forms of cybercrime. Anti-fraud management systems often use predictive modeling to identify potential threats and vulnerabilities, and they can be integrated with other security measures to provide a comprehensive defense against fraud. Example: 1. In banking, anti-fraud management systems can be used to monitor transactions and alert the bank to any suspicious activity, such as unusually large transfers or rapid succession of transactions. 2. In e-commerce, these systems can detect fraudulent purchases by analyzing the buyer's behavior, such as the speed of their clicks and the type of products they are buying. 3. In insurance, anti-fraud management can help to identify fraudulent claims by analyzing patterns in the claim data. LOST view: OV-Digital Public Services Catalogue Identifier: http://data.europa.eu/dr8/egovera/Anti-fraudManagementBusinessService EIRA traceability: eira:DigitalPublicBusinessService ABB name: egovera:Anti-fraudManagementBusinessService EIRA concept: eira:ArchitectureBuildingBlock Last modification: 2023-07-27 dct:identifier: http://data.europa.eu/dr8/egovera/Anti-fraudManagementBusinessService dct:title: Anti-fraud management Digital Public Service