| 摘要 |
<p>A method and system for evaluating fraud risk in an electronic commerce transaction between consumer and a merchant over a network is disclosed. An e-commerce transaction or electronic purchase order is received, the level of risk associated with each order is measured, and a risk score is returned (560). Data validation, highly predictive artificial intelligence pattern matching (520), network data aggregation and negative file checks are used to examine numerous factors to calculate fraud risk. Other analysis includes a comparative comparison of the current transaction against past known fraudulent transactions, and a search of a transaction history database to identify abnormal velocity patterns, name and address changes, and known defrauders. In one alternative, scoring algorithms are regularly refined through the use of a closed-loop risk modeling process that enables the service provided by the system to be fine-tuned to adapt to new or changing fraud patterns.</p> |
