Abstract: A multi-stage filtering process and system for fraud detection is disclosed. The process includes one or more preliminary filtration stages followed by one or more additional filtration stages that provide for enhanced screening for fraudulent activity. In one such embodiment the preliminary filtration provides for evaluating financial transactions based on financial transaction attribute data and secondary filtration provides for further evaluating the financial transactions based on a customer's account event data. Over a plurality of transactions, a portion of the transactions are cleared for processing (e.g., deemed not likely fraudulent or of too low value to continue processing) after each filtration stage. As such, acceptable transactions are not unnecessarily scrutinized. In specific embodiments, filtration is based on financial transaction data and account event data.

Abstract: A multi-stage filtering process and system for fraud detection is disclosed. The process includes one or more preliminary filtration stages followed by one or more additional filtration stages that may include velocity filters that provide for enhanced screening for fraudulent activity. Over a plurality of transactions, a portion of the transactions are cleared for processing (e.g., deemed not likely fraudulent or of too low value to continue processing) after each filtration stage. As such, acceptable transactions are not unnecessarily scrutinized.

Abstract: A multi-stage filtering process and system for fraud detection is disclosed. The multi-stage filtering process allows for the ability to dynamically increase/decrease server capacity, as well as application capacity to support fraud detection activities. The system monitors the queues of the transactions being made using various channels, and responds by adjusting the server and application resources needed for performing pre-filtering on the transactions in the queues. The invention allows for the fraud detection systems to maintain the capacity necessary to examine, at some level, if one or more of the transactions being processed by a financial institution are potentially fraudulent. The capacity can be changed during times of high and low volumes, thus allowing the allocation of resources based on transaction volume, which reduces the computing, energy, labor, etc. costs associated with fraud detection systems without losing the ability to detect almost all of the fraudulent transactions occurring.

Abstract: A multi-stage filtering process and system for fraud detection is disclosed. The process includes one or more preliminary filtration stages followed by one or more additional filtration stages that may include customer history filters that provide for enhanced screening for fraudulent activity. Over a plurality of transactions, a portion of the transactions are cleared for processing (e.g., deemed not likely fraudulent or of too low value to continue processing) after each filtration stage. As such, acceptable transactions are not unnecessarily scrutinized.

Abstract: A multi-stage filtering process and system for fraud detection is disclosed. The process includes one or more preliminary filtration stages followed by one or more additional filtration stages that provide for enhanced screening for fraudulent activity. Over a plurality of transactions, a portion of the transactions are cleared for processing or marked as not fraudulent (e.g., deemed not likely fraudulent or of too low a value to continue analyzing) after each filtration stage. As such, acceptable transactions are not unnecessarily scrutinized.

Abstract: A multi-stage filtering process and system for fraud detection is disclosed. The process includes one or more preliminary filtration stages followed by one or more additional filtration stages that may include velocity filters that provide for enhanced screening for fraudulent activity. Over a plurality of transactions, a portion of the transactions are cleared for processing (e.g., deemed not likely fraudulent or of too low value to continue processing) after each filtration stage. As such, acceptable transactions are not unnecessarily scrutinized.

Abstract: A multi-stage filtering process and system for fraud detection is disclosed. The process includes one or more preliminary filtration stages followed by one or more additional filtration stages that provide for enhanced screening for fraudulent activity. Over a plurality of transactions, a portion of the transactions are cleared for processing (e.g., deemed not likely fraudulent or of too low value to continue processing) after each filtration stage. As such, acceptable transactions are not unnecessarily scrutinized. Methods include receiving transaction data; filtering the transaction data based on a first stage filtration to produce filtered data; enriching the filtered data with geo-positioning data to produce enriched data; and filtering the enriched data based on other attributes to indentify a possible fraud.

Abstract: A multi-stage filtering process and system for fraud detection is disclosed. The process includes one or more preliminary filtration stages followed by one or more additional filtration stages that provide for enhanced screening for fraudulent activity. In one such embodiment the preliminary filtration provides for evaluating financial transactions based on financial transaction attribute data and secondary filtration provides for further evaluating the financial transactions based on a customer's account event data. Over a plurality of transactions, a portion of the transactions are cleared for processing (e.g., deemed not likely fraudulent or of too low value to continue processing) after each filtration stage. As such, acceptable transactions are not unnecessarily scrutinized. In specific embodiments, filtration is based on financial transaction data and account event data.

Abstract: A multi-stage filtering process and system for fraud detection is disclosed. The process includes one or more preliminary filtration stages followed by one or more additional filtration stages that may include customer history filters that provide for enhanced screening for fraudulent activity. Over a plurality of transactions, a portion of the transactions are cleared for processing (e.g., deemed not likely fraudulent or of too low value to continue processing) after each filtration stage. As such, acceptable transactions are not unnecessarily scrutinized.

Abstract: A multi-stage filtering process and system for fraud detection is disclosed. The process includes one or more preliminary filtration stages followed by one or more additional filtration stages that provide for enhanced screening for fraudulent activity. Over a plurality of transactions, a portion of the transactions are cleared for processing (e.g., deemed not likely fraudulent or of too low value to continue processing) after each filtration stage. As such, acceptable transactions are not unnecessarily scrutinized. Another user of the multi-stage filtering process and system is to detect false positive fraud alerts produced by other systems. By reducing the prevalence of false positives, the process and system saves the financial institution costs associated with conducting expensive screening of valid transactions and saves the customers inconvenience and frustration of having valid transactions declined.

Abstract: A multi-stage filtering process and system for fraud detection is disclosed. The multi-stage filtering process allows for the ability to dynamically increase/decrease server capacity, as well as application capacity to support fraud detection activities. The system monitors the queues of the transactions being made using various channels, and responds by adjusting the server and application resources needed for performing pre-filtering on the transactions in the queues. The invention allows for the fraud detection systems to maintain the capacity necessary to examine, at some level, if one or more of the transactions being processed by a financial institution are potentially fraudulent. The capacity can be changed during times of high and low volumes, thus allowing the allocation of resources based on transaction volume, which reduces the computing, energy, labor, etc. costs associated with fraud detection systems without losing the ability to detect almost all of the fraudulent transactions occurring.