System and method of detecting fraud
First Claim
1. A computerized method of detecting fraud, the method comprising:
- receiving, on at least one processor, data associated with a financial transaction and at least one transacting entity, wherein the data associated with the transacting entity comprises respective values of at least one data field of each of a plurality of historical transactions of the transacting entity;
applying the data to at least one first model;
generating a score based on the first mode; and
generating data indicative of fraud based at least partly on the score.
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Accused Products
Abstract
Embodiments include systems and methods of detecting fraud. In particular, one embodiment includes a system and method of detecting fraud in transaction data such as payment card transaction data. For example, one embodiment includes a computerized method of detecting that comprises receiving data associated with a financial transaction and at least one transacting entity, wherein the data associated with the transacting entity comprises at least a portion of each of a plurality of historical transactions of the transacting entity, applying the data to at least one first model, generating a score based on the first model, and generating data indicative of fraud based at least partly on the score. Other embodiments include systems and methods of generating models for use in fraud detection systems.
256 Citations
45 Claims
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1. A computerized method of detecting fraud, the method comprising:
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receiving, on at least one processor, data associated with a financial transaction and at least one transacting entity, wherein the data associated with the transacting entity comprises respective values of at least one data field of each of a plurality of historical transactions of the transacting entity; applying the data to at least one first model; generating a score based on the first mode; and generating data indicative of fraud based at least partly on the score. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 41)
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22. A system for detecting fraud, the system comprising:
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a storage configured to receive data associated with at least one transacting entity, wherein the data associated with the transacting entity comprises respective values of at least one data field of each of a plurality of historical transactions of the transacting entity; and a processor configured to; apply transaction data and the data associated with the at least one transacting entity to at least one first model; generate a score based on the first model; and generate data indicative of fraud based at least partly on the score. - View Dependent Claims (23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37, 38, 42)
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39. A system for detecting fraud, the system comprising:
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means for receiving data associated with at least one transacting entity, wherein the data associated with the transacting entity comprises respective values of at least one data field of each of a plurality of historical transactions of the transacting entity; and means for processing transaction data, said processing means configured to; apply transaction data and the data associated with the at least one transacting entity to at least one first model; generate a score based on the first model; and generate data indicative of fraud based at least partly on the score. - View Dependent Claims (43)
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40. A computerized method of detecting fraud, the method comprising:
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receiving, on a processor, data associated with a financial transaction and at least one account, wherein the data associated with the account comprises respective values of at least one data field of each of a plurality of historical transactions of the account; applying the received data to at least one first model; generating a score based on the first model; applying the received data to at least one second model; identifying the account as being associated with a plurality of clusters, wherein each of the clusters is identified as being associated with a plurality of accounts based on the application of the received data to the at least one second model and the received data and wherein the at least one cluster is based at least in part on respective data values of the at least one data field of each of the plurality of historical transactions associated with each of the plurality of historical transactions of each of the plurality of accounts; identifying a transition associated with the account between at least two of the clusters; and generating data indicative of fraud based at least partly on the score and at least partly on the identified transition. - View Dependent Claims (44, 45)
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Specification