Predictive fraud analysis system for data transactions

Abstract

A method for execution by a computing entity of a data transactional network includes generating a plurality of risk analysis responses regarding a transaction for fraud evaluation, where the transaction is between a first computing device and a second computing device regarding transactional subject matter. The method further includes performing a first level interpretation of the plurality of risk analysis responses to produce a first level fraud answer. The method further includes determining a confidence of the first level fraud answer compares unfavorably with a confidence threshold. The method further includes determining a second level interpretation of the plurality of risk analysis responses based on a level of the confidence of the first level fraud answer. The method further includes performing the second level interpretation of the plurality of risk analysis responses to produce a fraud evaluation answer regarding the transaction.

What is claimed is: 
     
         1 . A method for execution by a computing entity of a data transactional network comprises: 
       generating a plurality of risk analysis responses regarding a transaction for fraud evaluation, wherein the transaction is between a first computing device of the data transactional network and a second computing device of the data transactional network regarding transactional subject matter; 
       performing a first level interpretation of the plurality of risk analysis responses to produce a first level fraud answer; 
       determining a confidence of the first level fraud answer compares unfavorably with a confidence threshold; 
       determining a second level interpretation of the plurality of risk analysis responses based on a level of the confidence of the first level fraud answer; and 
       performing the second level interpretation of the plurality of risk analysis responses to produce a fraud evaluation answer regarding the transaction. 
     
     
         2 . The method of  claim 1 , wherein the fraud evaluation answer is one of: 
       further analysis is required; 
       a low risk of fraud; and 
       a high risk of fraud. 
     
     
         3 . The method of  claim 1  further comprises: 
       generating a plurality of evidence vectors regarding the transaction, wherein an evidence vector of the plurality of evidence vectors is a piece of information regarding a topic, or portion thereof, of a list of topics. 
     
     
         4 . The method of  claim 3  further comprises: 
       engaging a plurality of tools; and 
       generating, by the plurality of tools, the plurality of risk analysis responses based on the plurality of evidence vectors. 
     
     
         5 . The method of  claim 4 , wherein the plurality of tools comprises: 
       a set of risk assessment tools. 
     
     
         6 . The method of  claim 4 , wherein the plurality of tools comprises: 
       a set of evidentiary tools. 
     
     
         7 . The method of  claim 4 , wherein the plurality of tools comprises: 
       a set of swarm processing tools. 
     
     
         8 . The method of  claim 3 , wherein the topic comprises user information regarding a user associated with the first computing device. 
     
     
         9 . The method of  claim 8 , wherein the topic comprises information regarding network affiliations of the user. 
     
     
         10 . The method of  claim 3 , wherein the topic comprises information regarding the first computing device. 
     
     
         11 . The method of  claim 10 , wherein the information regarding the first computing device comprises one or more sub-topics of: 
       device information; 
       device type; and 
       user-device affiliation information. 
     
     
         12 . The method of  claim 3 , wherein the topic comprises anomaly information regarding the first computing device. 
     
     
         13 . The method of  claim 12 , wherein the anomaly information further comprises information regarding the second computing device. 
     
     
         14 . The method of  claim 12 , wherein the anomaly information further comprises information regarding the data transaction network. 
     
     
         15 . The method of  claim 3 , wherein the topic comprises anomaly information regarding the data transaction network. 
     
     
         16 . The method of  claim 3 , wherein the topic comprises information regarding network affiliations of the first computing device. 
     
     
         17 . The method of  claim 3 , wherein the list of topics further includes: 
       transaction mechanism information that includes one or more sub-topics of:
 information regarding the transactional subject matter; 
 transmission medium information regarding transmission of a request for the transaction from the first computing device to the second computing device; 
 host layer information; and 
 proxy information. 
 
     
     
         18 . The method of  claim 3 , wherein the list of topics further includes: 
       bad actor information that includes one or more sub-topics of:
 markers indicating use of hacker tools; and 
 professional bad actor indicators. 
 
     
     
         19 . The method of  claim 3 , wherein the list of topics further includes: 
       fraud information that includes one or more sub-topics of:
 account take over; 
 fake account information; 
 fraudulent login; 
 fraud attempt rate; and 
 multiple user collusion. 
 
     
     
         20 . The method of  claim 1 , wherein the performing the first level interpretation on the plurality of risk analysis responses is further based on risk tolerance inputs associated with the second computing device.