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.

Abstract: A method includes selecting, for evaluation, an entry regarding a transaction from a current transaction-answer (TA) matrix that includes a prediction field for the entry. The method further includes determining whether the prediction field associated with the entry includes an indication that a predicted fraud answer for the transaction is favorable. When unfavorable, the method further includes obtaining inputted data utilized by a fraud assessment model that includes a plurality of artificial intelligence (AI) modules, obtaining additional data regarding the transaction, augmenting the inputted data with the additional data to produce updated data, utilizing the updated data to produce an updated fraud evaluation answer, and determining whether the updated fraud evaluation answer is favorable.

Abstract: A method includes receiving, by a computing entity, a transaction for fraud evaluation. The method further includes generating, by the computing entity, evidence vectors regarding the transaction, wherein an evidence vector is a piece of information regarding a topic, or portion thereof, of a list of topics. The method further includes engaging, by the computing entity, tools to generate risk analysis responses based on the evidence vectors. The method further includes discarding, by the computing entity, indeterminate responses of the risk analysis responses to produce a group of risk analysis responses. The method further includes interpreting, by the computing entity, the group of risk analysis responses to produce a fraud evaluation answer of low risk of fraud, high risk of fraud, or further analysis is required.

Abstract: A method includes receiving, by a computing entity, a transaction for fraud evaluation. The method further includes generating, by the computing entity, evidence vectors regarding the transaction, wherein an evidence vector is a piece of information regarding a topic, or portion thereof, of a list of topics. The method further includes engaging, by the computing entity, tools to generate risk analysis responses based on the evidence vectors. The method further includes discarding, by the computing entity, indeterminate responses of the risk analysis responses to produce a group of risk analysis responses. The method further includes interpreting, by the computing entity, the group of risk analysis responses to produce a fraud evaluation answer of low risk of fraud, high risk of fraud, or further analysis is required.