Abstract: Techniques and systems for detecting malicious activity within a network are provided herein. A method for detecting malicious activity within a network may include receiving, by a network-based authentication system, a network transaction. The network-based authentication system may identify a first attribute of the network transaction. The method may also include selecting, by the network-based authentication system, a first learning statistical model and a second learning statistical model from a plurality of models for handling the network transaction. Each of the first learning statistical model and the second learning statistical model may create a likelihood that the network transaction is authentic. The first learning statistical model may calculate a first score and the second learning statistical score may calculate a second score. Based on a comparison of the first score to a first threshold and the second score to a second threshold, the network transaction may be authenticated.

Abstract: Techniques and systems for determining a malicious derivative entity within a network are provided herein. A method for determining a malicious derivative entity may include receiving, by a network-based authentication system, a plurality of network transactions. A first attribute of a network transaction within the plurality of network transactions may be identified. The method may also include identifying a plurality of entities for the first attribute. The network-based authentication system may generate a first visual representation of a relationship between the first attribute and the plurality of derivative entities. Each of the derivative entities and the first attribute may be represented as nodes within the first visual representation. A first score for each of the nodes may be determined based on a degree of centrality of the nodes within the first visual representation. One network transaction may be blocked based on at least one node exceeding a first threshold.

Abstract: Techniques and systems for detecting malicious activity within a network are provided herein. A method for detecting malicious activity within a network may include receiving, by a network-based authentication system, a network transaction. The network-based authentication system may identify a first attribute of the network transaction. The method may also include selecting, by the network-based authentication system, a first learning statistical model and a second learning statistical model from a plurality of models for handling the network transaction. Each of the first learning statistical model and the second learning statistical model may create a likelihood that the network transaction is authentic. The first learning statistical model may calculate a first score and the second learning statistical score may calculate a second score. Based on a comparison of the first score to a first threshold and the second score to a second threshold, the network transaction may be authenticated.

Abstract: Techniques and systems for determining a malicious derivative entity within a network are provided herein. A method for determining a malicious derivative entity may include receiving, by a network-based authentication system, a plurality of network transactions. A first attribute of a network transaction within the plurality of network transactions may be identified. The method may also include identifying a plurality of entities for the first attribute. The network-based authentication system may generate a first visual representation of a relationship between the first attribute and the plurality of derivative entities. Each of the derivative entities and the first attribute may be represented as nodes within the first visual representation. A first score for each of the nodes may be determined based on a degree of centrality of the nodes within the first visual representation. One network transaction may be blocked based on at least one node exceeding a first threshold.

Abstract: In some embodiments, a non-transitory computer-implemented method of assessing a fraud risk is provided. The method can include: receiving data associated with a plurality of customer complaints, wherein data associated with each of the customer complaints at least suggests that a money-transfer transaction did not complete as expected, and wherein data associated with each of the customer complaints is associated with one or more of a plurality of money-transfer agents; electronically storing the data related in a complaint database; and for each of the plurality of money-transfer agents, using a risk processor to: retrieve data associated with the money-transfer agent from the complaint database, and determine a fraud-risk index for the money-transfer agent based on the retrieved data.

Abstract: Techniques and systems for determining a malicious derivative entity within a network are provided herein. A method for determining a malicious derivative entity may include receiving, by a network-based authentication system, a plurality of network transactions. A first attribute of a network transaction within the plurality of network transactions may be identified. The method may also include identifying a plurality of entities for the first attribute. The network-based authentication system may generate a first visual representation of a relationship between the first attribute and the plurality of derivative entities. Each of the derivative entities and the first attribute may be represented as nodes within the first visual representation. A first score for each of the nodes may be determined based on a degree of centrality of the nodes within the first visual representation. One network transaction may be blocked based on at least one node exceeding a first threshold.

Abstract: Techniques and systems for detecting malicious activity within a network are provided herein. A method for detecting malicious activity within a network may include receiving, by a network-based authentication system, a network transaction. The network-based authentication system may identify a first attribute of the network transaction. The method may also include selecting, by the network-based authentication system, a first learning statistical model and a second learning statistical model from a plurality of models for handling the network transaction. Each of the first learning statistical model and the second learning statistical model may create a likelihood that the network transaction is authentic. The first learning statistical model may calculate a first score and the second learning statistical score may calculate a second score. Based on a comparison of the first score to a first threshold and the second score to a second threshold, the network transaction may be authenticated.

Abstract: A money transfer system includes a risk assessment system and a risk modeling system. The risk assessment system uses rules engines and Z scores to assess, on a real time basis, risk factors associated with money transfers. The risk modeling system develops risk scores based on historical transaction data in order to create a risk model. The risk model may be analyzed over time to refine the rules engines and take other actions to understand and reduce the risk of improper activity in connection with money transfers.

Abstract: In some embodiments, a non-transitory computer-implemented method of assessing a fraud risk is provided. The method can include: receiving data associated with a plurality of customer complaints, wherein data associated with each of the customer complaints at least suggests that a money-transfer transaction did not complete as expected, and wherein data associated with each of the customer complaints is associated with one or more of a plurality of money-transfer agents; electronically storing the data related in a complaint database; and for each of the plurality of money-transfer agents, using a risk processor to: retrieve data associated with the money-transfer agent from the complaint database, and determine a fraud-risk index for the money-transfer agent based on the retrieved data.

Abstract: In some embodiments, a non-transitory computer-implemented method of assessing a fraud risk is provided. The method can include: receiving data associated with a plurality of customer complaints, wherein data associated with each of the customer complaints at least suggests that a money-transfer transaction did not complete as expected, and wherein data associated with each of the customer complaints is associated with one or more of a plurality of money-transfer agents; electronically storing the data related in a complaint database; and for each of the plurality of money-transfer agents, using a risk processor to: retrieve data associated with the money-transfer agent from the complaint database, and determine a fraud-risk index for the money-transfer agent based on the retrieved data.

Abstract: Systems, methods, and devices are described for a refundable prepaid transaction cards. The methods and systems include a prepaid transaction card funded with funds by a purchaser. Also included is an issuer. The issuer receives the funds a distributes a prepaid transaction card associated with the funds. The methods and systems also include a prepaid transaction card identifier, wherein the prepaid transaction card identifier identifies the prepaid transaction card. The issuer maintains a central computer system that stores at least one parameter entitling the purchaser to a refund of at least a portion of the funds. The methods and systems also include a cash pool, the cash pool holding at least a portion of the funds funded by the purchaser.

Abstract: Systems, methods, and devices are described for a refundable prepaid transaction cards. The methods and systems include a prepaid transaction card funded with funds by a purchaser. Also included is an issuer. The issuer receives the funds a distributes a prepaid transaction card associated with the funds. The methods and systems also include a prepaid transaction card identifier, wherein the prepaid transaction card identifier identifies the prepaid transaction card. The issuer maintains a central computer system that stores at least one parameter entitling the purchaser to a refund of at least a portion of the funds. The methods and systems also include a cash pool, the cash pool holding at least a portion of the funds funded by the purchaser.

Abstract: A money transfer system includes a risk assessment system and a risk modeling system. The risk assessment system uses rules engines and Z scores to assess, on a real time basis, risk factors associated with money transfers. The risk modeling system develops risk scores based on historical transaction data in order to create a risk model. The risk model may be analyzed over time to refine the rules engines and take other actions to understand and reduce the risk of improper activity in connection with money transfers.

Abstract: Systems, methods, and devices are described for a refundable prepaid transaction cards. The methods and systems include a prepaid transaction card funded with funds by a purchaser. Also included is an issuer. The issuer receives the funds a distributes a prepaid transaction card associated with the funds. The methods and systems also include a prepaid transaction card identifier, wherein the prepaid transaction card identifier identifies the prepaid transaction card. The issuer maintains a central computer system that stores at least one parameter entitling the purchaser to a refund of at least a portion of the funds. The methods and systems also include a cash pool, the cash pool holding at least a portion of the funds funded by the purchaser.

Abstract: A money transfer system includes a risk assessment system and a risk modeling system. The risk assessment system uses rules engines and Z scores to assess, on a real time basis, risk factors associated with money transfers. The risk modeling system develops risk scores based on historical transaction data in order to create a risk model. The risk model may be analyzed over time to refine the rules engines and take other actions to understand and reduce the risk of improper activity in connection with money transfers.

Abstract: A money transfer system includes a risk assessment system and a risk modeling system. The risk assessment system uses rules engines and Z scores to assess, on a real time basis, risk factors associated with money transfers. The risk modeling system develops risk scores based on historical transaction data in order to create a risk model. The risk model may be analyzed over time to refine the rules engines and take other actions to understand and reduce the risk of improper activity in connection with money transfers.

Abstract: Systems, methods, and devices are described for a refundable prepaid transaction cards. The methods and systems include a prepaid transaction card funded with funds by a purchaser. Also included is an issuer. The issuer receives the funds a distributes a prepaid transaction card associated with the funds. The methods and systems also include a prepaid transaction card identifier, wherein the prepaid transaction card identifier identifies the prepaid transaction card. The issuer maintains a central computer system that stores at least one parameter entitling the purchaser to a refund of at least a portion of the funds. The methods and systems also include a cash pool, the cash pool holding at least a portion of the funds funded by the purchaser.

Abstract: In some embodiments, a non-transitory computer-implemented method of assessing a fraud risk is provided. The method can include: receiving data associated with a plurality of customer complaints, wherein data associated with each of the customer complaints at least suggests that a money-transfer transaction did not complete as expected, and wherein data associated with each of the customer complaints is associated with one or more of a plurality of money-transfer agents; electronically storing the data related in a complaint database; and for each of the plurality of money-transfer agents, using a risk processor to: retrieve data associated with the money-transfer agent from the complaint database, and determine a fraud-risk index for the money-transfer agent based on the retrieved data.

Abstract: Systems, methods, and devices are described for a refundable prepaid transaction cards. The methods and systems include a prepaid transaction card funded with funds by a purchaser. Also included is an issuer. The issuer receives the funds a distributes a prepaid transaction card associated with the funds. The methods and systems also include a prepaid transaction card identifier, wherein the prepaid transaction card identifier identifies the prepaid transaction card. The issuer maintains a central computer system that stores at least one parameter entitling the purchaser to a refund of at least a portion of the funds. The methods and systems also include a cash pool, the cash pool holding at least a portion of the funds funded by the purchaser.

Abstract: Systems, methods, and devices are described for a refundable prepaid transaction cards. The methods and systems include a prepaid transaction card funded with funds by a purchaser. Also included is an issuer. The issuer receives the funds a distributes a prepaid transaction card associated with the funds. The methods and systems also include a prepaid transaction card identifier, wherein the prepaid transaction card identifier identifies the prepaid transaction card. The issuer maintains a central computer system that stores at least one parameter entitling the purchaser to a refund of at least a portion of the funds. The methods and systems also include a cash pool, the cash pool holding at least a portion of the funds funded by the purchaser.