Disclosed herein are system, method, and apparatus for detecting a skimmer via a vibration sensor on a transaction card. The method includes receiving, at a server, from a user equipment, vibration information recorded by a transaction card in response to an execution of a transaction at a point-of-service (POS) terminal of a plurality of POS terminals using the transaction card. The vibration information may be recorded by a microphone or an accelerometer on the transaction card while the transaction card is swiped through the POS terminal or inserted into or removed from the POS terminal. The method includes determining, at the server, a state of the POS terminal based on the received vibration information and in response to a determination of the state of the POS being compromised, sending to one or more stakeholders of the transaction a warning message containing the POS terminal information including the POS terminal’s state.

A method for electronic transaction monitoring and reporting includes: determining whether the received transaction request is encrypted, upon determining that the received transaction request is not encrypted, sending a failure alert to the merchant, determining a receiving acquirer processor for the transaction request, and transmitting the transaction request to the determined acquirer processor.

A system and a method of data communication between a first computing device, associated with a first user, and at least one second computing device associated with a second user may include: receiving, by the first computing device, one or more data elements pertaining to details of a transaction request from the second computing device, via a voice channel; extracting said transaction request details by the first computing device; transmitting, by the first computing device, one or more authentication data elements of an electronic wallet module, comprised in the first computing device, to the second computing device, via the voice channel; and carrying out the requested transaction by the first computing device, based on the extracted transaction request details and the electronic wallet authentication data.

A system detects a transaction outcome by obtaining video data associated with a transaction area and analyzing the video data to obtain at least one video transaction parameter concerning transactions associated with the transaction area. The transaction area can be a video count of items indicated in the video data as detected by an automated item detection algorithm applied to the video data. The system obtains at least one expected transaction parameter concerning an expected transaction that occurs in the transaction area, such as a scan count of items scanned at a point of sale terminal. The system automatically compares the video transaction parameter(s) to the expected transaction parameter(s) to identify a transaction outcome that may indicate fraudulent activity such as sweethearting in a retail environment.

Systems and methods are disclosed for providing a payment authorization to a real-time payment (RTP) network to initiate an RTP between a customer financial institution account and a merchant financial institution account. One method performed by a payment facilitator device includes, based on a user device of a customer and a point-of-sale (POS) device of a merchant performing a direct communication regarding a transaction, receiving a payment request for a transaction amount of the transaction and receiving a customer authorization for the transaction. The payment facilitator then provides a payment authorization to an RTP network to initiate an RTP for the transaction amount of the transaction from a customer financial institution account to a merchant financial institution account, based on receiving the customer authorization for the transaction.

A machine-learning algorithm is trained with features relevant to basket data for items of transactions. The trained algorithm is trained to predict whether a given transaction is more or less likely to be associated with theft being engaged in by a transaction operator for the transaction. The trained algorithm is then provided basket data for a given transaction and produces as output a theft prediction value. When the theft prediction value exceeds a configured threshold value, the transaction is flagged for manual intervention or the transaction is flagged for subsequent manual verification.

A merchant and a user register with a payment processing system, which establishes a facial template based on a user image. The user signs into a payment application via a user computing device, which receives an identifier from a merchant beacon device to transmit to the payment processing system. The payment processing system transmits facial templates to the merchant camera device for other users who are also signed in to the payment application in range of the merchant beacon device. The merchant camera device compares a captured facial image against the received facial templates to identify the user. A merchant POS device operator selects an account of the user. The merchant POS device transmits transaction details to the payment processing system, which processes the transaction with an issuer system. The payment processing system receives an approval of the transaction authorization request and transmits a receipt to the merchant POS device.

Various examples are directed to systems and methods for authentication transactions. A mobile computing device may send to a financial institution system, an access request message. The mobile computing device may receive from a second server system, a transaction request message requesting authorization for a transaction on an account associated with the mobile computing device, the transaction request including a transaction amount. The mobile computing device may prompt a user of the mobile computing device to authorize the transaction. The mobile computing device may receive, from the financial institution system, summary data describing the transaction amount.

Techniques described herein are directed to embedded card reader security. In an example, personal account number data read from a payment instrument may be temporally and/or spatially separated from personal identification number data utilized to complete a payment for products. Temporal separation may include removing the personal account number data from a merchant device prior to request personal identification number data. Spatial separation may include utilization of trusted execution environments, separated embedded card reader applications, intermediary applications, and/or trust routines, for example to enable different components of a merchant device, and/or components of other devices and systems to handle personal account number data and personal identification number data.

The present disclosure relates generally to systems and methods that enable access control for digital objects based on measured physiological signals of a user. A method of operation of a human mind interface (HMI) system includes measuring, via a physiological sensor of a HMI device, a brain pattern of a user while the user retrieves a digital object after training. The method includes identifying, via a processor of the HMI device, the measured brain pattern stored in a memory of the HMI device, and determining, via the processor, the digital object stored in the memory that is associated with the identified brain pattern. The method includes accessing, via the processor, the digital object and retrieving information contained in the digital object and providing, via the processor of the HMI device, the information contained in the digital object to a recipient on behalf of the user.