A system for a customer-initiated payment transaction includes a mobile device of a customer and a payment card of the customer. The mobile device includes a mobile application or a digital wallet, on which a customer may register one or more of a plurality of payment methods. The mobile application or the digital wallet may be activated to establish a point-of-sale (OIS) system on the mobile device and include a process to authenticate the customer.

The embodiments of the present application provide a method and apparatus for information and an electronic device. The method includes: when it is detected that a transaction record for a target account is generated in a blockchain ledger, obtaining the generated transaction record for the target account as a current transaction record; comparing the current transaction record with a locally stored transaction record(s) for the target account; when it is determined that the current transaction record differs from any one of the locally stored transaction records for the target account, determining that a security risk of the target account exists; and outputting alert information to alert a user of the target account that the security risk of the target account exists. In this way, the legitimacy of the asset transaction is identified, and thus the security of the account is identified.

Aspects of the disclosure relate to electronically detecting and responding to a security risk associated with a non-electronic transaction. These aspects include recording and storing a video of a customer entering a financial institution (FI). Upon review of the video, the method confirms that the customer is a legacy customer and then deletes the video, or confirms that the customer is a non-legacy customer. If the customer is a non-legacy customer, the method stores the video for an amount of time sufficient to quantify a security risk associated with the customer. The method may then use an input device including at least one customer-imperceptible biometric sensor to retrieve information about the customer. The method compares the stored video to the biometric information to adjust a level of the security risk associated with the customer or transaction. If the security risk is lower than a threshold, the method may delete the video.

A device profiling computer system for determining and analyzing characteristics of devices used in payment transactions includes a processor, a device profiling database in communication with the processor, and a memory coupled to the processor. The device profiling computer system is configured to receive a set of first transaction data associated with a first transaction initiated by a cardholder at an online merchant wherein the cardholder initiates the first transaction using a cardholder computing device and wherein the set of first transaction data includes a set of first device characteristic data related to the cardholder computing device, analyze the set of first transaction data to determine a set of device characteristics, and update a device record stored in a device profiling database with the set of first transaction data wherein the device record is associated with the set of device characteristics.

For a system that provides services to users, it is desirable to provide a technique capable of improving the flexibility of the system while securing the validity of a value and the validity of a user accessing the value. Provided is an information processing device including: an information acquisition unit that acquires, in a case where information indicating that card authentication corresponding to a user terminal has succeeded is acquired, an activation state of a service management application on the user terminal; and an information providing unit that provides the activation state to a service providing device that provides a service to the user terminal.

Aspects of the disclosure relate to electronically detecting and responding to a security risk associated with a non-electronic transaction. These aspects include recording and storing a video of a customer entering a financial institution (FI). Upon review of the video, the method confirms that the customer is a legacy customer and then deletes the video, or confirms that the customer is a non-legacy customer. If the customer is a non-legacy customer, the method stores the video for an amount of time sufficient to quantify a security risk associated with the customer. The method may then use an input device including at least one customer-imperceptible biometric sensor to retrieve information about the customer. The method compares the stored video to the biometric information to adjust a level of the security risk associated with the customer or transaction. If the security risk is lower than a threshold, the method may delete the video.

Embodiments of the present invention can simplify the use of payment cards by capturing or generating an electronic image of a customer's payment card at the time of requesting a payment card transaction, and processing the electronic image to automatically determine required payment card information, including the payment card number, account name, and expiry date printed or otherwise represented on the payment card.

A method for determining an association between a bankcard identifier and at least one mobile communications terminal identifier. The method is implemented by an electronic device and includes: obtaining an identifier of a current bankcard, a bankcard used to make a purchase of an article or a service by using a payment terminal, the obtaining being implemented at the time of the execution of a payment transaction made by using the bankcard; at least one step of obtaining a piece of data representative of at least one communications terminal identifier; and computing a score of correspondence between bankcard identifier and the at least one piece of data representative of a communications terminal identifier.

A particular machine learning architecture involving a two-part artificial intelligence (AI) model is disclosed, with one portion being trained on first data (e.g. older data) and another portion being trained on second data (e.g. newer data) in various embodiments. A robust AI model can be combined with an adaptive AI model to account for long-term trends as well as newly emerging population trends. The model architecture can be constructed using gradient boosting trees, artificial neural networks, or other machine learning models. The adaptive AI model can be re-trained on a more frequent basis than the robust AI model, and can use newer types of data in its classification techniques. The adaptive and robust AI models can be combined using logistic regression to provide unified predictions. Electronic transactions and other types of data subject to potential pattern shifts can thus be more accurately classified.

A system for authorizing a financial transaction of a financial presentation device such as a credit or debit card being presented from a customer to an online merchant. The system includes a peripheral device having a processor configured to generate a dynamic verification value for the card which changes for each financial transaction, and to transmit the dynamic verification value to a user computer via an I/O interface during an online transaction. The system also includes an authentication computer having a memory for storing information used to generate a comparison verification value, a communication device for receiving the dynamic verification value originating from the peripheral device, a processor and an authentication module executable by the processor adapted to generate the comparison verification value using information stored in memory. The authentication computer determines whether to authorize the financial transaction based on whether the comparison verification value matches the received dynamic verification value.