This disclosure is directed to receiving a request for attesting security of a device, determining to approve the request based on attestation data associated with the device, generating a ticket having validity conditions, and sending the ticket to the device to enable the device to receive payment data from a second device.

The disclosed embodiments provide a system that verifies user access to accounts. One example method involves: receiving a request to access a feature of a first account; obtaining, from a data repository, one or more transactions of a first account; obtaining, from the data repository, one or more transactions of a second account; matching at least one of the one or more transactions of the first account to at least one of the one or more transactions from the second account; generating a first verification of ownership of the first account by a user based on the matching at least one of the one or more transactions of the first account to the at least one of the one or more transactions from the second account; and enabling the user to access the feature of the first account based on the first verification of ownership.

Disclosed are methods and systems for enabling a package of assertions to be provided to a relying entity seeking to interact with an account. A server computer may receive, from a relying entity, a request for assertions, wherein the request for assertions includes an identifier of the relying entity and a hash of an identifier of an account. The server computer may determine an assertions model based on the identifier of the relying entity. The server computer may retrieve a package of assertions associated with the account based on the assertions model and the hash of the identifier of the account. The server computer may transmit the package of assertions to the relying entity.

Various methods, apparatuses, and media for implementing a fraud machine learning model execution module are provided. A processor generates a plurality of machine learning models. The processor generates historical aggregate data based on prior transaction activities of a customer from a plurality of databases for transactions. The processor also tracks activities of the customer during a new transaction authorization process and generates a transaction data; integrates the transaction data with the historical aggregate data; executes each of said machine learning models using the integrated transaction data and the historical aggregate data to generate a fraud score and stores the fraud score into the memory; and determines whether the new transaction is fraudulent based on the generated fraud score.

An E-commerce protocol is provided. The E-commerce protocol has been developed as a solution to malicious attacks such as credit card fraud and stealing of various financial data, wherein the malicious attacks appeared particularly in a cyber world. With the help of the E-commerce protocol, a manipulated version of user information in an E-commerce database removes security risks of compromising on E-commerce systems. Even though a user does not have to share personal information of the user with E-commerce companies, an application also eliminates a necessity of entering the user information for each online transaction.

The present invention concerns the verification and authentication of independent digital wallets and, particularly, the linking of regulated and unregulated digital wallets when there is established common ownership and a desire to achieve rapid linking of those different accounts supported across disparate platforms for inter-dependent wallet operation. System intelligence (30, 42, 46, 50) makes use of selective scraping of data, in third-party database resources (52, 54), relating to or associated with events or transaction recorded in the public (unregulated) wallet that belong to an initially unknown individual whose identity requires verification for linking purposes. In the event of a verified response to such a randomly generated query, a non-transferrable NFT is generated by the system intelligence (46) of the regulated platform (27) and these non-transferable NFTs are placed within an accessible public ledger (66) as well as the purview of the private ledger (26). When sufficient correlation of responses occurs, linking can be established. The certificates provide a record of associations and go to the credibility and integrity of transactions, documents and wallet owners.

Methods, systems, and apparatuses are described herein for improving computer authentication processes by analyzing user response times to authentication questions. A request for access to an account may be received. Transaction data associated with a user of that account may be retrieved, and a list of merchants may be generated based on the transaction data. A blocklist may be retrieved, and the list of merchants may be filtered based on the blocklist. An authentication question may be presented. The authentication question may relate to the list of merchants. User responses may be received, and response times for the user responses may be measured. Based on the response times and the response times for other users, an average response time for the merchants may be determined. Based on the average response time for a particular merchant exceeding a threshold, the particular merchant may be added to the blocklist.

A new approach is proposed to support instant merchant activation for secured in-person payment at a point of sale (POS) of a merchant. When a customer initiates an in-person payment request at a payment initiation device associated with the merchant, the payment initiation device collects both sensitive and non-sensitive portions of electronic payment transaction data for the request and encrypts the sensitive data portion for secured transmission. A payment gateway in the payment transaction process relays the data and the payment request to a payment processor for approval by an issuer and transmits only the non-sensitive portion of the data to a payment service engine for risk analysis if the payment request is approved by the issuer. The payment service engine determines if the payment request is at high risk based on risk analysis of non-sensitive portion of the data and notifies the payment initiation device and/or merchant accordingly.

Example methods, apparatuses, and systems are presented that allows a consumer to conduct a purchase backed by a volatile currency that is not recognized by a merchant as a valid form of payment, such as a cryptocurrency. A third-party payment system is configured to issue a secure, reliable token to replace a reserved amount of volatile currency that represents a reliable amount of currency that is recognized by the merchant as a valid form of payment. The third-party payment platform may issue the reliable amount of currency in the reliable token based on one or more risk factors associated with the volatile currency. After purchase, the third-party payment platform may perform a consumer settlement process at a later time, including performing a cryptocurrency blockchain verification process that typically takes at least several minutes and would be impractical to perform at the point of sale.

This application relates to apparatus and methods for identifying fraudulent transactions. A computing device receives return data identifying the return of at least one item. The computing device obtains modified strategy data identifying at least one rule of a modified strategy. The rule may be based on the application of at least one discrete stochastic gradient descent algorithm to an initial strategy. The computing device applies the modified strategy to the received return data identifying the return of the at least one item, and determines whether the return of the at least one item is fraudulent based on the application of the modified strategy. The computing device generates fraud data identifying whether the return of the at least one item is fraudulent based on the determination, and may transmit the fraud data to another computing device to indicate whether the return is fraudulent.