Systems and methods for verifying a digital title of an asset transferred via a math-based currency transaction. The method includes receiving a digital title request regarding an asset, creating a digital title for the asset in a digital title database, receiving, from a financial institution computing system, an asset transfer request regarding the asset that is the subject of the math-based currency transaction, verifying that an identity of a seller in the math-based currency transaction matches the identity of the owner of the asset. Then, responsive to the verification that the identity of the seller in the math-based currency transaction matches the identity of the owner of the asset, the method includes transmitting, to the financial institution computing system, a positive title verification and updating the identity of the asset of the digital title for the asset to match an identity of a buyer in the math-based currency transaction.

Information security processes, systems, and machines for authenticating users, wirelessly detecting a user's local devices, calculating a trust score based on the local devices, and setting a transaction limit are disclosed. An ATM or POS machine can read a card, authenticate a user, and wirelessly read MAC or other unique hardware addresses for one or more of the user's local devices. Trust scores can be calculated based on the number of local devices that are detected in relation to the number of the user's devices that are registered, the historical presence of the user's devices during prior transactions, historical usage of the ATM or POS machine, geolocating, biometric authentication(s), etc. Dynamic transaction limits, types, and rights may be set for transactions corresponding to the trust score values. Transactions may be conducted wholly or partially in a contactless fashion.

A method includes receiving a payment request that indicates a card identifier corresponding to a payment instrument to be used for payment. The method further includes determining that the card identifiers fails to satisfy at least one card activity criteria. Additionally, method includes subsequent to determining that no failed authorization attempts were performed for the card identifier within a previous time period, retrieving, from a database, a decline probability score associated with the card identifier. The method also includes based on the decline probability score, determining whether to transmit an authorization request for the card identifier prior to processing the payment request.

The present disclosure relates to a system and computer-implemented method for fulfilling an order request. The method includes receiving information regarding a transaction between a user and a merchant, and information regarding an error while processing the transaction. Further, based on a received assurance value from the merchant, requesting one or more entities for providing at least one of a partial or total of the assurance value. Furthermore, in response to the request, a contribution value is received from each of the one or more entities, where the contribution value is one of the partial or total of the assurance value. Finally, an assurance message is provided to the merchant indicating successful payment for fulfilling the order request of the user upon determining the contribution value received from the one or more entities is summing up to the assurance value.

Processing transaction requests may be considered a computationally expensive operation for a computing system such as an e-commerce platform. An aspect of the present disclosure relates to systems and methods to reduce the number of transaction requests that are received and/or processed by a computing system. This may reduce demand on the computing system's resources and potentially improve the responsiveness of the computing system. In some embodiments, a set of users is selected based on at least one defined condition for a particular transaction request. Origination of the particular transaction request on behalf of users excluded from the set of users is prevented in order to reduce the number of the particular transaction requests that are received and/or processed by a corresponding computing system.

Aspects described herein may allow for authenticating a user by generating a customized set of authentication questions based on spending patterns that are automatically detected and extracted from user data. The user data may include transaction data collected over a period of time that may indicate the types of merchants that a user frequently transacts with. By automatically detecting user patterns that correspond to user behavior over a period of time, an authentication system may be able to generate authentication questions about those spending patterns that are easily answerable to an authentic user but difficult to guess or circumvent for any other user.

Provided is a computer-implemented method for real-time automatic authorization of a payment transaction that is independent of an authorization input from a consumer. The method may include receiving first data associated with a consumer, generating a payment transaction classification model based on the first data associated with the consumer, receiving second data associated with the consumer, determining whether to process a payment transaction in real-time between the consumer and a merchant independent of an authorization input received from the consumer using the payment transaction classification model and the second data associated with the consumer, and processing a payment transaction between the consumer and the merchant based on determining to process the payment transaction in real-time between the consumer and the merchant.

Methods, systems, and apparatuses are described herein for authenticating access to an account using questions which allow users to provide textual information about transactions conducted by an account. A machine learning model may be trained to predict the guessability of merchants. A request for access to an account may be received, and transaction data for that account may be received. An authentication question may be presented. For example, a user may be prompted to list places they have shopped recently. A user response comprising text data may be received. The text data may be processed to identify one or more merchants. If the one or more merchant(s) are represented in the transaction data, the machine learning model may be used to determine the guessability of the one or more merchants. An authentication score may be determined based on the guessability, and access to the account may be provided.

A computerized method (200) of performing a purchase and an associated communication system are disclosed. A customer mobile computing device (CMCD) communicates (210) with a server computing device (SCD) to generate an order for the purchase. The server computing device (SCD) communicates (220) with a payment processor computing device (PPCD) to perform a first part of a payment transaction for the purchase, wherein the first part of the payment transaction involves reserving funds for the purchase. A merchant computing device (MCD) performs (230) a digital handshake procedure with the customer mobile computing device (CMCD). The digital handshake procedure involves short-range wireless data communication to verify spatial proximity between the customer mobile computing device (CMCD) and the merchant computing device (MCD). When spatial proximity has been verified, the merchant computing device (MCD) communicates (240) with the server computing device (SCD) to accept the order. The server computing device (SCD) communicates (250) with the payment processor computing device (PPCD) to perform a second part of the payment transaction, wherein the second part of the payment transaction involves capturing funds for the purchase.

A trans-boundary water resource usage detection method, system, and computer program product, including predicting an estimated water usage by an upstream administrative region using a machine learning model and a tracked water usage, detecting an excess water usage when the estimated water usage exceeds a contracted usage value by more than a threshold value by executing a smart contract on blockchain, and penalizing, via a token exchange in blockchain, the upstream administrative region for the excess water usage by executing the smart contract on blockchain.