The Computationally Efficient Transfer Processing, Auditing, and Search Apparatuses, Methods and Systems (“SOCOACT”) transforms smart contract request, crypto currency deposit request, crypto collateral deposit request, crypto currency transfer request, crypto collateral transfer request inputs via SOCOACT components into transaction confirmation outputs. Also, SOCOACT transforms transaction record inputs via SOCOACT components into matrix and list tuple outputs for computationally efficient auditing. A blockchain transaction data auditing apparatus comprises a blockchain recordation component, a matrix Conversion component, and a bloom filter component. The blockchain recordation component receives a plurality of transaction records for each of a plurality of transactions, each transaction record comprising a source address, a destination address, a transaction amount and a timestamp of a transaction; the source address comprising a source wallet address corresponding to a source digital wallet, and the destination address comprising a destination wallet address corresponding to a destination virtual currency wallet; verifies that the transaction amount is available in the source virtual currency wallet; and when the transaction amount is available, cryptographically records the transaction in a blockchain comprising a plurality of hashes of transaction records. The Bloom Filter component receives the source address and the destination address, hashes the source address using a Bloom Filter to generate a source wallet address, and hashes the destination address using the Bloom Filter to generate a destination wallet address. The Matrix Conversion component adds the source wallet address as a first row and a column entry to a stored distance matrix representing the plurality of transactions, adds the destination wallet address as a second row and column entry to the stored distance matrix representing the plurality of transactions, adds the transaction amount and the timestamp as an entry to the row corresponding to the source wallet address and the column corresponding to the destination wallet address; and generate a list representation of the matrix, where each entry in the list comprises a tuple having the source wallet address, the destination wallet address, the transaction amount and the timestamp.

Implementations of the present specification disclose a consensus verification method, apparatus, and device. In the implementations of the present specification, for each piece of service data, if first consensus verification on the service data fails, a first node determines whether the service data satisfies a predetermined retry condition instead of directly considering the service data to be invalid. If the predetermined retry condition is satisfied, then the service data is stored as service data to be retried. The first node can perform the first consensus verification on the service data to be retried in response to determining that a predetermined retry execution condition is triggered.

A system for closing pre-authorization amounts on a virtual token account is disclosed. The system may receive a transaction authorization request for a virtual token. The virtual token may be associated with a parent transaction account, and have a virtual token ID, a token parameter, a virtual token balance, an authorized variance, and a settlement variance. The transaction authorization request may have a transaction request amount and be linked to the virtual token ID. The system may compare the transaction request amount to the virtual token balance and the authorized variance, and authorize the transaction authorization request in response to the transaction request amount being less than the virtual token balance. The system may compare the settlement variance to the virtual token balance, and expire the virtual token in response to the virtual token balance being less than the settlement variance.

Systems and methods build blockchains and verify assets for smart contracts. A system includes a memory, a blockchain, a set of nodes, a set of verifiers, a set of miners, and a consensus protocol. The memory can have a block data structure representing a transaction for an asset having an identifier and at least one verifiable characteristic. The consensus protocol can include rules for: receiving the stake at risk from the verifiers, providing the reputational score to the verifiers, verifying the verifiable characteristic of the asset by the verifiers, cryptographic verification by the miners, adding the new block to the blockchain by the miners, providing the reward to the miners, and distributing the copy of the blockchain to each node.

Apparatuses, methods, and computer program products are provided for generating user connections. An example method includes receiving first user account parameters associated with a first user and determining a financial deficiency of the first user account based on the first user account parameters. The method further includes receiving second user account parameters associated with a second user and determining a fulfillment opportunity of the second user account based on the second user account parameters. In response to the determined fulfillment opportunity, the method includes generating a fulfillment action from a second account of the second user to a first account of the first user in satisfaction of the financial deficiency.

A payment system includes: a payment server including a first processor including hardware; and a terminal including a second processor including hardware, and a display, wherein the first processor is configured to cause the display to display a condition for renting a vehicle, the condition being set based on credit information on a plurality of payment methods registered in a wallet system.

Embodiments provide methods and systems for detecting frauds in payment transactions made by payment instrument using spend patterns of multiple payment instruments associated with user. The method performed by server system includes accessing payment transaction data associated with a plurality of customers from a transaction database. The method includes training a first generative adversarial network (GAN) model based on the payment transaction data and a plurality of probable fraud risk conditions. The first GAN model is trained to generate simulated customer fraud behaviors. The method includes filtering, by the server system, the simulated customer fraud behaviors based on a predetermined filtering criteria. The method includes generating, by the server system, fraud risk scores for the simulated customer fraud behaviors based on a fraud risk model. The method includes extracting fraud risk rules based on a set of simulated customer fraud behaviors from the simulated customer fraud behaviors.

The present disclosure relates to an information processing device, an information processing terminal, an information processing method, and a program capable of further enhancing convenience of a settlement service. Acquired are an upper limit amount set as an upper limit for payment at a time of purchase of a desired product or service, and identification information assigned to a card used when the payment is made. Then, performed is processing of associating the identification information with and recording the upper limit amount on continuous settlement information that continuously records information regarding a settlement for a payment. The present technology can be applied to, for example, an information processing system that provides a settlement service.

In an electronic payment system according to an example embodiment of the present disclosure, when a terminal device receives, from a user, an order for filling with energy a vehicle to which energy is to be supplied, it determines whether the balance of electronic money is equal to or greater than a predetermined maximum amount of money. When the balance is equal to or greater than the maximum amount of money, the terminal device causes an electronic money management server to secure the maximum amount of money as a credit amount from the balance. After energy is supplied to the vehicle on the basis of the order, the electronic money management server deducts the cost of the energy supply from the credit amount.

Disclosed are methods, systems, and non-transitory computer-readable medium for generating recommendations regarding products. A method may include determining a set of content features including one or more product attributes; determining a set of latent features; receiving a query user identifier and a query product identifier; determining a feature vector associated with the query user identifier and the query product identifier based on the set of content features and the set of latent features; determining one or more model coefficients for a linear model; and utilizing the linear model to determine a fit score for the query user identifier and the query product identifier.