Abstract: Systems and methods for digital identity verification are disclosed. In one embodiment, in an information processing apparatus comprising at least one computer processor, a method for digital identify verification may include: (1) receiving, from a user electronic device or at a website, an image of an identity document for a user, the identity document comprising an image of the user; (2) processing the identity document with at least one business-specific rule; (3) extracting identity information from the identity document; (4) determining a match rate of the image of the user on the identity document to a captured image; (5) assigning a verification score to the user based on extracted identity information and the match rate; and (6) publishing the verification score to at least one system.

Abstract: This disclosure relates to systems and methods for constructing a customized debt reduction plan for a user. In some implementations, a customized debt reduction system obtains a plurality of financial attributes of the user and a plurality of other users, where the plurality of financial attributes are indicative of credit card debt, and identifies users from the plurality of other users who successfully repaid their credit card debt based on their respective financial attributes and one or more repayment techniques that resulted in successful repayment of their credit card debt. The customized debt reduction system correlates the plurality of financial attributes of the user with the plurality of financial attributes of a number of the identified users and determines a personalized score for the user, using a trained machine learning model, based on the correlation to determine a customized debt reduction plan for the user based on the personalized score.

Abstract: Systems and methods for offering and purchasing tokenized securities on a blockchain platform meeting current and future federal, state, and offering and holding entity rules and regulations. Tokenized securities purchased during or after the tokenized securities offering are tradable on a secondary market. The server computer of the tokenized securities provides an automated transfer capability for tokenized securities holders.

Abstract: A method and apparatus for improving the management of cash and liquidity of an organization utilizing a plurality of currency accounts is described. The improvements optimize the interest earnings for the cash balances in each currency account, and minimizes the expenses related to funding the currency accounts. Machine learning techniques are incorporated to forecast payments, receipts, interest rates and currency exchange rates, and then cash is transferred or borrowed or loaned to fund the payments and utilize available cash.

Abstract: Embodiments of the invention make consumer application adoption more efficient by giving suppliers access to the desired target audience by displaying the applications to the right audience. Suppliers can provide criteria for the kinds of users they are looking to target using constraints. Embodiments of the invention enable viewers that match the constraints to see the service. The user gets to see an automatically generated application set, that is instantly available, with a high probability of containing the application the user is likely to seek. Identity and Payment support are built into the platform, such that the user no longer needs to register with each application or set up payment with each application. In addition, the platform reduces bandwidth consumption, storage front print, and power consumption of the user device by choosing when and which modules to download to the user device.

Abstract: Example embodiments relate to transaction authentication using biometric inputs from multiple users. The biometric inputs are input via a single computing entity simultaneously or within a configurable time period. The biometric inputs can be used to generate a transaction authentication record to authenticate the transaction.

Abstract: An electronic device generates a dynamic security code for a card transaction, e.g. a card not present transaction. The electronic device receives a user request to generate a dynamic security code. The electronic device sends a time request to a time source and receives a message including a time from the time source. The electronic device determines an authenticity of the message containing the time and computes the dynamic security code based on the time received in the message and a key stored at the electronic device. The electronic device causes the dynamic security code to be displayed on a display of the electronic device. The electronic device may be capable of computing a dynamic security code for a plurality of different cards. The electronic device may be a smart phone, a tablet, or a personal computer.

Abstract: A computer-implemented method associated with a payment service provided by a payment server, comprising processing, by the payment server, a payment for a point-of-sale (POS) transaction using a payment instrument associated with a user account maintained in a data store of the payment server. The payment server determines a reward configuration stored in the user account, wherein the reward configuration includes settings to reward the user account with cryptocurrency assets and is based on historical transaction activity associated with the user account. The payment server calculates an amount of cryptocurrency assets according to the reward configuration, wherein the amount of the cryptocurrency assets is based on a value of the cryptocurrency at a time of the transaction. The payment server assigns the amount of cryptocurrency assets from a cryptocurrency wallet of the payment service to a cryptocurrency wallet of the user.

Abstract: A graphical structure model trained by using labeled samples is obtained. The graphical structure model is defined based on an enterprise relationship network that includes nodes and edges. Each labeled sample includes a label indicating whether a corresponding node is a risky credit node. The graphical structure model is configured to iteratively calculate an embedding vector of at least one node in a hidden feature space based on an original feature of the at least one node and/or a feature of an edge associated with the at least one node. An embedding vector corresponding to a test-sample is calculated by using the graphical structure model. Credit risk analysis is performed on the test-sample. The credit risk analysis is performed based on a feature of the test-sample represented in the embedding vector. A node corresponding to the test-sample is labeled as a credit risk node.

Abstract: A method for rendering results of an audit includes receiving data corresponding to the results of the audit. The data includes an image to be rendered on a display screen of an electronic computing device. The data includes one or more insights derived from the results of the audit. A user of the electronic computing device is identified. The image is rendered on the display screen. One or more insights derived from the results of the audit are rendered on top of the image on the display screen. A content of the one or more insights derived from the results of the audit that are rendered on top of the image on the display screen is dependent upon the identity of the user of the electronic computing device.

Abstract: One or more implementations of the present specification provide risk control of transactions based on a graphical structure model. A graphical structure model trained by using labeled samples is obtained. The graphical structure model is defined based on a transaction data network that includes nodes representing entities in a transaction and edges representing relationships between the entities. Each labeled sample includes a label indicating whether a node corresponding to the labeled sample is a risky transaction node. The graphical structure model is configured to iteratively calculate an embedding vector of the node in a latent feature space based on an original feature of the node or a feature of an edge associated with the node. An embedding vector of an input sample is calculated by using the graphical structure model. Transaction risk control is performed on the input sample based on the embedding vector.

Abstract: Systems and methods are disclosed herein relating to payment processing systems. Payment processing systems facilitate financial transactions between customers and vendors. Cash-enabled payment processing systems facilitate transactions by those without bank accounts or who choose to use a cash-based system. Communication between vendors and customers simplifies invoicing and encourages payment.

Abstract: A method and apparatus for improving the management of cash and liquidity of an organization utilizing a plurality of ledger accounts and a plurality of currency accounts is described. One improvement in the accuracy of the forecasts comes from the uses of individual ledger accounts. The improvements optimize the interest earnings for the cash balances in each currency account and minimizes the expenses related to funding the currency accounts. Machine learning techniques are incorporated to forecast payments, receipts, interest rates, and currency exchange rates, and then the cash is transferred or borrowed or loaned to fund the payments and utilize available cash.

Abstract: A service engine determines that an entity meets a first nexus establishment condition for a first domain and a second nexus establishment condition for a second domain. The service engine then computes a first selected resource for the first domain and a second selected resource for the second domain. When the service engine determines that the entity no longer meets the second nexus establishment condition for the second domain, the service engine determines a nexus-ending date for the second domain. Prior to the nexus-ending date being satisfied, the service engine continues to compute the first selected resource for the first domain and the second selected resource for the second domain. In response to the nexus-ending date being satisfied, the service engine computes the first selected resource for the first domain but does not compute the second selected resource for the second domain.

Abstract: A method for translating transaction messages includes receiving, by a server from an acquirer, an inbound transaction message that is associated with a transaction and pursuant to a first message format supported by the acquirer. The server translates the inbound transaction message from the first message format to a second message format supported by the server when the first and second message formats are different. The server processes the inbound transaction message having the second message format and generates an outbound transaction message having the second message format. The server translates the outbound transaction message from the second message format to a third message format supported by an issuer that corresponds to the transaction when the second and third message formats are different, and transmits the translated outbound transaction to the issuer for processing the transaction. Thus, the method allows the server to translate transaction messages between different message formats.

Abstract: Systems and methods relating to generating trackable transaction requests are disclosed. A financial institution computing system includes a customer database storing financial information and tracking information, a network interface circuit enabling the financial institution computing system to exchange information over a network, and a transaction circuit generating trackable transaction requests across a plurality of financial institutions. The transaction circuit receives financial information from an originator computing system over the network and generates a corresponding transaction request including a transaction identification code. The transaction request is transmitted to a correspondent institution over the network and tracking information is received from at least one correspondent institution. The tracking information is provided to the originator computing system the transaction circuit settles the transaction request.

Abstract: Systems, methods, and apparatuses described herein relate to a method for delivering cash by an unmanned vehicle to a plurality of customers at different locations. The method includes receiving cash delivery requests from user devices of the plurality of customers via a communications network. The method includes determining a path for the unmanned vehicle from a current location of the unmanned vehicle to Global Position System (GPS) locations of the user devices of the plurality of customers. The method also includes instructing each of the plurality of compartments of a cash container of the unmanned vehicle to open in response to authenticating a corresponding customer of the plurality of customers or a corresponding user device of the user devices that generated a corresponding cash delivery request for which each of the plurality of compartments is storing cash.

Abstract: Systems and methods for offering and purchasing tokenized securities on a blockchain platform meeting current and future federal, state, and offering and holding entity rules and regulations. Tokenized securities purchased during or after the tokenized securities offering are tradable on a secondary market. The server computer of the tokenized securities provides an automated transfer capability for tokenized securities holders.

Abstract: Systems and methods for offering and purchasing tokenized securities on a blockchain platform meeting current and future federal, state, and offering and holding entity rules and regulations. Tokenized securities purchased during or after the tokenized securities offering are tradable on a secondary market. The server computer of the tokenized securities provides an automated transfer capability for tokenized securities holders.

Abstract: Techniques are described for managing devices, such as Internet of Things (IoT) devices, using smart contract(s) on a distributed ledger (e.g., blockchain). Smart contract(s) executing on a distributed ledger may control access to one or more devices in a home or other environment. The smart contract(s) may employ information stored on the distributed ledger and information in a transaction sent to the smart contract(s) to determine whether particular user(s) and/or process(es) may access the device(s), issue commands to the device(s), access data generated by the device(s), and/or control the device(s). The smart contract(s) may provide a secure portal through which user(s) and/or service(s) may access device(s) for command and control of such device(s), and secure access may be based on permission information that is specified or provided by an owner or operator of the device(s) and that is stored on the distributed ledger.