Abstract: An example operation may include one or more of receiving a loan application of a user, extracting a plurality of personal attributes about the user from the loan application, querying a machine learning model via an application programming interface (API) based on the plurality of attributes about the user to identify one or more rules for auto-adjudicating the loan application, determining whether or not to approve the loan application based on the one or more rules identified via the machine learning model, and transmitting notice of the determination to a device associated with the user.

Abstract: An apparatus, method, and non-transitory medium for betting on weather predictions are disclosed herein. A plurality of longitude and latitude coordinate pairs may be received from a remote device. The display device may render data representing a binary option based on whether a storm will make landfall within the certain radius. A request to purchase the binary option may be received. It may be determined whether the landfall location corresponds to a zip code associated with the given longitude latitude pair in the memory.

Abstract: A computer-implemented system and method of tracking telemetry data at a financial computing system is presented. The system and method includes receiving an electronic message that includes a payment transaction originating from a payment terminal, and associating a unique transaction identifier to the payment transaction. Telemetry data for the payment transaction is received from payment processing applications through a telemetry interface and aggregated into a data store. The aggregated telemetry data associated with the unique identifier is presented on a user interface by the financial computing system.

Abstract: A payment method includes a cloud application instance sending an order and a device identity to a payment management node. The payment method further includes the payment management node recording a correspondence between the order and the device identity. The payment method further includes the cloud application instance sending an order payment request to a terminal device. The payment method further includes the terminal device sending, to the payment management node based on the order payment request, an order obtaining request carrying the device identity. The payment method further includes the payment management node obtaining the order from the correspondence based on the device identity carried in the order obtaining request, and sending the order to the terminal device. The payment method further includes terminal device receiving and processing the order.

Abstract: In embodiments of the present invention, methods are provided for maintaining a plurality of public addresses, and a plurality of virtual representations of a plurality of respective items. For each virtual representation, a set of digital tokens may respectively correspond to an item represented by the virtual representation, and each digital token may be cryptographically linked with the corresponding virtual representation. Owners of a token may request redemption of the digital token and have ownership information and fulfillment details verified. Fulfillment details may be provided to a fulfillment system that satisfies transactions for items.

Abstract: Systems and methods for identifying a user to a merchant include creating a token for the user, the token identifying the user and user information of the user, where creating the token includes generating a string based on a user biometric and hashing the string to generate a hashed string, sending a notification indicating that a merchant requests the user information of the user, sending the token to a user device associated with the user where the token is configured to be activated via the user device before the token is selectively transmitted by the user device, receiving the token from a merchant computing system associated with a merchant, identifying the user and the user information based on the received token, receiving an indication from the user device, and withholding the user information from the merchant computing system based on the indication.

Abstract: Techniques for identifying a fraudulent interaction of a user device using time based risk features are described herein. In embodiments, time stamp information provided by an external clock and time units may be maintained by a user device. The user device may include an authentication component that is communicatively coupled to a clock component that generates the time units. In response to conducting an interaction with an access device and user device first time information may be received from the access device. Second time information may be determined based at least in part on the time units from the clock component and the time stamp information. The second time information may be compared to the first time information. An authentication plan for the interaction may be determined based at least in part on the comparison of the second time information to the first time information.

Abstract: Aspects of the present disclosure are directed to method for facilitating a transaction between a service provider and a customer using an online payment platform. The method includes receiving a request from a customer's device to enter into a transaction with a service provider and receiving a request from a service provider's device to process a cardless payment transaction for the transaction. The method further includes determining a tipping process to be applied to the transaction whereby an automatically determined tip amount or a manually determined tip amount is added to the transaction. The processing of the transaction is delayed until the automatically determined or the manual tip amount is added to the transaction. The cardless payment including the tip amount is then processed and a confirmation thereof is communicated to the respective devices of the customer and the service provider.

Abstract: Embodiments provide artificial intelligence-based methods and systems for predicting account-level risk scores associated with cardholders. Method performed by server system includes accessing payment transaction data and cardholder risk data associated with cardholder. The payment transaction data includes transaction variables associated with past payment transactions performed at Point of Interaction (POI) terminals within a particular time window. Method includes generating cardholder profile data based on the transaction variables and the cardholder risk data. Method includes determining account-level risk scores associated with the cardholder based on cardholder profile data. Each account-level risk score of account-level risk scores is determined by a trained machine learning model. The account-level risk scores include a wallet reload risk score, an account reissuance risk score, and a transaction channel risk score.

Abstract: Apparatus and associated methods related to generate at least one quotation request from records related to tangible property. In an illustrative embodiment, a signal corresponding to input from a user identifying a real environment is received. For example, the user may transmit a quotation request associated with the real environment. Based on the quotation request, for example, identify information related to the real environment based on predetermined requirements associated with at least one API related to a type of the request. For example, at least one second quotation request may be generated as a function of the information to a plurality of vendors through the at least one API. Various embodiments may perform virtual environment operations to present a plurality of records related to the real environment.

Abstract: Systems and methods for future trends forecasting based on prediction market probability estimates. Alternative simulated starting values for prediction markets are used in order to determine the preferred starting values for prediction markets to use in volumetric forecasting. A user interface that facilitates using prediction market probability estimates to determine future trends forecasts is described herein.

Abstract: In an aspect, a computer-implemented method is disclosed.

Abstract: Apparatuses, methods, computer program products, and systems are disclosed for payment processing. An apparatus includes one or more processors and one or more memories that store code executable by the one or more processors to exchange payment information for a transaction wirelessly between a mobile hardware computing device of a user and a hardware payment terminal for a merchant, to validate an availability of funds for the transaction using an electronic interface for an account for the user at a third-party institution, and to electronically transfer the funds directly from the account for the user to an account for the merchant to complete the transaction.

Abstract: Systems and methods for fraud monitoring are disclosed, including: receiving a transaction request associated with a first instrument of a user; extracting, characteristics of the transaction request; identifying, by the first processor, user data based on the transaction request; determining a fraud severity value and notification value based on inputting the characteristics and user data into a fraud machine learning model; performing a first fraud action based on the fraud severity value; wherein the first fraud action is at least one selected from the group of locking the first instrument for a period of time, deactivating the first instrument, and electronically transmitting a first query message to a user device associated with the first instrument; and transmitting a fraud notification based on the notification value, wherein the fraud notification includes severity information associated with the fraud severity value.

Abstract: According to some embodiments, data may be received indicative of a plurality of insurance claims along with an indication of an appropriate claim segment classification for each insurance claim. A first claim handler may then be automatically selected for a first insurance claim based at least in part on: (i) a first segment classification associated with the first insurance claim, (ii) numbers of other insurance claims currently assigned to claim handlers, and (iii) load factors associated with claim handlers. An indication of the selected first claim handler may then be transmitted.

Abstract: Methods, systems, and computer program products for implementing currency conversion and foreign exchange processes for an exchange payment platform system. An offer look-up request for an offer associated with a booking event is received. The offer look-up request including a first currency, a second currency, and a transaction context information. A foreign exchange rate request including the offer look-up request is provided to a foreign exchange server. A converted offer associated with a proposed foreign exchange rate is received from the foreign exchange server. A payment webpage including the converted offer is provided to the merchant. The converted offer is presented in a standard format based on formatting rules associated with the merchant.

Abstract: Illustrated herein are systems and methods of transferring physical currency into electronic credit that becomes electronically available. One method includes remotely and quickly depositing non-negotiable instruments, such as cash, by communicating information, such as an image of the currency, about the instrument to a depositor. An exemplary system includes computing devices and a capture module with a retrieval engine, a transmission engine, an inspection engine, and a conferral engine. The capture module receives information about a non-negotiable instrument, and an inspection engine analyzes the information to confirm if the unit of currency is authentic.

Abstract: This application relates to apparatus and methods for identifying fraudulent transactions. The embodiments may employ machine learning processes to detect fraudulent activity. In some examples, a computing device determines customer data and device data for a customer and device involved in a transaction. The customer data may include previous transactions by the customer, and the device data may include previous transactions involving the device. The computing device generates features based on the customer data and the device data, and applies one or more machine learning models to the generated features to generate a trust score. The trust score is indicative of how likely a transaction is to be fraudulent. In some examples, the transaction is not allowed if the trust score is beyond a threshold. In some examples, the computing device trains the machine learning models based on customer data and device data for a plurality of customers and devices.

Abstract: In a preferred embodiment of the invention, transaction systems create instruments and transaction products using a transaction product computer. The transaction product computer accepts transaction product input as a means to customize a transaction product that can be offered to end users. The platform has a product engine that accepts parameters and builds an application programming interface transaction product that enables user devices to manage and configure aspects of the transaction product and value unit transactions at the product level and on a per-transaction basis.

Abstract: The present disclosure is directed to a system, method, and computer program for funding a payment card account from an external funding gateway just-in-time for a purchase. A payment card processing system maintains a payment card account for a user for funds from a third party funding source. Funds from the funding source are controlled by an external funding gateway. In order to approve a purchase authorization transaction, the payment card account must have a positive balance equal to or greater than the purchase amount. Funding requests are sent from the payment card processing system to the external funding gateway in response to receiving a purchase authorization request for the payment card, and, if the funding request is approved by the external funding gateway, the system credits to the payment card account with the funds just-in-time for approval of a purchase authorization request.