Arrangements for intelligent routing of transactions via a transaction adapter are provided. In some aspects, a request for a system selected mobile transaction adapter may be received from a user computing device in a current geographic location. Responsive to receiving the request, a computing platform may generate a plurality of requests for external entity data. The computing platform may receive entity data from the one or more external entities. In some examples, the entity data from the one or more external entities may be analyzed using machine learning. For instance, one or more machine learning models may be executed to identify, based on the data, an optimal or preferred service provider and/or mobile transaction adapter associated with the identified service provider. The identified mobile transaction adapter may then be transmitted to the user computing device for installation.

Systems, methods, and computer program products are provided for providing an electronic centralized gateway switch to a plurality of network devices. The method includes assigning a resource value to a resource received from a sending user. The resource value corresponds to a value of the resource received. The method also includes receiving a resource transfer information. The resource transfer information includes intended transfer target information corresponding to an intended transfer target account associated with an intended transfer target. The intended transfer target account is associated with one of a plurality of resource entities. The method further includes connecting to the resource entity associated with the intended transfer target account based on the resource entity associated with the intended transfer target account. The method still further includes causing a transmission of the resource value to the intended transfer target account at the resource entity associated with the intended transfer target account.

Systems and methods for predicting forward market pricing for renewable energy credit based on human behavioral data are disclosed. An example transaction-enabling system may include a forward market circuit to access a forward energy credit market and a market forecasting circuit to automatically generate a forecast for a forward market price of an energy credit in the forward energy credit market where the forecast is based at least in part on a human behavior information collected from at least one human behavioral data source. The example system may further include wherein the energy credit includes a renewable energy credit associated with a renewable energy system, and a smart contract circuit to perform at least one of selling the renewable energy credit or purchasing the renewable energy credit on the forward energy credit market in response to the forecasted forward market price of the energy credit.

Systems and methods are disclosed for providing a virtual updated appraisal of a valuable asset without an onsite inspection. The appraisal system may provide attestation of the integrity of the updated appraisal generated by verifying the asset through video and image capture transmissions and geolocation data extracted from the transmissions. The updated appraisal may be configured as self-authenticating and recorded in a transaction on a blockchain, accessible via a QR code image. The updated appraisal may be stored in a blockchain wallet and configured as a non-fungible token. The geolocation data can enables the appraisal system to verify the integrity of the submission and thereby reduces the chance of fraud. In this way, updated appraisals generated by the system can increase confidence for insurance companies as to the authenticity and accuracy of the updated appraisal.

A contactless delivery system is provided. The contactless delivery system includes a contactless card storing a cryptogram containing a unique identifier associated with a user account. After entry into a communication field, the contactless card is configured to transmit the cryptogram to a server. Upon receipt of the cryptogram, the server is configured to validate and decrypt the cryptogram, and extract the unique identifier. The server can query a database for an identity of the user account using the unique identifier, generate a digital signature based on the identity of the user account, and transmit a verification notification including the identity of the user account and the digital signature.

Systems and methods for operating a vending machine and/or kiosk. The methods comprise: detecting a presence of a person in a seat of the vending machine; obtaining a full or partial body heat map for the person that was created based on sensor data generated by at least one sensor of the vending machine or at least one sensor located in proximity to the vending machine (the full or partial heat map showing relative temperatures of different parts of a body of the person); selecting at least one vending service parameter for the vending machine using information obtained based on the full or partial body heat map; and causing the vending machine to provide the person with a vending service in accordance with the at least one vending service parameter that was selected.

A computer implemented method of processing an authorization request for a transaction in a first territory associated with a payment card issued in a second territory is disclosed. The method comprises receiving, at a server of a payment network, a transaction authorization request, the transaction authorization request comprising an indication of a payment card identifier of a payment card associated with the transaction; determining, using the payment card identifier, a local nominated issuer, the local nominated issuer being an issuing authority within the first territory authorized to process authorization requests associated with the payment card; routing the transaction authorization request to a server of the local nominated issuer; and receiving a transaction authorization response from the server of the local nominated issuer.

The present disclosure relates to systems, non-transitory computer-readable media, and methods that predicts in real time (or near real time) whether an initiated network transaction is fraudulent based on a machine-learning model that intelligently weights features associated with the initiated network transaction. For example, in less than a hundred millisecond latency, the fraud detection system can determine an initiated network transaction is fraudulent based on device metadata, historical transactions, and/or other feature families. To illustrate, in one or more embodiments, the fraud detection system uses various IP distances between devices (e.g., at certain times) associated with a sender account and/or a recipient account to determine whether a given network transaction is fraudulent. By utilizing a machine-learning model to analyze these and other features, the fraud detection system can intelligently adapt to new fraud schemes, changes to fraud algorithms, and guard the network security of various network transactions in real time.

Multifactor authentication techniques described herein may allow a user to submit a recent proof of purchase as a part of a multifactor authentication process to access an account associated with a financial institution. As part of the login process, the user may submit a proof of purchase associated with a transaction. The financial institution may determine information associated with the transaction, such as a merchant associated with the proof of purchase, a time of the transaction, the last four numbers of the transaction card used, a dollar amount, or any combination thereof. If the information matches one or more records in the transaction history of the user's account, the financial institution may authenticate the user and provide access to the account. In this way, the financial institution may leverage transaction history known to the financial institution and the user to authenticate the user.

A smart card with secure and efficient image capture and analysis is provided. The card may include a non-transitory memory embedded in the housing storing computer-executable instructions. The instructions, when run on the microprocessor, are configured to capture, via the camera, an image of a building (or other suitable image), process the image via an image processing module, determine, based at least in part on the processing of the image, a payment amount and a payment recipient associated with the building. The smart card may also display payment information on the display screen. The payment information may include the payment amount and/or the payment recipient. When authorization is received via a tactile sensor, the card may execute a payment or other communication, over a payment gateway from an account associated with a user of the platform to an account associated with the payment recipient.