A payment processing method uses a credit push for disbursing funds at ATM. The process can include scanning an optical code at an ATM using a mobile device to determine creditor bank information. A debtor bank server receives a funds disbursement request and provides a credit push request to a payment rail. The payment rail communicates a credit payment transaction request to a creditor bank sever. The creditor bank server identifies the ATM using an ATM identifier provided to the mobile device via the optical code. The ATM is instructed to disburse funds by the creditor bank server. The method includes using the mobile device, or other issuer domain, authentication procedures. The funds can be disbursed by the ATM without the ATM performing any authentication procedures.

Cloud-based methods and systems are presented for aggregating custom groupings of Self-Service Terminals (SSTs) and managing the SSTs through a network. Real-time information for the SSTs are gathered and interfaces are used to direct selective usage of particular SSTs within a grouping. The groupings optimized for reducing media replenishment and service of any particular SST within the grouping.

Systems, methods, and computer program products for a contactless automated teller machine (ATM) experience receive, from a telephone number, a first short message service (SMS) message including a unique identifier associated with an ATM terminal; in response to receiving the first SMS message, communicate, to the ATM terminal, a first password associated with the telephone number and the unique identifier; receive, from the telephone number, a second SMS message including the first password; verify the first password; in response to verifying the first password, transmit, to the telephone number, a third SMS message including an option to withdraw cash from the ATM terminal; receive, from the telephone number, a fourth SMS message including a selection of the option to withdraw the cash from the ATM terminal; and communicate, to the ATM terminal, a cash dispense command that causes the ATM terminal to dispense the cash.

Disclosed herein are systems and methods for deploying and/or rolling back automatic teller machine (ATM) updates. Such methods can store a back-up system image of a client operating system on a virtual hard drive. When an update is deployed from a host operating system to the client operating system, the system update may fail to install properly, and the ATM may shut down. In response, the host operating system can execute instructions to the client operating system to boot from a bootable image on the virtual hard drive. Then, the virtual hard drive can emulate, by a boot loader on the back-up system image, the client operating system on the ATM from the virtual hard drive without loading the client operating system. Then, the virtual hard drive can install a rolled-back operating system on the ATM. The rolled-back operating system can comprise the back-up system image.

This disclosure relates to an intelligent smart glasses that may be worn by a customer. The smart glasses may sense cash information on automated teller machine (“ATM”). The smart glasses may accordingly split up a cash transaction across various ATM units in close to proximity to the customer. The smart glasses may split a requested cash transactions among various ATMs so that if the desired amount/denomination of cash is not available at an ATM to the customer, the customer is seamlessly directed to one or more other ATMs that are capable of dispensing the desired amount of cash.

Disclosed herein are methods and systems to facilitate a blockchain-backed peer-to-peer transaction without requiring the recipient's personally identifiable information and without updating the recipient's blockchain. A central server may receive a transaction request from a sender and may identify a system blockchain associated with the sender. When the server determines that the sender's accounts can satisfy the request, the server generates a unique transaction token. The server then transmits the unique transaction token to the sender, recipient (if indicated within the sender's request), and one or more electronic terminals. When the server receives an indication that the recipient has inputted the unique transaction token to the electronic terminal, the server appends a block instance corresponding to the transaction to the system blockchain.

An ATM fraud detection system having a plurality of vibration sensors to detect vibration of one or more of an ATM cash dispenser, card reader, cash rejection bin, and/or cash tray. The system further having NFC sensor to detect persistent presence of wireless signal near an ATM machine. The system also includes a plurality of reed switch sensors to detect tampering of cash door, network cable-model interface, network cable-computer interface, hard disk drive-computer interface and/or ATM keyboard cable-computer interface. A micro controller is programmed to detect fraudulent ATM activity such as jackpotting, transaction reversal, shimming, skimming, cash trapping or internal theft.

A network of nodes for a distributed register, in which the nodes include interaction terminals (e.g., ATMs, recyclers, point-of-sale devices, or the like). The interaction terminals allow a user to enter into an interaction that includes transferring resources through the use of the distributed register. The interaction terminals may be utilized in order to authenticate the user using traditional authentication processes or through the use of the distributed register. The interaction terminals may determine if the interaction is for a traditional interaction or if the interaction is being used for an interaction on the distributed ledger. Since the interaction terminals are operated by the organizations, they can be registered as trusted authorities on the distributed register, and as such, the blocks created for interactions by the interactional terminals may be validated without the need for consensus algorithms, or with reduced consensus requirements.

Aspects of the disclosure relate to intelligent processing of broken or failed ATM transactions. In some embodiments, a computing platform may receive transaction data associated with a pending transaction initiated on a mobile computing device and generate hash information corresponding to the received transaction data. Then, the computing platform may identify ATMs previously visited by the user. Based on performing analytics on those previously visited ATMs, the computing platform may identify, from those previously visited ATMs, one or more alternate ATMs for completing the pending transaction. Next, the computing platform may send a notification to the mobile computing device that includes navigation information. Thereafter, the computing platform may cause the alternate ATMs to await input from the user by sending the generated hash information. In response to receiving a message indicating completion of the pending transaction, the computing platform may initiate clearing of a pending status of the pending transaction.

Aspects of the disclosure relate to ATM monitoring and enhancement. A computing platform may detect ATM performance information from an ATM. The computing platform may validate the ATM performance information against baseline ATM performance information. Based on validating the ATM performance information, the computing platform may generate a digital twin for the ATM, and may input the digital twin into a deep learning model for anomaly detection. Based on identifying that the digital twin includes an anomaly, the computing platform may update and simulate the updated digital twin. The computing platform may determine, using smart contracts stored on a distributed ledger, whether or not an update to the ATM based on the updated digital twin is approved. Based on determining that the update to the ATM is approved, the computing platform may direct the ATM to perform a configuration update based on the updated digital twin.