Abstract: A device may receive, from client devices of users, user data identifying the users, client device data identifying the client devices, and transaction card data identifying transaction cards, and may receive transaction account data identifying transaction accounts. The device may process the user data, the client device data, the transaction card data, and the transaction account data, with a machine learning model, to determine trust scores for the transaction cards, and may identify trusted transaction cards based on the trust scores. The device may receive, from trusted client devices associated with the trusted transaction cards, location data identifying locations of the trusted client devices and communication data indicating communications between the trusted transaction cards and the trusted client devices. The device may generate a card mapping for the trusted transaction cards based on the location data and the communication data, and may perform actions based on the card mapping.

Abstract: A controller of a transaction card may cause the transaction card to be in a first state. The transaction card may include a battery and at least one other component. In the first state, the battery does not provide power to the at least one other component of the transaction card. The transaction card may receive a signal from a near-field communication (NFC) device and may cause the transaction card to be in a second state based on receiving the signal. In the second state, the battery provides power to the at least one other component of the transaction card. The transaction card may perform a transaction based on the transaction card being in the second state.

Abstract: A machine learning model supported trend detection engine can be available via an application programming interface to business or community planners to evaluate the potential for new plans or ventures. The model can be based upon transaction trends and available merchant data from transactions such as location, time, merchant type, and transactions history longevity from particular retailers. The model can generate a dashboard that shows past performance, predicted future performance, trends, similarity between businesses, and profitability. The new plan or venture can be correlated with other retailers that have been established and successful under a similar model and located near another retailer similar to the new plan or venture.

Abstract: Arrangements requiring additional multi-factor authentication (MFA) in certain instances of dynamic virtual transaction token (e.g., virtual credit card token) generation via a browser extension.

Abstract: Disclosed herein are system, method, and apparatus for detecting a skimmer via a vibration sensor on a transaction card. The method includes receiving, at a server, from a user equipment, vibration information recorded by a transaction card in response to an execution of a transaction at a point-of-service (POS) terminal of a plurality of POS terminals using the transaction card. The vibration information may be recorded by a microphone or an accelerometer on the transaction card while the transaction card is swiped through the POS terminal or inserted into or removed from the POS terminal. The method includes determining, at the server, a state of the POS terminal based on the received vibration information and in response to a determination of the state of the POS being compromised, sending to one or more stakeholders of the transaction a warning message containing the POS terminal information including the POS terminal's state.

Abstract: A toll transponder may receive transaction card data identifying a transaction card associated with a transaction account. The toll transponder may provide to a toll server device, and via a toll antenna of a toll collection system, a request for a transaction amount for a vehicle toll, and may receive a response requesting authorization for payment of the transaction amount. The toll transponder may determine, based on the response, an authorization request cryptogram for payment of the transaction amount, and generate an encrypted signal identifying the authorization request cryptogram, the transaction card data, and a toll transponder identifier identifying the toll transponder. The toll transponder may provide the encrypted signal to the toll server device via the toll antenna, and may receive from the toll server device, via the toll antenna, data indicating whether the transaction amount for the vehicle toll is approved.

Abstract: An exemplary system, method, and computer-accessible medium for denying a financial transaction(s) initiated by a customer(s) can include receiving information related to the financial transaction(s), determining a transaction impairment(s) associated with the customer(s), and denying the financial transaction(s) based on the transaction limitation. The transaction impairment(s) can be a particular time period, and the computer arrangement can be configured to deny the transaction(s) if the transaction(s) is initiated within the particular time period. The particular time period can be received from the user(s). The transaction impairment(s) can be an impairment of the customer(s). The transaction impairment(s) can include a cognitive impairment.

Abstract: A device may receive application data associated with transaction applications of client devices and transaction card data associated with transaction cards. The device may receive geographical data identifying a geographical area associated with users of the client devices and the transaction cards. The device may determine, based on the application data, the transaction card data, and the geographical data, location data identifying geographical locations of the users in the geographical area. The device may determine, based on the location data, quantity data identifying quantities of the users located on multiple paths of the geographical area. The device may process the geographical data, the location data, and the quantity data, with a machine learning model, to identify a path with less than a threshold quantity of users in the geographical area. The device may perform one or more actions based on the path.

Abstract: Various embodiments are directed to techniques for ensuring that a negotiable instrument has not been altered between the time the instrument leaves the hands of the payor and when the check is presented for redemption by the payee by recording an image of the check in a data block in a blockchain and retrieving the image when the check is presented for redemption for comparison with the check. A match between the stored image and the check indicates that no alteration of the check has occurred.

Abstract: An exemplary system, method, and computer-accessible medium for providing a financial account recommendation to person(s) can include receiving a transaction history for the person(s) associated with a first financial account, determining first rewards information based on the transaction history, accessing database(s) containing rewards rates for a plurality of second financial accounts, determining second rewards information for a particular second financial account of the plurality of second financial accounts based on the transaction history, and providing the financial account recommendation to the person(s) to one of (i) keep the first financial account or (ii) switch to the second financial account based on a comparison of the first rewards information to the second rewards information.

Abstract: A fraud detection platform may receive transaction data relating to a transaction conducted by a user with a transaction card. The fraud detection platform may receive, from a biometric sensor of the transaction card, biometric data relating to one or more biometric characteristics of the user during the transaction. The fraud detection platform may receive, from an accelerometer of the transaction card, card movement data relating to a measure of shaking of the transaction card by the user during the transaction. The fraud detection platform may process the transaction data, the biometric data, and the card movement data, with a fraud detection model, to determine a fraud score associated with the transaction. The fraud detection platform may perform one or more actions based on the fraud score.

Abstract: Techniques to pre-authenticate an identity for an electronic account are described and claimed by the present disclosure. The electronic account may enforce a multi-factor authentication procedure that involves a number of steps. In addition to the electronic account, a user may have other accounts requiring authentications. Successful authentications with respect to those other accounts may provide evidence of the user's identity. If sufficient evidence is present, one or more steps of the multi-factor authentication procedure may be bypassed. Other embodiments are described and claimed.

Abstract: Logic to determine a record indicating an authentication by a first multi-factor authentication does not exist for a user in a memory. Logic to receive a request for issuance of a transaction token for a financial transaction, maintain a situation-specific predetermined value for each of a plurality of predetermined situations, and select the situation-specific predetermined value of the predetermined situation in the request, and sum a number of requested transaction tokens. And logic to retrieve the predetermined value and a predetermined number of transaction tokens, issue the transaction token, and complete the financial transaction using the transaction token issued.

Abstract: In some implementations, a device may detect loading of a first web page associated with a domain, and may create an inline frame element that references a second web page associated with the domain. The second web page may require an authenticated user session to access particular content of the second web page. The device may insert the inline frame element into code for the first web page, and may transmit a request for the second web page based on inserting the inline frame element into the code for the first web page. The device may receive a response to the request for the second web page, and may determine whether there is an authenticated user session for the domain based on the response. The device may selectively perform an action based on determining whether there is an authenticated user session for the domain.

Abstract: Various embodiments described herein are generally directed to techniques for managing fraud rules and generating authentication directions according to location data from one or more client devices. Embodiments may include using a payment server informed by a client device application to manage and/or apply fraud rules for transactions. In embodiments, fraud rules may be managed based on location data provided by a client device application and/or location data associated with at least one transaction system. In some embodiments, fraud rules may be managed based on location data provided by multiple client device applications and/or location data associated with at least one transaction system. In some embodiments, rules may be managed for an individual authorization request according to information from at least one client device application and location data for a transaction system associated with the authorization request.

Abstract: In order to facilitate electronic meeting scheduling and coordination, systems and methods are disclosed including receiving, by a processor, a plurality of electronic meeting requests to schedule a meeting. The processor determines, for each electronic meeting request, meeting room needs. A meeting scheduling machine learning model is utilized to predict parameters of meeting room objects representing the candidate meeting rooms based at least in part on the meeting room needs, schedule information associated with a respective electronic meeting request and location information associated with the respective electronic meeting request. The processor causes an indication of the candidate meeting rooms to display in response to the electronic meeting request on a screen of computing devices associated with the respective attendees based at least in part on the predicted parameters.

Abstract: A method for providing a locked electronic item includes receiving a selection of an electronic lock and the electronic item from a first computing device associated with a sender. The electronic lock includes a lock clue and a lock solution. The method includes determining an answer input field configuration that includes a number of input boxes and spaces that may be arranged to correspond to the lock solution. The method includes transmitting the lock clue and the input field configuration to a second computing device associated with a recipient for display by the second computing device and receiving an attempted lock solution from the second computing device. The method further includes transmitting the electronic item to the second computing device for display or use by the second computing device in response to determining that the attempted lock solution matches the lock solution.

Abstract: A machine learning model supported trend detection engine can be available via an application programming interface to business or community planners to evaluate the potential for new plans or ventures. The model can be based upon transaction trends and available merchant data from transactions such as location, time, merchant type, and transactions history longevity from particular retailers. The model can generate a dashboard that shows past performance, predicted future performance, trends, similarity between businesses, and profitability. The new plan or venture can be correlated with other retailers that have been established and successful under a similar model and located near another retailer similar to the new plan or venture.

Abstract: A device may obtain, from a client device associated with a customer and based on the customer joining a rewards program, item data identifying an item, of a plurality of items, placed in a shopping cart and customer data identifying the customer, obtain rewards data identifying rewards associated with the plurality of items, process the item data, the rewards data, and the customer data, with a machine learning model, to identify a reward based on the rewards data associated with the item, verify a completed purchase of the item based on data indicating an intent of the customer to purchase the item and transaction data, provide, to the client device, data identifying the identified reward based on verifying the completed purchase of the item, and retrain the machine learning model based on the identified reward.

Abstract: In order to facilitate meeting room allocation and calendaring, systems and methods are disclosed including receiving electronic meeting requests to schedule a meeting. A meeting room locator machine learning model is utilized to predict meeting room parameters of a meeting room object representing a candidate meeting room based on a meeting room needs data and location information. A meeting scheduling machine learning model is utilized to predict meeting parameters of a calendar object representing a candidate meeting time based on the candidate meeting room, schedule information and the location information. An indication of the candidate meeting room and the candidate meeting time is displayed in response to the electronic meeting request on a screen associated with each attendee. A selection of the candidate meeting room and the candidate meeting time is received from each attendee, and the candidate meeting room is dynamically secured at the candidate meeting time.