Ncr Corporation

Ncr Voyix Corporation

Ncr Atleos Corporation

Matthew Robert Burris

Christopher John Costello

Jodessiah Sumpter

Gregory Joseph Hartl

Sudip Rahman Khan

Caleb Wayne Martinez

Andrew Cohen

Jason Robert Dyer

Itamar David Laserson

Shelby Frances Apps

Gary C Dalton

Norman Leonard Trujillo

Shelby Apps

Stefan Bjelcevic

Brian Robert Compau

An item return transaction for an item is identified at a transaction terminal. The item is authenticated using multiple factors at least some of which are independent of item code identification for the item. A fraud score is calculated based on the multiple factors, item code identification, and data that is specific to a customer associated with the transaction, specific to the item, specific to a store associated with the transaction terminal, and specific to a retailer associated with the store. The fraud score and a customer-return grade for the customer are processed to determine whether the transaction can complete at the terminal without assistance or whether the transaction is to be held in abeyance for an audit (onsite audit or remote network-based audit). In an embodiment, the t terminal is a Self-Service Terminal (SST) and the transaction is a self-item return transaction conducted by a customer at the terminal.

Self-service terminal (SST) item return anti-fraud processing

A first device is detected within a geofenced area of an establishment. A second device is determined to be within the geofenced area. A first individual associated with the first device is instructed to enter the establishment and complete a first portion of opening security procedures associated with an opening of the establishment. Upon completion of the first portion, a second individual associated with the second device is instructed to enter the establishment for a second portion of the opening security procedures. The first individual and the second individual are monitored through video feeds during the first portion and the second portion of the opening security procedures for compliance with the opening security procedures.

Frictionless security processing

A server obtains real-time video depicting an area that includes a terminal. The server analyzes the video for depictions of a vehicle and objects associated with attacks on terminals, A server provides factors associated with the analysis to a machine learning model (MLM). The server receives a confidence value as output from the MLM. The server sends an alert when the confidence value exceeds a threshold as an indication that a potential attack on the terminal may be in progress.

Monitoring and predicting physical force attacks on transaction terminals

An asset is identified in a predefined area. The type of asset is identified through video or wireless tag identification. A security policy associated with the type of asset is obtained. Entries in an asset log are recorded based on a location of the asset, an individual handling the asset, and/or actions taken by an individual with respect to the asset based on the security policy. A real-time notification is sent when the location, the handling, and/or any of the actions warrant a notification based on the security policy.

Asset tracking and notification processing

An item return for an item is identified and a workflow is determined based on first factors defined in customized rules. Resources associated with the workflow may be staged on devices associated with the item return and the workflow is initiated. When the item is detected as being present at a drop-off location for the item, item and customer information are gathered in accordance with the customized rules associated with the workflow. Security checks are processed using second factors defined in the customized rules. A decision is made based on the security checks as to whether the item return can continue processing with the workflow or as to whether an item return exception is to be raised for evaluation and/or inspection of the item and item return information collected before the item return exception was raised.

Item return architecture and processing

A monitoring project is defined interactively through an interface. Resources needed for the project are obtained, configured, arranged, and verified within a target area. Video and audio feeds are captured and analyzed during a project period within the target area and customer interactions and intentions are derived from detected customer behaviors within the feeds. The intentions and behaviors are indexed with aggregated metrics within a data store. The interface provides custom queries, reports, interactive graphics, and real-time notifications from the data store that depict the custom aggregated metrics for the intentions and behaviors of the monitoring project.

Monitoring of a project by video analysis

A user makes a request from a requesting device for access to a secure operation associated with a network-based service. A first biometric authentication is processed for the request and at least one second scope-based authentication is processed for the request based on an analysis of a physical environment for the requesting device. A determination is made based on at least the first biometric authentication and the scope-based authentication whether the secure operation can be: processed on behalf of the user by the network-based service, not processed at all, or processed only if requested from a specific medium/channel associated with a specific device, which may or may not be the requesting device.

Multi-factor secure operation authentication

Security video is captured when one or more individuals are detected as entering a secure area. Actions of the one or more individuals are monitored based on security policies associated with the secure area. Identifiers for the one or more individuals and action identifiers for the actions are recorded in a security log while the one or more individuals remain in the secure area. The security video is stopped when the individuals are detected as exiting the secure area. The security video is linked to entries recorded in the security log. In an embodiment, when a non-compliant action is detected from the actions based on the security policies, a real-time alert is raised, and/or the security video is streamed in real time to a security monitor.

Security audit and notification processing

Cash trapping at an Automated Teller Machine (ATM) is detected in real time. One or more images from one or more cameras are analyzed. The camera(s) is/are focused overhead of the ATM or on a cash slot of a dispense module for the ATM. The images are analyzed for determining one or more of whether the dispenser module is authentic, whether the cash slot opened or did not open when it should have opened for a cash withdraw, whether visual features of the dispense module have changed over a configurable period of time, and whether hands, gestures, and actions of a person present at the ATM indicate that cash trapping is taking place at the ATM. When cash trapping is detected at the ATM a variety of automated actions are processed, such as shutting down the dispense module, shutting down the ATM, notifying a financial institution, and/or notifying legal authorities.

Currency trapping detection

A pre-staged or in-person provided order is received from a customer location. Order details are sent to a fulfillment terminal and items associated with the order are prepared or collected. The items are loaded into an autonomous device. The autonomous device plans a route from its current location to the customer location and the autonomous device navigates from its current location to the customer location using the route. The customer is verified at the autonomous device and a secure bin is unlocked by the autonomous device. The customer removes the items associated with the order from the unlocked secure bin, and the autonomous device navigates back to its original location within an enterprise.

Autonomous delivery

A consumer is identified engaged in an activity at a specific physical location. A context is formulated for the consumer based on the activity, the location, preferences associated with the consumer, and a history associated with the consumer. A natural language voice-based assistance session is initiated with the consumer. The session follows the consumer as the consumer travels and remains engaged in the activity. In an embodiment, the session is seamlessly maintained and is seamlessly transferred from a plurality of different devices as the consumer is engaged in the activity and travels. In an embodiment, the session is initiated without the consumer requesting the session.

Personalized voice-based assistance

An identity of a customer within an establishment is authenticated using a variety of captured biometric features obtained from sensors and/or video. Video capturing movements/interactions of the customer is analyzed in real time to identify the customer's behavior and actions. Any staff of the establishment who interact with the customer are identified from the video. Transaction data and other data retained for the customer by the establishment are aggregated and linked with the video and the customer identity. The linked data is analyzed in combination with the customer behavior and actions to determine responses within the establishment to customer-initiated transactions. In an embodiment, the customer is authorized to perform at least one transaction within the establishment based on the authenticated identity and linked data without a presentation by the customer of an identification card, a Personal Identification Number (PIN), a password and/or verification by a staff member.

Frictionless authentication and monitoring

A consumer is identified at a transaction terminal. A natural-language voice chatbot is initiated for the transaction. The chatbot is configured with store information for a store associated with the terminal and, optionally, with preferences registered to the consumer. A natural language voice dialogue using, at least the store information, is initiated between the chatbot and the consumer while the consumer is at the terminal and during the transaction. The consumer may order store items from the store and pay for the items through the dialogue. In an embodiment, the items ordered are delivered to the terminal where the consumer is located.

Voice-based transaction terminal ordering

A cross-entity and cross-retailer platform is provided that captures transaction data (and/or browser history data associated with online browser-based transactions), indexes, and stores the data in a cloud-accessible data store. A cloud service is provided that custom processes retailer and entity-defined workflows based on purchase transactions using the data store. The service discovers and updates trends and patterns associated with item sales for a given retailer or for a given entity across channels associated with in-store and online item sales. The trends and patterns are dynamically reported to the corresponding entity or the corresponding retailer. The entities may comprise manufacturers of an item, a supplier of the item, a distributor of the item, and a Consumer Packaging Goods (CPG) company of the item.

Growing community of inventors

Atlanta, GA, United States of America

Matthew Robert Burris