Ncr Corporation

Ncr Voyix Corporation

Ncr Atleos Corporation

Christopher John Costello

Matthew Robert Burris

Gregory Joseph Hartl

Sudip Rahman Khan

Caleb Wayne Martinez

Jodessiah Sumpter

John Fredrick Crooks

Itamar David Laserson

Norman Leonard Trujillo

Brent Vance Zucker

Yehoshua Zvi Licht

Sik Piu Kwan

Yoshitaka Utsumi

Gregory Scott Egan

Steve Pixton

Levino Felix Perrucci

Si Ha

Brian Robert Compau

Vreeland Phillip Tharp

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

Images are captured of a customer during a transaction at a transaction terminal along with images associated with items of the transaction and any bags or cart used to hold the items. The images are processed to track any movement and locations of the customer, items, bags, and cart relative to a known location of the transaction terminal. When a transaction payment is required for the transaction and movement is detected in a direction that is moving away from the transaction terminal before a payment notification is received for the transaction, one or more alerts are raised as an indication to staff and/or security systems of a potential in-progress walk-away theft.

Person transaction tracking

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 mapping of a physical environment and objects within the physical environment are generated. The objects are tracked within the physical environment and any transaction data associated with transaction correlated with the objects. The objects, relationships between each object, and any transaction data are evaluated to assign a risk score or an assessment needs score. Each score is mapped to one or more unique visual features and a heat map is generated that depicts the objects within the physical environment along with their visual features. The heat map is continuously updated in real time as scores change for the objects and the visual features change. The heat map is rendered within an interface of a device operated or worn by an attendant to assist the attendant in quickly ascertaining any risk of loss, any risk of threat, and/or any customer in need of assistance within the physical environment.

Real-time risk tracking

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

Item images and item information for an item identified as being associated with a potential theft during a transaction at a transaction terminal are sent in real time to an alert controller of a management terminal. The item images and item information with transaction details are presented on a display for resolution by a clerk operating the management terminal. A timer is also set and a confidence score calculated representing a confidence level that the item is the subject of theft. When the timer expires and there is still no resolution provided by the clerk a decision is made as to whether to interrupt the transaction processing on the transaction terminal for assistance or whether to permit the transaction to complete on the transaction terminal based on the calculated confidence score.

Alert controller for loss prevention

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 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.

Cross-entity channel integration services

Payment card slot tampering at a transaction terminal 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 terminal on an area adjacent to and in front of a card slot for a card reader of the terminal. The images are analyzed for determining whether hands of arms for an operator of the terminal are performing actions that indicate the operator may be attempting to install a card skimmer/shimmer into the card slot and/or attempting to remove an existing skimmer/shimmer from the card slot. When card slot tampering event is detected at the terminal a variety of automated actions are processed, such as shutting down the card reader, shutting down the terminal, confiscating any payment card inserted into the card slot, notifying a financial institution, and/or notifying legal authorities.

Hand action tracking for card slot tampering

Visual features of a vehicle, a vehicle's orientation with respect to a transaction terminal, and an individual associated with the vehicle are derived from video captured of the terminal and a surrounding area of the terminal. Additional information associated with brute force attacks in a location associated with the terminal are obtained as additional features. The visual features and the additional features are provided as input to a trained Machine-Learning Model (MLM) and the MLM provides as output a confidence value representing a prediction as to whether the current vehicle and the current individual are potentially about to engage in a brute force attack on the terminal. When the confidence value exceeds a threshold value, enhanced feature detection is enabled on the video, external systems are notified, and an incident packet of information is assembled.

A cross-entity and cross-retailer platform is provided that captures transaction data, indexes, and stores the data in a cloud-accessible data store. A service is provided that custom processes retailer and entity-defined workflows based on purchase transactions using the data store. The service also generates and maintains correlations between items, the transactions, geographical locations, retailers, and stores of the retailers. The correlations are provided as timely retail recommendations to the retailers and entities for suggested changes that are likely to optimize purchase transactions. 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

Suwanee, GA, United States of America

Christopher John Costello