Abstract: Methods, systems and device for verifying a transaction in a loyalty or advertising system are described. One such method includes: receiving, at least one processor, transaction data associated with a transaction between a customer and a merchant; determining, at the at least one processor, from the transaction data whether the customer and the merchant are associated with the loyalty or advertising system; and upon determining from the transaction data whether the transaction corresponds to a reward or advertisement, triggering the redemption of the reward or advertisement.

Abstract: A system and computer-implemented method for approving a dynamic mortgage application. In one aspect, the method may include determining a customer is approved for a mortgage and determining a real estate property is mortgage ready, including calculating an appraisal value for the real estate property based upon the information about the real property retrieved from a computer file or memory location/address (such as by using a machine learning or artificial intelligence algorithm). The method may still further include comparing the calculated amount the customer is approved for a mortgage loan with the calculated appraisal value of the real estate property; and approving the mortgage application of the customer for the real estate property when the calculated amount the customer is approved for the mortgage loan meets, or exceeds, the calculated appraisal value of the real estate property.

Abstract: A claim adjudication system including an automatic adjudication pipeline that uses pipeline rules to automatically adjudicate a claim associated with a benefit plan at one or more stages. The automatic adjudication pipeline can redirect the claim to a user interface for manual review when a pipeline rule associated with a manual review condition is triggered. The user interface can present information about the claim relevant to the manual review condition in an integrated format, including highlighting the reasons for the manual review. A user can evaluate the claim in the user interface and provide user input that addresses the manual review condition, and the claim can be routed back to the automatic adjudication pipeline. The user input can also be used as training data for machine learning to adjust pipeline rules that are used to automatically process claims and to redirect future claims for manual review.

Abstract: Among other things, instructions stored in a tangible storage medium are executable by a processor to receive data representing an attitude of a vehicle being driven relative to a frame of reference and process the received attitude data to determine a risk factor in the driving of the vehicle.

Abstract: A method of reducing a future amount of electronic fraud alerts includes receiving data detailing a financial transaction, inputting the data into a rules-based engine that generates an electronic fraud alert, transmitting the alert to a mobile device of a customer, and receiving from the mobile device customer feedback indicating that the alert was a false positive or otherwise erroneous. The method also includes inputting the data detailing the financial transaction into a machine learning program trained to (i) determine a reason why the false positive was generated, and (ii) then modify the rules-based engine to account for the reason why the false positive was generated, and to no longer generate electronic fraud alerts based upon (a) fact patterns similar to fact patterns of the financial transaction, or (b) data similar to the data detailing the financial transaction, to facilitate reducing an amount of future false positive fraud alerts.

Abstract: The following relates generally to light detection and ranging (LIDAR). In some embodiments, a homeowners insurance quote is produced based upon data received from a LIDAR camera. For instance, in some embodiments, a system: receives light detection and ranging (LIDAR) data generated from one or more LIDAR cameras; analyzes the LIDAR data to determine or identify one or more features or characteristics of a home; and generates an electronic homeowners insurance quote based upon, at least in part, the one or more features or characteristics of the home determined or identified from the LIDAR data.

Abstract: A method receives an electronic image and uses the image as an input to a neural network. Based on a determination that the image represents a document, the method uses the image as an input to another neural network to identify a portion of the document containing an identifier. The method extracts the identifier by performing character recognition on the identified portion and determines whether the identifier is valid by using a validation API to determine whether the identifier is associated with a valid account at an institution. Based on a determination that the identifier is associated with a valid account, the method authorizes a transaction associated with the identifier. Based on a determination that the identifier is not associated with a valid account, the method denies the transaction. The first neural network classifies the electronic image into one of multiple valid document types and an invalid document type.

Abstract: An activatable spoilage monitoring device (2) is housed in a lid for a container. The device comprises a reservoir containing a digestor fluid and a tray (62) containing a digestible material or gel and having a tactile pattern of protuberances (68) formed in a base of the tray. The two parts (4, 6) of the lid axially compress together as the lid is opened resulting in activation of the device by permitting the fluid to come into contact with the digestible material.

Abstract: A media enhanced shopping cart system comprises a shopping cart, a locationing component, and a display component for displaying at least one advertisement for a product based on the location of the shopping cart within the store, wherein the locationing component is further operable to determine a location of the product within the store relative to the shopping cart, and wherein the display component is further operable to display an indication of the location of the advertised product relative to the location of the shopping cart.

Abstract: A method for selecting an AI solution for an automated robotic process including receiving at least one functional media including information indicative of brain activity by a human engaged in a task of interest, analyzing the functional media, identifying an activity level in at least one brain region, identifying a brain region parameter and an activity parameter; identifying an action parameter based in part on the brain region parameter or the activity parameter; and selecting a component of the AI solution in part on the brain region parameter, the activity parameter, or the action parameter.