A device and a method for detecting a fraudulent financial transaction in an in-vehicle payment may include a processor that detects the fraudulent financial transaction in the in-vehicle payment based on at least one of a vehicle location, the number of vehicle occupants, a state of a communication network, a vehicle speed, whether a fingerprint authentication module is mounted, a state of a battery, a user account, and/or information on the in-vehicle payment when the in-vehicle payment is requested from a vehicle providing an in-vehicle payment function. An effect of strengthening security of the in-vehicle payment by detecting the fraudulent financial transaction in the in-vehicle payment may be provided.

A system including: one or more processors; a memory storing instructions that, when executed by the one or more processors are configured to cause the system to receive primary and secondary user account data. The system generates one or more predictive model systems based on the primary and secondary user account data. The system receives a first input from the primary user corresponding to a first spending limitation for the secondary user. The system identifies a first transaction of the secondary user exceeding the spending limitation and determines using the one or more predictive model systems whether to authorize a spending limitation override. The system automatically authorizes the spending limitation override when the first transaction exceeds the spending limitation by less than a predetermined threshold. The system can also identify and automatically fund recurring transactions with an associated funding account using the one or more predictive model systems.

The present disclosure relates to systems and methods to generate user or user group behavior similarities based on computing distances between individual users or user groups and without using demographic data, e.g., based on anonymized data. The methods include creating a multidimensional vector representation for each user in a group by summarizing user's behaviors across various categories. Based on the created vectors, distance calculation and nearest neighbor search are performed to locate users that are most similar to target users. The resulting distance metrics may be used to rank similarities. Additionally, dimensionality reduction may be performed to further distill the behavior information to make the disclosed methods suitable for a variety of analytics and modeling tasks.

This application relates to systems and methods for automatically generating fraud strategies. A system may comprise customer computing devices, a database, and retailer computing device(s). The retailer computing device(s) are configured to receive data related to customer transactions, calculate a negative reaction score, negative resolution score, anomaly score, and impact score for at least one value of the received data, determine whether the calculated scores are greater than or equal to respective thresholds, identify a value of the received data as a potentially fraudulent data value when one or more of the calculated scores is greater than or equal to its respective threshold, generate an output comprising a list of potentially fraudulent data value(s) and impact scores, identify area(s) of high impact leaks based on the output, and determine which customer computing devices are executing fraudulent transactions based on the identification of areas of high impact leaks.

A technique is described for implementing drones as a service. As an example, a drone may receive instructions from one or more network elements, coordinate operations with the one or more network elements, and perform at least one task associated with the instructions. The drone may deliver a container to a first location and perform object recognition to validate an object of a subscriber being delivered to a second location. The drone may measure the weight and dimensions of the object to confirm the object is within operating guidelines. After verifying the object is within operating guidelines, the drone may transport the container containing the object to the second location.

Described herein are examples of gift card management systems that provide gift cards that must be activated prior to being used in a transaction. In some examples, a purchaser may be refunded some or all of a purchase price for the gift card when the gift card is not activated. In some examples, the activation may additionally include certain safeguards to prevent fraud.

A system can efficiently control access to an interactive computing environment using an entity profile. The system can receive entity data relating to a target entity. The entity data can include real-time data and external data. The system can extract features from the entity data. The system can generate signals based on the features. Each signal can include a subset of the features, and each signal can correspond to an amount of risk associated with the target entity. The system can generate, based on the signals, an entity profile. The system can provide a responsive message based on the entity profile that can be used to control access to an interactive computing environment.

A system and a method for controlling a bicycle used in an online to offline (O2O) service platform that provides a sharing service of bicycles are provided. The system may detect a pressure signal from at least one part of the bicycle. The system may determine an access permission level based at least on the pressure signal. The system may further control at least one electric control component of the bicycle according to at least the user permission level.

Systems and methods of the present disclosure include computer systems for improving data security. To do so, an authorization request associated with a user profile is received, including a time-stamp for a profile activity, a profile identifier, and a value. Application analytics data for a software application on a user device associated with the user profile is accessed, including an open event indicator indicating a time of a loading, and a close event indicator indicating a time of a termination. An open period of the software application at the time-stamp is determined based on the application open event indicator and the application close event indicator. A reduced set of fraud checks is selected and executed when the time-stamp associated with the profile activity is within the open period of the software application. A fraud determination is generated, and an authorization notification is generated based on the fraud determination.

A method for processing card not present (CNP) transactions includes: receiving an authentication transaction request including authentication transaction data associated with a CNP transaction, receiving an authorization transaction request including authorization transaction data associated with the CNP transaction; in response to receiving the authorization transaction data and the authentication transaction data, determining an authorization decision for the CNP transaction; and communicating the authorization decision. Systems for processing CNP transactions are also disclosed.