Allstate Insurance Company

Soton Ayodele Rosanwo

Howard Hayes

Sunil Kumar Chintakindi

Surender Kumar

Timothy W Gibson

Tim Gibson

Regina Madigan

Aleksandr Likhterman

Caleb Johnson

Srinivas Nainala

Anuradha Kodali

Juan Ortiz-Zabala

Methods, computer-readable media, systems, and/or apparatuses for evaluating movement data to identify a user as a driver or non-driver passenger are provided. In some examples, movement data may be received from a mobile device of a user. The movement data may include sensor data including location data, such as global positioning system (GPS) data, accelerometer and/or gyroscope data, and the like. Additional data may be retrieved from one or more other sources. For instance, additional data such as usage of applications on the mobile device, public transportation schedules and routes, image data, vehicle operation data, and the like, may be received and analyzed with the movement data to determine whether the user of the mobile device was a driver or non-driver passenger of the vehicle. Based on the determination, the data may be deleted in some examples or may be further processed to generate one or more outputs.

Multi-computer processing system for dynamically executing response actions based on movement data

Methods, computer-readable media, systems, and/or apparatuses are provided for providing offer and insight generation functions. User input requesting an offer or insight may be received and an image of a photographic identification of a user may be requested. The image of the photographic identification may be captured and stored. A self-captured image of the user may be captured (e.g., via an image capture device of the computing device) and compared to an image of a user from the photographic identification. Responsive to determining that the images match, displaying an instruction to capture a vehicle identification number. The vehicle identification number may be captured. Data, including location data, may be extracted and an archive including the extracted data may be generated and the data may be transmitted to an entity computing system for processing. The entity computing system may evaluate the data and generate one or more insights and/or outputs.

Data processing system with machine learning engine to provide output generation functions

Methods, computer-readable media, systems, and/or apparatuses for providing offer and output generation functions are provided. For instance, a request for an output may be received by a device. In response, user physical trait data, pre-stored data, location data, and the like, may be extracted and received from a plurality of sources. Machine learning may be used to analyze the data to predict one or more factors associated with the user and the output or offer may be generated based on the predicted factors.

Methods, computer-readable media, systems, and/or apparatuses for providing offer and insight generation functions are provided. For instance, user input may be received requesting generation of an offer. In response to receiving the request, an application may be transmitted to a device, such as a mobile device of a user. In some examples, the application may be executed by the device and may facilitate establishing a communication session with a third party system, identifying and extracting data from the third party system, and transmitting the extracted data to an entity for evaluation. In some examples, evaluation by the entity may include generating one or more insights, outputs and the like. In some arrangements, the evaluation may be performed using machine learning and, in some examples, may be performed in real-time or near real-time.

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Chicago, IL, United States of America

Soton Ayodele Rosanwo