TECHNICAL FIELD

Aspects of the disclosure generally relate to one or more computer systems, servers, and/or other devices including hardware and/or software. In particular, aspects of the disclosure generally relate to capturing data via one or more sensors in a mobile device and aggregating that data with other data to generate an output based, in some examples, on machine learning.

BACKGROUND

Nearly everyone today uses some sort of personal mobile device on a regular basis. For instance, people use smartphones, cell phones, wearable devices such as smart watches and fitness monitors, tablets, laptops, and the like. These personal mobile devices are regularly carried by users throughout the day and can capture a variety of information regarding the user's usage of their personal mobile device, locations visited, and the like.

In addition, user data is collected and stored by a variety of different sources. For instance, user data that is collected by a mobile device, wearable device, or other similar device of a user may be stored via one or more third party systems (e.g., cloud-based environments) or entity systems with the permission of the user (e.g., upon downloading an application, executing an application, or the like). This data may be transmitted to an entity for evaluation and may be useful in evaluating user behaviors and identifying insights that may be helpful to users. In some examples, this data may be useful to other entities to evaluate users and generate offers. However, it is difficult for users to view and/or retrieve this data from the third party or entity. Accordingly, it may be advantageous to retrieve data from the third party and analyze the data to generate and provide outputs to a user.

Further, some conventional processes require human interaction, evaluation, and the like. Given the volume of data captured by the mobile device, stored by one or more entities, and the like, it would be advantageous to perform these processes based on sensor data collected rather than requiring human evaluation.

SUMMARY

The following presents a simplified summary in order to provide a basic understanding of some aspects of the disclosure. The summary is not an extensive overview of the disclosure. It is neither intended to identify key or critical elements of the disclosure nor to delineate the scope of the disclosure. The following summary merely presents some concepts of the disclosure in a simplified form as a prelude to the description below.

Aspects of the disclosure relate to methods, computer-readable media, systems, and apparatuses for evaluating device usage, capturing user data, and generating one or more outputs based on the device usage and/or user data. For instance, data from one or more sensors within a mobile device can be received and processed to determine movement associated with the device. In addition, an amount of usage (e.g., hours, minutes, etc.) associated with the device can be received. In some examples, application usage and/or types of applications used can also be received. This data can be processed to determine travel patterns for the user of the device and those travel patterns can be utilized to build a risk profile for the user. The risk profile can be utilized for a variety of purposes, including determining rate information and confirming information provided by the user, as well as for generating other insights.

Additional aspects of the disclosure relate to methods, computer-readable media, systems, and apparatuses for retrieving user data collected by, for example, a mobile device of a user, from a third party system for use in evaluating user behaviors, generating outputs and insights, and the like. In some examples, machine learning may be used to evaluate user data and/or generate one or more outputs.

In some arrangements, methods, computer-readable media, systems, and/or apparatuses are provided for receiving a request to generate an offer. For instance, user input may be received requesting generation of an offer. In response to receiving the request, in some examples, an application may be transmitted to a device, such as a mobile device of a user. In some examples, the transmission of the application and request for an offer may be performed in advance of other processes described herein (e.g., just before, days or hours before, or the like). 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.

These and other features and advantages of the disclosure will be apparent from the additional description provided herein.

