Abstract: A method, apparatus, and computer-readable medium are described that enable agent instances to be instantiated in containerized environments. When a new container is detected, a list of agent instances expected to be running in a compute instance or in a container may be obtained and compared with status information regarding which agent instances are active. For a non-active agent instance, an agent object and configuration information for the agent instance may be obtained from a storage. Based on the available name, the agent object, and the configuration information, the agent instance may be instantiated and connected to an agent status server. An application related to the new agent instance may be deployed.

Abstract: A device receives vehicle data associated with vehicles located at a vehicle dealership lot, and receives, from a user device, profile data identifying a user of the user device and data identifying a particular vehicle of the vehicles. The device compares the data identifying the particular vehicle and the vehicle data to determine particular vehicle data associated with the particular vehicle, and processes the particular vehicle data and the profile data of the user, with a first model, to determine purchase options for the particular vehicle and the user. The device provides, to the user device, the particular vehicle data and the purchase options for the particular vehicle to cause the user device to display the particular vehicle data and the purchase options for the particular vehicle.

Abstract: Disclosed herein are system, method, and computer program product embodiments for identifying and managing emerging risks. Businesses, such as those participating in regulated industries, may need to regularly monitor enforcement actions that are cited in a variety of sources. Embodiments disclosed herein provide for scraping information from those sources and comparing it to existing risk events in order to determine possible discrepancies that should be assessed.

Abstract: Disclosed herein are system, method, and computer program product embodiments for identifying and managing emerging risks. Businesses, such as those participating in regulated industries, may need to regularly monitor enforcement actions that are cited in a variety of sources. Embodiments disclosed herein provide for scraping information from those sources and comparing it to existing risk events in order to determine possible discrepancies that should be assessed.

Abstract: A device receives vehicle data associated with vehicles located at a vehicle dealership lot, and receives, from a user device, profile data identifying a user of the user device and data identifying a particular vehicle of the vehicles. The device compares the data identifying the particular vehicle and the vehicle data to determine particular vehicle data associated with the particular vehicle, and processes the particular vehicle data and the profile data of the user, with a first model, to determine purchase options for the particular vehicle and the user. The device provides, to the user device, the particular vehicle data and the purchase options for the particular vehicle to cause the user device to display the particular vehicle data and the purchase options for the particular vehicle.

Abstract: Disclosed herein are system, method, and computer program product embodiments for identifying and managing emerging risks. Businesses, such as those participating in regulated industries, may need to regularly monitor enforcement actions that are cited in a variety of sources. Embodiments disclosed herein provide for scraping information from those sources and comparing it to existing risk events in order to determine possible discrepancies that should be assessed.

Abstract: The present disclosure provides methods and systems for collecting and processing user transaction information for determining a financial profile associated with an income generating activity of a user. One exemplary method comprises: accessing email data associated with a user of an account associated with a financial service; monitoring a user financial profile by scanning the email data associated with the user and identifying email messages including transaction information associated with an income generating activity; extracting income information by determining an amount of payment to the user from the identified email messages; determining user income associated with the income generating activity within a previous period based on the extracted income information; and generating, based on the user income within the previous period, an output indicating an adjustment of at least one service term of the account of the financial service.

Abstract: A device may receive third-party data associated with merchants and may receive customer interest data associated with customers of the merchants, wherein the customer interest data includes data identifying locations of the customers and birthdates of the customers. The device may train a machine learning model, with the third-party data and the customer interest data, to generate a trained machine learning model. The device may receive, from a user device, data identifying a location and a birthdate of a particular customer of a particular merchant, wherein the particular merchant is one of the merchants, and may process the data identifying the location and the birthdate of the particular customer, with the trained machine learning model, to determine a predicted interest of the particular customer. The device may perform one or more actions based on the interest of the particular customer.

Abstract: A device may receive third-party data associated with merchants and may receive customer interest data associated with customers of the merchants, wherein the customer interest data includes data identifying locations of the customers and birthdates of the customers. The device may train a machine learning model, with the third-party data and the customer interest data, to generate a trained machine learning model. The device may receive, from a user device, data identifying a location and a birthdate of a particular customer of a particular merchant, wherein the particular merchant is one of the merchants, and may process the data identifying the location and the birthdate of the particular customer, with the trained machine learning model, to determine a predicted interest of the particular customer. The device may perform one or more actions based on the interest of the particular customer.

Abstract: Disclosed herein are system, method, and computer program product embodiments for identifying and managing emerging risks. Businesses, such as those participating in regulated industries, may need to regularly monitor enforcement actions that are cited in a variety of sources. Embodiments disclosed herein provide for scraping information from those sources and comparing it to existing risk events in order to determine possible discrepancies that should be assessed.

Abstract: A pre-qualification platform may obtain credit history information associated with a user and determine that the user is pre-qualified for one or more loans based on the credit history information associated with the user, wherein the credit history information may include a credit score associated with the user and values for one or more impact factors affecting the credit score. The pre-qualification platform may search an inventory for one or more products that the user is eligible to finance based on financing options associated with the one or more products and terms associated with the one or more loans for which the user is pre-qualified. The pre-qualification platform may populate a user interface to enable one or more actions related to the one or more financing options associated with the one or more products based on determining that the user is pre-qualified for the one or more loans.

Abstract: A device receives vehicle data associated with vehicles located at a vehicle dealership lot, and receives, from a user device, profile data identifying a user of the user device and data identifying a particular vehicle of the vehicles. The device compares the data identifying the particular vehicle and the vehicle data to determine particular vehicle data associated with the particular vehicle, and processes the particular vehicle data and the profile data of the user, with a first model, to determine purchase options for the particular vehicle and the user. The device provides, to the user device, the particular vehicle data and the purchase options for the particular vehicle to cause the user device to display the particular vehicle data and the purchase options for the particular vehicle.

Abstract: A device receives vehicle data associated with vehicles located at a vehicle dealership lot, and receives, from a user device, profile data identifying a user of the user device and data identifying a particular vehicle of the vehicles. The device compares the data identifying the particular vehicle and the vehicle data to determine particular vehicle data associated with the particular vehicle, and processes the particular vehicle data and the profile data of the user, with a first model, to determine purchase options for the particular vehicle and the user. The device provides, to the user device, the particular vehicle data and the purchase options for the particular vehicle to cause the user device to display the particular vehicle data and the purchase options for the particular vehicle.

Abstract: Disclosed herein are systems and methods for a photograph driven vehicle identification system. In some embodiments, a system for image-based vehicle identification includes a database, an image processor, and a vehicle search engine. The database can include vehicle information. The image processor may apply one or more machine learning models on images received by a user device. The user device can include a camera that obtains the images. The user device can provide a display having images of a vehicle and information associated with the vehicle through a user interface (UI) of the user device. The display can include a first portion at a first location of the UI, and a second portion at a second location of the UI. The first portion and the second portion may be provided at a single instance. The vehicle search engine may identify one or more vehicles in the images received.