Abstract: A computer-implemented method includes a method comprising using at least one hardware processor to: receive a plurality of data from a plurality of data sources; standardize the plurality of data; tag the standardized plurality of data with one or more companies; train a prediction model to predict a metric for each of the one or more companies based on the standardized plurality of data tagged with that company and historical measurements for that company; and apply the prediction model to new data to predict the metric for at least one of the one or more companies.

Abstract: A computer-implemented method comprising at least one hardware processor to: at each of one or more times, receive, from a user, a company identifier and one or more conditions, generate an alert for the company identifier and the one or more conditions, and associate the alert with the user; receive a plurality of data from a plurality of data sources in real time; update a plurality of signals based on the plurality of data, wherein each of the plurality of signals represents one of a plurality of critical indicators for one of a plurality of companies; and for each alert associated with the user, apply the one or more conditions of the alert to at least one of the plurality of signals to determine whether or not the alert is triggered.

Abstract: A computer-implemented method comprising receiving user preference information, based on the received user preference information, determining one or more user settings, processing data to determine a data condition, wherein, to determine the data condition, a plurality of alternate data inputs of different types are processed and normalized, and applied to a series of operations to generate a forecast having a degree of confidence, and the data condition is compared with third party information; providing an electronic notification indicative of the data condition to the user device, wherein the electronic notification includes the data condition compared with the third party information, a confidence indicator associated with the data condition, and a user prompt; in response to a single user input, the user device generating an instruction to execute the user request; and based on the instruction, executing the user request based on the determined one or more user settings.