Abstract: This invention relates generally to the personal finance and banking field, and more particularly to the field of lending and credit notification methods and systems. Preferred embodiments of the present invention provide systems and methods for automatically generating high quality adverse action notifications based on identifying variations between a declined borrower's profile and that of approved applicants, both with simple and sophisticated credit scoring systems, using specific algorithms.

Abstract: A method performed by one or more processing devices includes receiving data indicative of amounts of users in population segments that access a resource; applying an expectation-maximization algorithm to the data received; generating, based on applying, estimates of weights indicative of an accuracy of the amounts of users; wherein the expectation-maximization algorithm is applied and the estimates are generated until the estimates reach an asymptotic approximation of the weights; adjusting the amounts of the users in accordance with the estimates of the weights; and generating, based on the amounts of the users adjusted, an estimate of a composition of a population of users that access the resource.