Kpmg LLP

Francesco Grossi

Chaitanyasinh Ejner

Ajay Wanchoo

The invention relates to computer-implemented systems and methods for assessing the quality of a document or a technical memorandum written with a loosely defined template, stereotype and/or outline of key sections or headers. An embodiment of the present invention leverages Natural Language Processing (NLP) and Machine Learning (ML) techniques to identify key sections in a document using NLP text patterns and further establish, using ML, how closely a given section matches similar sections in other documents that are considered by human Subject Matter Experts (SMEs) to be 'well-written' for the intended purpose of the overall document. An embodiment of the present invention further ascertains whether the overall flow of the document follows a general outline in terms of the order of sections.

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New York, NY, United States of America

Francesco Grossi