Publication Date:
March 11, 2018
Science
March 11, 2018
In Mergers and Acquisition due diligence, lawyers are tasked with analyzing a collection of contracts and determine the level of risk that comes from a merger or acquisition. This process has historically been manual and resulted in only a small fraction of the collection being examined. This paper reports on the user-focused redesign of our document viewer that is used by clients to review documents and train machine learning algorithms to find pertinent information from these contracts.
We present an overview of the due diligence task and the user stories, generated through analysis of support tickets, user interviews, and usability testing sessions, that we used to redesign our document viewer to accommodate the variety of workflows that our clients employ. Additionally, we detail the important design decisions made and discuss the implications of our redesign beyond our particular use case.
Automatic and Semi-Automatic Document Selection for Technology-Assisted Review
A Dataset and an Examination of Identifying Passages for Due Diligence