Beyond eDiscovery:
Applying Data Analytics To Build Early Warning Systems And Address Other Legal Challenges
Keynote Address by Bennett Borden
Predictive analytics, such as those used in Technology Assisted
Review, are a powerful means to help solve the significant challenge
of finding relevant information within a larger corpus for ediscovery
purposes. This can provide significant strategic legal advantages
well beyond mere discovery for the party employing them. Having
applied analytics to great effect in litigation, we began
experimenting with how we might apply analytics in other legal and
information governance settings. These have included applying
predictive and other data analytics in investigations, due diligence,
and compliance systems. Based on our success in these areas, we
decided to see if we could use predictive analytics not just to
predict the classification of a document, but to actually predict the
future, or at least the probability of certain events occurring in the
future. In our most ambitious application, we’ve built an early
warning system that can predict corporate misconduct. Leveraging
developments in different aspects of data science, our system finds
patterns in human conduct as revealed through ESI and alerts
stakeholders when those patterns potentially relate to
misconduct. While still in the early stages of development, I will
discuss how this type of application of data analytics to a myriad of
legal challenges is showing great promise in continuing to
revolutionize the practice of law.
Doug Oard
Last modified: Tue May 12 09:54:30 2015