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