It’s Time to Mine
using Predictive Analytics in Litigation Management
By Peter Wu, David Duden, Misty Price, Karen Stankevitz and Steven C. Testan
We have heard a lot about predictive analyticsoverthelastseveralyears, but what is it really? Predictive analytics is the analysis of data through statisti- cal or mathematical techniques that
results in meaningful relationships being identified in the
data. These results can then be used for better prediction of
future events and better decision-making.
This definition may not appear to be new since it is what
mathematicians and scientists have been doing throughout
history to advance human knowledge. Business leaders have
been using analytics to gain competitive advantage for many
years. Indeed, the insurance industry may be the earliest
adopter in applying predictive analytics given that one of the
oldest examples is the use of mortality tables to price annuities and life insurance policies dates back to the 17th century.
However, the new features about today’s modern predictive
analytics include the scale, depth and wide range of information available for the analysis. Combining the wide range
of information with the fast development in computation
technology, data storage capacity and statistical modeling
techniques, allows the modern predictive modeling to perform large-scale multivariate analysis. Multivariate analysis
looks not only at individual correlations but how different
relationships affect one another.
Banking and credit card industries are well known to be the
leader in the use of modern predictive analytics to assist
in credit card fraud detection. If you’ve had a credit card
