Predictive analytics – saving the day, driving the law

Han Pham, Thomson Reuters

Whether we realize it or not, predictive analytics gives us a jump start to our daily lives. Sometimes it is in the form of synthesizing traffic patterns to triangulate the most efficient route to work in the morning by using a maps app. Or sometimes, like I recently experienced, it is a credit card company analyzing your purchasing history to detect inconsistencies in your spending activity. When I received the call from my credit card company, I was almost confrontational with the poor man on the phone, so much did I want those errant charges to be legitimate—one of the first responses of being victimized seems to be denial.

We have all gotten those annoying, untimely calls from the credit card company to verify charges that are actually legitimate. These calls tend to happen when you are traveling and trying desperately to impress some new friends by spending recklessly until the clerk or waiter returns to you, holding out your card in a way that points you out to the entire world, to let you know that there is an "issue" with your card. With all eyes upon you, you call the credit card company and answer those mundane questions that reveal to your new friends that although, yes, you are who say you are, that, no, you are not who you think you are.

The charge that they did find was large, yet not entirely out of the ordinary—I had been doing a lot of travel in that year and this was a charge to a travel agency. Had I been glancing through my statement on my own, I might have missed it entirely. I had never appreciated how nuanced the predictive models for fraudulent charges must be until I had actually reviewed them that day. And I was glad for it.

Analytics can also play a role in jump-starting your legal work. Just as with traffic or spending activity, litigation activities create data that can be aggregated, synthesized and interpreted to predict future results. Many litigators already engage in this type of data analysis, and new tools and technology are making it easier to process large sets of these data into meaningful insights. Here are a few ways that data and analytics can help with setting case strategy.

1. Verdict, settlement or motion: Historic data on the outcomes of litigation for a particular judge or venue can help you see the bigger trends on verdict, settlement or decision on motion. Learning that your judge almost never has cases that reach a verdict may make you more comfortable when outside counsel suggests settlement as the right strategy.
2. Judge investigation and preferences: Judges are humans and although they are theoretically unbiased, historical data can reveal unconscious biases toward the plaintiff or defendant. Looking at this view from a long-term perspective will also show how their preferences have developed, giving you an indication on what key events have shaped their views.
3. Expected timelines for phases of litigation: One major factor in the cost of litigation is time, especially when you're paying outside counsel by the billable hour. Data from dockets and cases aggregating the duration of litigation will give you an indication of how to budget your legal expenses.

Who knows how many of these applications of predictive analytics may end up saving your day?

About the author

Han Pham is director at Thomson Reuters focused on innovation and growth, exploring how to bring better tools to better solve our customers' need. She is admitted to the New York Bar.

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