AI helps predict spend and outcomes

This article was originally published in Corporate Counsel Business Journal

With legal teams increasingly responsible for helping to meet corporate business goals, they have a greater need than ever to be able to predict spend and plan for the most likely outcomes of their matters.

How much is a particular matter going to cost? What is the range of potential outcomes? Should we litigate or settle? Which matters do we need to focus on for maximum cost control? Which law firm should represent us? Does anyone have a crystal ball we can use? These are some of the questions legal professionals have to ask themselves when dealing with a matter.

You Don’t Need a Crystal Ball to Run a Law Department

So many of the decisions made by legal professionals would be easier if we could just see into the future. When psychic abilities are not an option, however, decisions have to be based on available information, which is often limited, or simple gut feelings. Even though most law departments use e-billing and matter management solutions that capture significant raw data, there’s a good chance that most of it hasn’t been analyzed or made available in a format that is conducive to making informed decisions. As a result, attorneys are often forced to make educated guesses.

Seasoned legal professionals may sometimes have a well of experience to draw on, making inferences based on their many past matters, but no one has infallible memory or judgment. And newer team members lack this level of experience, finding it much more difficult to make decisions confidently.

That’s why educated guesses no longer suffice in a modern environment where business value can be just as important as legal expertise. Legal teams need a way to leverage the valuable data in their invoices, matter management solutions and elsewhere to make actionable, informed decisions.

Mining Data to Predict the Future

For legal professionals without psychic abilities, there is a class of artificial intelligence technology known as predictive analytics. Predictive analytics tools use data to help set reasonable expectations about future results. By analyzing relevant historical information, comparing it to recent data, and identifying the likelihood of various events and outcomes, predictive analytics – using AI technology – can evaluate that data and provide decision-makers with reliable recommendations. As a result, even relatively inexperienced legal professionals can base their decisions on past events

Predictive analytics are proving to be game-changing technologies for legal teams and their outside counsel. They let teams move beyond human instinct to make careful and considered decisions based on actual historical data. Law departments are using the technology to inform the important decisions they make every day about considerations such as law firm selection, budget planning and likely settlement amounts. 

Outside Counsel Selection

Selecting the right outside counsel for a particular case can be tricky. Often, legal teams and claims managers try to circumvent the complexity of the process by simply turning to the most recent law firm partner they’ve used, a phenomenon known as “recency bias.” But these decisions are based as much on personal impression as on fact, and the likelihood of selecting the wrong partner under these circumstances is high. Most companies can’t afford to take those chances.

Predictive AI offers a much more reliable indication than memory or intuition of whether or not a firm is the right fit for a particular matter. An AI algorithm can analyze information from past cases and performance and apply the metrics to the current situation. Based on this data, the AI engine can make a recommendation as to which firm would likely be the best fit. No need to make a guess or rely on a gut feeling.

Predicting Matter Costs and Outcomes

Once a partner is selected, there are still more predictions to be made. These include concerns about what budget to set, whether and when to settle the matter, and what outcomes are most likely based on the decisions made. Attorneys and legal operations professionals don't always have experience in dealing with such questions, or their history may be limited to matters that are dissimilar in significant ways.

It would take a great deal of manual research and/or guesswork for even a seasoned team member to build an accurate representation of settlement amounts and other factors that could help set expectations for a matter. However, AI can do this work automatically to help teams refine their numbers, spot outliers, and identify cases that have the potential to become complicated and incur high costs.

Predictive analytics can offer succinct recommendations on how to proceed with litigation – or whether to proceed at all. These tools provide well-informed recommendations regarding budgets, settlement amounts, and other considerations that impact the department’s ability to predict and control spend. Moreover, thanks to AI’s ability to integrate new information and improve over time, the more matters it analyzes, the more accurate its recommendations become.

When legal professionals select technology that is advanced enough, there’s no need to see into the future – data and AI can provide all the information you need.

To learn more, download this whitepaper from Wolters Kluwer's ELM Solutions.


About The Author

Vince Venturella

Vince is the product manager responsible for the development of Wolters Kluwer's ELM Solutions insurance market offerings for claims and staff counsel. Vince is a strategic, results-oriented legal technology leader with a consistent record of improving processes, developing innovative solutions, and leading diverse product teams. He has worked in legal management consulting and technology solutions within the insurance market for almost a decade. Vince is a graduate of The Ohio State University in Columbus, Ohio.