Using Data Analysis to Improve Litigation Finance
The growth of litigation funding has been accelerated by technology. The internet has been crucial in helping litigants find funders who are willing and able to provide financing for their cases. But there is room for even more technological sophistication in litigation finance. By using sophisticated data analysis, funders can do an even better job of identifying the cases that deserve funding the most.
Many litigation financing companies rely upon business models that depend upon data analytics. For example, some companies use proprietary algorithms to compare attributes of millions of state and federal cases to the cases of the applicants seeking funding. These algorithms help funding companies identify the key characteristics of cases that produce discovery, and those who use these algorithms choose the cases that have a critical mass of such characteristics.
Such an analytical approach is only the tip of the iceberg, however. The collection of detailed data about litigation matters is still developing. As more data is collected and analyzed, the sophistication of the analytical methods will increase. Moreover, as litigation funding expands and continues, and as companies acquire granular data about the cases they have funded, data analysis will progress dramatically.
In addition, litigation funding can borrow analytical tools from financial analysis. Although some of the analytical approaches used by litigation funders have their origins in the world of finance, there are many more analytical tools that can be brought into the litigation funding arena. For example, predictive models could help estimate expected valuation and life span of cases. Data analytics could also help funding companies to benchmark themselves against the industry and understand where their own opportunities lie.
Litigation finance works for everyone when funders invest in cases that have a real chance at success. Such investment makes the legal system more effective, helps litigants find justice, and brings profits to investors. Of course, the trick in achieving this outcome comes in identifying the cases that have a real chance at success. As data analysis becomes more sophisticated and reliable, this task will become easier and litigation funding will clearly demonstrate that it is an asset for the legal system.
Topics: litigation finance, legal reform, third-party funding, litigation costs, data analysis, financial analysis
Works Cited:
Christopher Bogart, Litigation Finance, Big Data and the Limits of AI, Law360 (April 20, 2017) available at https://www.law360.com/texas/articles/914716?utm_source=rss&utm_medium=rss&utm_campaign=section
