One of the most common refrains across businesses today is the importance of data analytics. This urgency exists in the litigation finance industry as well, though many repudiate the fact. Indeed, legal funding firms struggle just as much with a fundamental aspect of data analytics-gathering data-as most companies do.
If one were to interview ten different industry insiders about using business intelligence and quantitative methods in litigation finance, the challenge of getting useful data would likely be mentioned ten times.
Thankfully, this challenge can be overcome. No company of any industry begins its data analytics journey with easy access to reliable data. In the world of data analytics, everyone starts at the same, initial stage: data extraction.
There are three sources of data in the legal funding field today: internal, survey and government generated.
All three types of data can benefit legal funding managers in unique ways, answering different questions.
First up, and perhaps the most powerful source of data, is the internal data your business generates throughout day-to-day operations.
The key to effectively gathering this data is to use facilitatory software and technology that enables your team to easily accurately collect and input the data you need. That same software should then render and organize that data in a digestible, user-friendly format.
As I touched upon in Make Analytics and Reporting Your Secret Weapon, internal data is best used for:
If you're using the right tools, accumulating internal data for these purposes will happen naturally, and the end product will be extremely conducive to answering questions about the state of your business today.
A bit of cautionary advice: do not exclude unfunded or unfinished cases from your data.
I cannot emphasize enough how debilitating this is to your data analytics. Gathering data on the characteristics of unfunded applications is just as important as gathering information on the properties and traits of successful investments.
If your system doesn't make this easy for you and your team, it's time for new technology.
Survey data has to be gathered through custom surveys, and, in my experience, it is primarily instrumental in identifying case outcomes in settled matters, as well as learning from attorneys and plaintiffs you have relationships with.
Attorneys like to say that 95% of cases settle. When such holds true, there is generally very little data on the outcome filed with any government body. Subsequently, the only way to get aftermath data is by anonymously surveying industry participants - e.g. plaintiffs, attorneys, and defendants - and structuring the surveys so that they do not violate anyone's privacy, often through aggregation.
Although survey data is expensive-its gathering process laborious-it is nevertheless an invaluable tool for quantitative analytics. To get a reliable survey, one needs the names of potential survey respondents (usually from a list broker) and a survey design. Once the survey is mailed or emailed to participants and the funder receives a meaningful number of responses, he or she must compile the results.
Though this sounds like drudgery, there is simply no substitute for acquiring firsthand data and information on case outcomes. This type of data can be used to understand case outcomes under various circumstances and has the potential to forecast or help forecast the outcomes of pending cases.
A second way legal funders can leverage survey data is by administering a survey of plaintiffs or attorneys in his or her market. By means of this study, a funder could evaluate just how familiar people are with his or her business, how well people understand legal funding, as well as perceptions of the company as a whole. Such information could help boost sales and improve marketing strategies.
Third, you might also consider using a survey to gather qualitative data on plaintiffs and attorneys you have already worked with, in order to better understand how to improve company funding processes. This is yet another way to profit from internal data.
Much ink has already been spilled on how to create a survey, so here are some of the best tools and resources to help you get started:
Resources for learning how to administer a survey yourself
Admittedly, the concept of surveys often draws a lot of skepticism. People have many reasoned concerns about survey response bias and sample size. Yet, surveys are still used widely in all fields, including finance, and for various important needs- from illiquid securities pricing to setting certain interest rates to developing league tables.
Apart from finance, television and radio stations use surveys to determine ratings, and marketing firms spend millions of dollars each day based on survey results. Some data can only be obtained by survey.
Apart from internal information and surveys, various governmental bodies offer systems by which to gather data, which can be useful in litigation finance.
Examples include litigation awards data from court sources and the IRS, broader economic data from the Federal Reserve and background data from the US Census Bureau.
Court sources are the most accessible data reservoirs to mine in litigation finance. The problem is that operating on this data at scale requires some understanding of textual analysis. While textual analysis isn't particularly difficult - tip: software programs like SAS offer canned black box text reading packages - it is time-consuming and has to be done carefully so as to be done correctly. Simply amassing the text data often requires basic Python or PERL web crawler knowledge as well. This level of industry exceeds the ability or time availability of most industry professionals in litigation finance but can be outsourced quite effectively.
Beyond the data from court filings, the IRS has data on litigation awards (along with salary data and a myriad array of other personal data) for all US taxpayers. However, that data can only be accessed if one has an affiliation with a constituent university of the thirteen US Census Research Data Centers around the country. Again, for most litigation finance professionals, this data source is not an option, but it can be outsourced.
Despite that, interested litigation finance professionals can gather background data related to the geographic region of a given case. This can be done effectively using two tools available over the internet, without charge: the Federal Reserve's FRED database and the US Census Bureau's DataFerret.
FRED is an Excel add-in that can be downloaded from the St. Louis Federal Reserve and it provides economic data at various macro levels, which is helpful when trying to determine former background conditions impacting a past case.
For example, understanding the level of auto sales, interest rates, and gasoline prices might all help shed light on the economics of the auto industry, which could be constructive to apposite cases. The FRED data won't reveal case outcomes, but it can still help clarify why two similar cases might have had very different outcomes at different points in time.
DataFerret is similar to FRED, but it comes from the US Census Bureau and offers demographic data at the most granular level across the country. Getting data from DataFerret can help funders identify the descriptive characteristics of plaintiffs, defendants, and other parties in a suit.
It's easy to determine that defendant Corporation A has 820 employees, but using the company's HQ location, funders can easily identify factors that might affect the firm's behavior, such as local economic conditions, population density, average education, average employee wage, etc.
Again, these factors won't directly influence the outcome of a case, but they are important to consider.
The Bureau of Justice Statistics is the one government entity I'm aware of that does provide public data, although it is a bit behind the times. Nonetheless, it can give you a sense of the broader PI market. For example, on the BJS site they provide data on:
The real lesson in data analytics is that one data source is never enough. Instead, the most powerful insights come from the combination of multiple sets of data and then being able to draw novel conclusions.
Needless to say, litigation finance professionals must look to draw upon primary source materials, such as court documents, for important information and details. They can come to more useful conclusions, however, if they supplement this information with background material, such as that available from FRED and DataFerret.
If they use survey data to dig deeper into what happens in unfinished or unfunded cases, as well as seek the thoughts and perspectives of parties in those cases, they will have one Hulk of a database.
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