AI Helps Litigation Funders Mine Court Dockets for Legal Gold

Companies that seek profits by funding lawsuits are using AI to help find cases to invest in, even as skepticism lingers about the tool’s usefulness.

Legalist Inc. built an algorithm called “the truffle sniffer” to search for lawsuits by focusing on variables such as the court, judge and case type. The tool was essential for the alternative asset manager’s growth, with $901 million now under management after its 2016 founding.

“The AI is a really crucial part of sourcing,” said Eva Shang, Legalist’s chief executive officer. She co-founded the company with the help of a $100,000 grant from billionaire Peter Thiel’s foundation after dropping out of Harvard.

Whether companies use AI to decide which cases to fund, or simply for research, the tool is becoming increasingly common in the $13.5 billion litigation finance industry, in which investors fund lawsuits and take a portion of any successful awards.

Litigation funder Qanlex created software called Case Miner to screen, rank and compare cases in Latin America and Europe. Case Miner then automatically reaches out to potential clients deemed most attractive.

Born out of funding from the Harvard Innovation Lab in 2020, Qanlex is “more of a technology company than investment fund,” said co-founder Fernando Folgueiro.

During the pandemic, the founders realized that international courts were increasingly putting dockets online, creating an opportunity to fund cases in untapped markets. The company invests from $100,000 to $3 million per case, and it tends to favor breach of contract cases.

Case Miner has been so successful that company leaders at times have had to halt using the tool because they could not handle the amount of leads it created for them, said co-founder Yago Zavalia Gahan, who is also an engineer and programmer.

AI Limitations

Using artificial intelligence to predict the value and length of a case is tricky because of a dearth of publicly available data. While many court dockets are online, settlement amounts are often confidential, leaving the most vital data point for funders out of reach.

Instead, algorithms are trained to look at other factors such as jurisdiction and judges to assess whether a case would be financially viable.

Legalist exclusively relies on its technology to find cases to fund. It then sends automated outreach to potential clients, which are typically the law firms representing plaintiffs but at times are the claimants themselves.

But the functionality of the AI reaches its limit once it’s time to determine the value and merit of a case.

“It does not do things that an underwriter would normally do,” said the CEO, Shang. “There’s still a very important human component.”

Eva Shang

Photo courtesy of Dennis Webber at Legalist Inc

At Qanlex, both Gahan and Folgueiro stress that once they’ve made contact with a lead, their human team uses the company’s technology and conducts diligence and underwriting before deploying any capital.

“It is a relationship-based business,” Gahan said. “We just use technology to be extremely efficient and let’s say leapfrog a few stages.”

UK-based Apex Litigation Finance advertises the use of AI on its website and the ability to predict case outcomes, timelines, and settlement amounts. But in reality, Apex CEO Maurice Power said, the data available is quite poor and the ability to predict is limited.

“For any AI predictive analytics model to be really effective, it’s only as good as the data that it has available to it,” he said.

Apex, which funds small to midsize commercial claims in the UK, began to explore AI four years ago with a company called CourtQuant. The model was to gather information on every recorded judgment in the high courts in the UK and through predictive analytics forecast the likely outcome of a case.

CourtQuant eventually shut down, so Apex employed people to build a similar model.

Right now, Power said, it’s more of a negative assessment tool that helps identify cases they don’t want to invest in. Apex doesn’t make funding offers or commit capital on what the AI tells them without running it through the company’s internal assessment team.

AI for Research

Burford Capital, one of two publicly traded legal finance firms, experiments with AI on its closed cases to see if the technology could accurately predict how a case turned out.

“No one’s got a tool where you could push a button and say, wow, this is an order of magnitude better—you still have to read the case,” said David Perla, co-chief operating officer at Burford.

Burford also uses AI to identify lawyers that handle the types of cases they typically get involved in, but the firm can’t envision using it to send out automated emails, Perla said. “It just won’t work for a company like Burford,” he said.

Litigation funder Parabellum Capital is skeptical of the role AI could currently play and instead said it relies on relationships to obtain clients and invest in cases. “We’re not in the business of cold outreaches, so people will approach us,” said Angela Ni, managing director at Parabellum.

But the funder has found other ways to use AI. Ni said Parabellum created a proprietary tool that automates the case management process. Parabellum often invests in portfolios—bundles of hundreds of cases typically handled by one law firm as a way to hedge risk—so there’s often a lot of tracking involved.

“We use rules, algorithms, and code so that we can see all this information,” Ni said. “And it helps us with decision-making moving forward.”

The software improves efficiency. Parabellum would likely hire two full time employees to do the job if not for the software, she said.

Burford’s Perla said it is likely AI will improve and will have more uses in the future.

“I’m optimistic a year from now, maybe less, we’ll get on the phone and I’ll say to you, ‘Yeah, it’s much, much faster, we’re now seeing stuff and we’re seeing things we didn’t see before,” he said.

“Everything in the next few years is gonna be incremental and then in 15 years, litigating is gonna look totally different than it looks today,” Perla said.