Companies that seek profits by funding lawsuits are using generative AI to help find cases to invest in, even as skepticism lingers about the tool\u2019s usefulness.<\/p>\n
Legalist Inc. built an algorithm called \u201cthe truffle sniffer\u201d 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\u2019s growth, with $901 million now under management after its 2016 founding.<\/p>\n
\u201cThe AI is a really crucial part of sourcing,\u201d said Eva Shang, Legalist\u2019s chief executive officer. She co-founded the company with the help of a $100,000 grant from billionaire <\/strong>Peter Thiel\u2019s foundation after dropping out of Harvard.<\/p>\n 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. <\/p>\n 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. <\/p>\n Born out of funding from the Harvard Innovation Lab in 2020, Qanlex is \u201cmore of a technology company than investment fund,\u201d said co-founder Fernando Folgueiro. <\/p>\n 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. <\/p>\n 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.<\/p>\n 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.<\/p>\n Instead, algorithms are trained to look at other factors such as jurisdiction and judges to assess whether a case would be financially viable. <\/p>\n 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. <\/p>\n But the functionality of the AI reaches its limit once it\u2019s time to determine the value and merit of a case. Eva Shang<\/p>\n Photo courtesy of Dennis Webber at Legalist Inc<\/p>\n<\/p><\/div>\n<\/p><\/div>\n At Qanlex, both Gahan and Folgueiro stress that once they\u2019ve made contact with a lead, their human team uses the company\u2019s technology and conducts diligence and underwriting before deploying any capital.<\/p>\n \u201cIt is a relationship-based business,\u201d Gahan said. \u201cWe just use technology to be extremely efficient and let\u2019s say leapfrog a few stages.\u201d<\/p>\n 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.<\/p>\n \u201cFor any AI predictive analytics model to be really effective, it\u2019s only as good as the data that it has available to it,\u201d he said.<\/p>\n 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.<\/p>\n CourtQuant eventually shut down, so Apex employed people to build a similar model.<\/p>\n Right now, Power said, it\u2019s more of a negative assessment tool that helps identify cases they don\u2019t want to invest in. Apex doesn\u2019t make funding offers or commit capital on what the AI tells them without running it through the company\u2019s internal assessment team.<\/p>\n 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.<\/p>\n \u201cNo one\u2019s got a tool where you could push a button and say, wow, this is an order of magnitude better\u2014you still have to read the case,\u201d said David Perla, co-chief operating officer at Burford. <\/p>\n Burford also uses AI to identify lawyers that handle the types of cases they typically get involved in, but the firm can\u2019t envision using it to send out automated emails, Perla said. \u201cIt just won\u2019t work for a company like Burford,\u201d he said.<\/p>\n 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. \u201cWe\u2019re not in the business of cold outreaches, so people will approach us,\u201d said Angela Ni, managing director at Parabellum.<\/p>\n 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\u2014bundles of hundreds of cases typically handled by one law firm as a way to hedge risk\u2014so there\u2019s often a lot of tracking involved.<\/p>\n \u201cWe use rules, algorithms, and code so that we can see all this information,\u201d Ni said. \u201cAnd it helps us with decision-making moving forward.\u201d<\/p>\n The software improves efficiency. Parabellum would likely hire two full time employees to do the job if not for the software, <\/strong>she said.<\/p>\n Burford\u2019s Perla said it is likely AI will improve and will have more uses in the future. <\/p>\n \u201cI\u2019m optimistic a year from now, maybe less, we\u2019ll get on the phone and I\u2019ll say to you, \u2018Yeah, it\u2019s much, much faster, we\u2019re now seeing stuff and we\u2019re seeing things we didn\u2019t see before,\u201d he said.<\/p>\n \u201cEverything in the next few years is gonna be incremental and then in 15 years, litigating is gonna look totally different than it looks today,\u201d Perla said.<\/p>\n<\/div>\nAI Limitations<\/h2>\n
\u201cIt does not do things that an underwriter would normally do,\u201d said the CEO, Shang. \u201cThere\u2019s still a very important human component.\u201d <\/p>\n![\"Eva](\"https:\/\/db0ip7zd23b50.cloudfront.net\/dims4\/default\/659df49\/2147483647\/resize\/633x10000%3E\/quality\/90\/?url=http%3A%2F%2Fbloomberg-bna-brightspot.s3.amazonaws.com%2Fdc%2Fbc%2Fb283a79d46aca3bc5410508f85bf%2Feva-shang.jpg\")
<\/p>\nAI for Research<\/h2>\n
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