US-based startup uses an algorithm to vet commercial lawsuits and finance those with potential for success.
Litigation financing is the process by which a third party provides financing for a legal dispute in exchange for a percentage of any damages recovered from the lawsuit. At best, it can level the playing field in a legal context, allowing plaintiffs who lack the capital to bring a case to court. Litigation finance is big business – the industry is valued at USD 3 billion. Regular readers may remember Lexshares US platform which allows users to crowdsource financing for a lawsuit and CrowdJustice which undertakes a similar function in the UK. Now, Legalist uses data on past lawsuits to predict and provide finance to those with cases that are potentially lucrative.
According to the website, Legalist provides “Data-backed litigation financing.” It searches through millions of past cases to source, vet and finance commercial litigation. The service plans to offer between USD 50,000 and USD 500,000 to claimants, taking up to 50 percent of the settlement in return. According to Co-founder Eva Shang, an algorithm assesses the risk on 58 variables, amongst them the identity of the judge, lawyer, court type and looks at how they relate to the likely outcome of the case. Legalist claim their data-backed approach allows them to make better decisions more quickly on which cases they should finance.
Legalist is providing legal support for those without the capital to seek justice in a commercial sphere but they only consider cases which exceed USD 1 million. Is there scope to use a data-based approach in lower-value claims?