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Key Takeaways from LFJ’s Digital Event: Legal Tech and LitFin

December 7, 2023

Key Takeaways from LFJ’s Digital Event: Legal Tech and LitFin

On December 6th, 2023, Litigation Finance Journal produced its final event of the year: Legal Tech and LitFin: How Will Tech Impact Litigation Finance Globally? Tets Ishikawa moderated an insightful and pertinent discussion on the use of legal tech in the litigation finance industry. Panelists included Nick Rowles-Davies (NRD), Founder of Lexolent, Isabel Yang (IY), Founder of Arbilex, and Joshua Masia (JM), Co-Founder and CEO of Dealbridge.ai. Below are some key takeaways from the event (answers have been truncated for the purpose of this article): Legal tech is quite a broad term.  What does the legal tech landscape mean to you, and how does it fit into your business? IY: We’re in a very exciting time in legal tech. Where I sit, I primarily deal with the underlying technology being artificial intelligence (AI). The primary advances in advanced AI have primarily occurred out of language being the source data. A lot of these text-based AI advancements all hold great significance for the practice of law. At Arbilex, we are taking advantage of large language modeling (LLM) to reduce the cost of data acquisition. When we take court briefings and unstructured data and try to turn that into structured data, the cost of that process has dramatically decreased, because of Chat GPT and the latest LLMs. On the flipside, because AI has become so advanced, a lot of off-the-shelf solutions have tended towards a black box solution. So the model’s output has become a more challenging task. At Arbilex, we have always focused on building the most stable AI—so we focus on how we can explain a particular prediction to our clients. We are increasingly investing a lot of our time and human capital into building that bridge between AI and that use case. How relevant has legal tech been, and will it be, in the growth of the litigation finance sector?  JM: When we look at scaling operational processes, a lot of times we have to put our traditional computer science hat on and ask, ‘how have we historically solved these problems and what has changed in the past several years to evolve this landscape?’ A lot of the emphasis with technology has been about normalizing and standardizing how we look at these data sets. There’s a big issue when you look at this approach and what existing platforms have been doing—this is a very human business. Because of that, there’s a lot of ad hoc requests that get mixed in. So what gen-AI is doing, we’re getting to a point where you don’t have to over-structure your sales or diligence process. Maybe the first few dozen questions you’re asking of a given data set are the same, but eventually we want to be able to ask questions that are specific to this deal. So being able to call audibles and ad-hoc analysis of data sets was really hard to do before the addition of generative AI. NRD: Legal tech is becoming increasingly relevant, but the real effect and usefulness has grown over time. It makes repetitive tasks easier, and provides insights that are not always readily apparent. But in terms of the specific use of AI to triage outcoming matters, we identify matters in different areas—is this something we simply aren’t going to assess, will it be sent back for further information, does it fit the bucket of something we would fund per our original mandate, or does it go on the platform for the purpose of others to look at and invest in that particular matter. AI is having an increasing impact and is being used with more regularity by litigation funders who are funding they can increase efficiency and get to a ‘yes’ much more quickly. A lot of lawyers would say, this is fascinating, but ultimately this is a human industry. Every circumstance will be different, because they will come down to the behaviors of human beings in that time. Is there a way that AI can capture behavioral dynamics? IY: In general, we need to have realistic expectations of AI. That comes from, what humans are uniquely good at are not necessarily the things that AI is good at. AI is really good at pattern-spotting. Meaning, if I train the model to look for recurring features of particular cases—say, specific judges in specific jurisdictions, when coming up against a specific type of argument or case—then AI in general has a very good ability to assign the weighting to a particular attribute in a way that humans instinctively can come to the same place, you can’t really quantify the impact or magnitude of a specific attribute. The other thing that we need to be realistic about, is that cases are decided not just on pattern, but on case-specific fact attributes (credibility of a witness, availability of key evidence). If you train AI to look for things that are so specific to one case, you end up overfitting the model, meaning your AI is so good at looking for one specific variable, that it loses it general predictive power over a large pool of cases. What I would caution attorneys, is use AI to get a second opinion on things you believe are a pattern. In arbitration, attorneys might use AI on tribunal matters—tribunal composition. AI models are way better at honing in on patterns—but things like ‘do we want to produce this witness vs. another witness,’ that is not something we should expect AI to predict. For the full panel discussion, please click here.

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Owner-Operators Join the Push for Funding Disclosure as Ohio’s Law Takes Effect

The Owner-Operator Independent Drivers Association has added its voice to the trucking industry's campaign for mandatory disclosure of third-party litigation funding, arguing that defendants in nuclear verdict cases should be told who is financing the claims against them.

As reported by Land Line, OOIDA wants outside funding of lawsuits disclosed as a matter of course rather than contested case by case. The association's position puts owner-operators and small fleets alongside the larger carriers that have driven the disclosure debate to date, and reframes it as a concern for the smallest operators rather than only for well-capitalised defendants.

The piece, written by Keith Goble, is pegged to Ohio's new funding law, which takes effect on 6 October. The statute requires disclosure of third-party litigation funding agreements and bars funding from foreign governments, foreign corporations and foreign investors outright. State Representative Meredith Craig, a Smithville Republican, said that "for too long, foreign actors have profited off Ohio citizens."

Michigan is moving on a broader measure. House Bill 5281 would require disclosure of funding agreements, establish a registration regime for funders operating in the state, prohibit commissions, referral fees and other payments between funders and attorneys or healthcare providers, and bar foreign entities from financing Michigan litigation. State Representative Mike Harris, a Waterford Republican, described the current arrangements as "shadow cash" moving through the civil justice system.

The article does not put a figure on how much outside capital is financing trucking claims, which remains the central gap in the industry's argument for disclosure.

Commercial

Rugby Brain Injury Claimants Face £2.8m Costs Bill as Court Blames Former Firm’s Approach

Claimants in the long-running rugby brain injury litigation have been left with a £2.8 million costs bill payable to the defendants by the end of October, with no clarity yet on who will actually pay it.

As reported by NR Times, Senior Master Cook attributed the delays that generated the costs to what he described as the "contradictory and misguided approach" taken by Rylands Garth, the firm that originally ran the group action. KP Law has since taken over the claimants' case and must meet outstanding disclosure obligations by 31 October.

The litigation is funded in full by Asertis, which has financed the entire action over six years, including the neurological testing required to establish each claimant's condition. The report notes that it remains unclear whether the £2.8 million falls to the funder, the former firm, or the claimants themselves, a question with direct consequences for a claimant group that includes seven rugby union players who have died since the action began.

Hundreds of claimants have already been struck off the group register as the case has progressed, and Paul Downes KC has warned of the consequences of further procedural failures. The costs order is the latest in a sequence of adverse developments for the action, which was presented as a landmark test of governing bodies' duty of care in contact sport.

For funders, the case illustrates how a cost liability generated by the conduct of a law firm rather than the merits of the underlying claims can land on a funded book, and how little clarity English procedure offers about where that liability ultimately sits.

Commercial

Krasha to Launch India-Focused Litigation Finance Platform With US$10 Million Minimum Claim Size

Krasha Financial Services has announced plans to launch a dedicated litigation finance platform aimed at the Indian market, with first deployments targeted for the fourth quarter of the 2026-27 financial year.

As reported by India CSR, the platform will fund commercial litigation, arbitration, insolvency claims and award enforcement. Krasha has set a minimum claim size of US$10 million and will cap funded matters at a five-year expected duration, a structure designed to filter out the long-tail cases that have historically made Indian litigation difficult to underwrite. The company said it is in advanced discussions with a UK-based legal finance firm about a strategic partnership, which would give it access to established underwriting practice in a more mature market.

Krasha's chief financial officer, Avdhesh Singh, framed the opportunity around the scale of unresolved Indian litigation, citing more than 50 million pending cases across the court system. The company pointed to global litigation finance market estimates of roughly US$29 billion in 2026, rising to about US$43 billion by 2031, and referenced Burford Capital's reported 26% internal rate of return as a benchmark for the asset class.

The litigation finance platform will sit separately from Krasha's existing neo-financing business, which has a deployment target of ₹1,200 crore for FY2026-27. The group also runs Prism Strategy, a Category II alternative investment fund of roughly US$60 million to US$70 million. Krasha was founded in November 2023.

India has no dedicated statutory framework for third-party funding, and the launch will test how far a domestic funder can build an underwriting model without one.