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Commercial

Dutch Funder FairPlay Legal Halts Financing of Gambling-Loss Claims After Supreme Court Ruling

FairPlay Legal has stopped funding Dutch gambling-loss claims and is terminating its existing files after the Hoge Raad, the Netherlands' Supreme Court, ruled that the absence of a Dutch licence does not by itself render an online operator's contracts void.

As reported by Casino Zorgplicht, the Court held in its 3 July 2026 judgment that the Wet op de kansspelen, the Dutch gaming act, never had the effect of invalidating contracts with operators acting contrary to article 1(1)(a). That conclusion removes the central legal theory underpinning thousands of claims seeking recovery of losses incurred with unlicensed offshore operators. The ruling followed preliminary questions referred in June 2024 by the district courts of Amsterdam and North Holland, and was consistent with the advisory opinion delivered by Advocate General Lindenbergh in November 2025.

FairPlay Legal withdrew financing immediately, telling the publication that the claims no longer offer "legal and commercial perspective." The funder, which worked exclusively with advocaat Pepijn Le Heux on the portfolio, said it will continue to pursue a separate category of cases in which operators refuse to pay out winnings. It has no connection to Fair Play Casino.

The decision illustrates how quickly a consumer-claims portfolio built on a single statutory argument can be wound down once an apex court closes the theory. Dutch gambling-loss claims had attracted significant funded volume over the past three years, and the ruling effectively strands files that had not yet reached judgment or settlement.

Commercial

Linklaters Urges Standalone Cost-Benefit Test for UK Antitrust Class Actions

Linklaters has called for a new standalone hurdle at the certification stage of UK antitrust collective proceedings, arguing that claims should advance only where their expected financial benefits substantially outweigh the costs of bringing them.

As reported by PYMNTS, citing Law.com International, the firm submitted the proposal to the Department for Business and Trade's consultation on "Swifter and simpler competition redress, regulatory appeals and competition enforcement," published in July with responses due 25 September. Linklaters argued that the Competition Appeal Tribunal should apply heightened scrutiny to novel or unestablished theories of harm, and framed its concerns around litigation costs, third-party funding structures and the proportion of any award that ultimately reaches class members.

The submission enters a debate that has intensified since the Supreme Court's decision in Merricks, widely read as lowering the certification threshold and opening the door to a substantial pipeline of opt-out claims. Critics of the regime point to outcomes such as Waterside v Mowi, where the distribution of recoveries between class members, their lawyers and their funders drew judicial attention.

The proposal sits in direct tension with submissions from the claimant and funding side, including the International Legal Finance Association's call for the government to clarify rather than rebuild the opt-out regime. With the consultation window now closed, attention shifts to whether the Department for Business and Trade treats funder economics as a certification question or leaves it to the Tribunal's existing discretion.

Commercial

Pogust Goodhead to Change Its Name as Both Namesake Founders Demand Removal

Pogust Goodhead will abandon the name it has traded under since 2021 after both of its namesake founders publicly demanded their names be stripped from the firm, deepening a governance crisis at one of the most heavily funded claimant firms in the UK market.

As reported by Legal Futures, Harris Pogust announced via LinkedIn that he had issued a cease-and-desist demanding the firm stop using his name, saying he was "embarrassed to have my name anywhere on that document" in reference to proceedings the firm has brought against its own client committee. "You are suing someone you are asking the court to allow you to continue to represent?" he wrote. Co-founder Tom Goodhead followed with a similar demand days later.

A firm spokeswoman confirmed the change: "We intend to move away from the Pogust Goodhead name. The firm has moved on from its former leadership and its name should too." The rebrand will be the practice's fourth identity since 2018, following SPG Law and PGMBM.

The dispute centres on the £36 billion Mariana Dam claim against BHP, brought on behalf of more than 400,000 Brazilian claimants. Pogust Goodhead has filed a claim against its own client committee after the committee moved to replace it with Bailey Glasser International. An expedited hearing is expected.

For funders, the episode is a reminder that concentration risk in mass-claims portfolios extends beyond case merits to the stability of the firm running the book.

Commercial

UK Tribunal Certifies Revived Apple and Amazon Consumer Claim, Subject to Changes in Funding Arrangements

The Competition Appeal Tribunal has partially certified a revived consumer claim against Apple and Amazon, but conditioned certification on changes to the proposed class representative's funding arrangements and remuneration — the second time funding terms have been the pivotal issue in this proceeding.

As reported by the Cyprus Mail, Judge Kelyn Bacon found the claim concerning Apple product sales on Amazon's UK marketplace to be "plausible, credible and grounded in the facts," while refusing to certify broader allegations relating to other retailers as resting on a "complex and speculative theory of harm." The certified claim is valued at between £289 million and £306 million including interest. Tribunal records list the case as 1759/7/7/25, brought by JLP A&A Class Representative Limited, with Justin Le Patourel as the proposed class representative.

Funding has shaped this litigation from the outset. In January 2025, the Tribunal refused a collective proceedings order sought by academic Christine Riefa, finding she was insufficiently independent of her funder, Asertis, given an uncapped success-fee multiple, a priority-payment obligation and confidentiality over the funding terms. Interim costs of £1,695,797.16 were awarded, with a further £1,355,347.77 in interest.

The latest ruling signals that the Tribunal remains willing to certify substantial opt-out claims while treating funder economics and class representative compensation as conditions precedent rather than post-certification housekeeping. The claimant side will now need to redraft its funding terms before the proceedings advance.

Commercial

Burford Capital Discloses Up to $1.4 Billion Entitlement From $5.7 Billion Apple Patent Verdict

Burford Capital has told the market it could be entitled to as much as $1.4 billion following a San Diego federal jury's award of roughly $5.7 billion to Taction Technology in a patent dispute with Apple. The verdict, returned after market close on Friday, is among the largest patent damages awards ever entered against the technology company.

As reported by PR Newswire, Burford said that if the award were paid as rendered, its entitlement would be approximately $1.4 billion, split roughly evenly between its balance sheet and its investment funds. The funder attached unusually heavy caveats to that figure, noting that Apple is expected to file post-trial motions including a motion for judgment as a matter of law, that any judgment would be subject to review by the U.S. Court of Appeals for the Federal Circuit, and that "very few large patent verdicts survive the post-verdict process intact." Burford cautioned that the ultimate recovery could be substantially lower than the verdict amount, or nothing at all.

Burford's shares rose approximately 9% in London trading following the disclosure, which was also filed with the U.S. Securities and Exchange Commission as an exhibit to a Form 8-K.

The announcement arrives roughly six months after the Second Circuit's reversal in the YPF matter, where Burford had reported a far larger potential entitlement tied to a $16 billion judgment against Argentina. That reversal underscored the volatility of concentrated, single-case exposures — a dynamic Burford's own caveats appear designed to pre-empt this time.

Commercial

ILFA Urges Government to Clarify Rather Than Rebuild the Opt-Out Collective Actions Regime

The International Legal Finance Association has filed its response to the UK Government's consultation on competition redress, arguing that reforms intended to speed up the opt-out collective actions regime must not add cost or complexity that makes meritorious claims harder to fund.

The submission responds to the Department for Business and Trade's consultation on "Swifter and Simpler Competition Redress, Regulatory Appeals and Competition Enforcement," which opened on 17 July and closed on 25 September. ILFA's central argument is that the Competition Appeal Tribunal and the appellate courts have already developed workable mechanisms for overseeing class representative suitability, and that the Government should deliver clarity through guidance and the formalisation of existing practice rather than new statutory or procedural requirements.

"Third-party litigation funding is the cornerstone of the opt-out collective actions regime," said Neil Purslow, Chairman of the Executive Committee of ILFA. "Without it, consumers and small businesses would have no realistic means of bringing meritorious claims against well-resourced defendants. In our response, we make it clear that any new reforms must not inadvertently introduce cost or complexity, which only serve to make valid claims harder to bring."

ILFA ties the Government's proposal to permit damages-based agreements in collective proceedings to the unresolved question of funder returns. "Crucially, the Government's proposal to permit damages-based agreements in collective proceedings underscores the urgent need to reverse the PACCAR ruling retrospectively," Purslow said. "To keep this regime viable and investable, we must give funders earlier certainty over returns and introduce better cost budgeting to rein in unpredictable, disproportionate costs."

On costs, the association supports mandatory costs budgeting for claimants and defendants alike from certification onwards, and greater use of alternative dispute resolution where it is required early and backed by real costs sanctions. It also backs a central CAT website for claims and settlements, while cautioning that efficiency measures such as reduced panel composition may yield only marginal savings.

"Maintaining a true equality of arms is essential," Purslow said. "Large defendants should not be allowed to weaponise structural hurdles to quash meritorious claims and ordinary businesses and consumers must remain empowered to hold the powerful to account."

Commercial

Which AI Model Is Best for Legal Work? What 2026 Research Says About Accuracy

Law firms, funders and legal departments are being sold AI for contract review, legal research and citation checking, and the models change every few months. So we looked only at independent studies published in 2026 that tested the current generation of models from OpenAI, Anthropic and Google on real legal tasks. The short version: the best models are now genuinely good at reading and extracting from documents you give them, still unreliable at recalling law from memory, and the commercial legal research tools lag behind the best custom systems.

At a Glance

Best overall model for legal document work: Google's Gemini 3.1 Pro. It was at or near the top in every 2026 study that tested it, and it was usually the fastest and cheapest of the leaders. OpenAI's GPT-5.5 found slightly more errors in contract review, and Anthropic's Claude models were the most careful about not flagging problems that weren't there.

Best accuracy recorded on a full legal task: 92%, on a 50-state statutory research test run by Stanford, achieved by a purpose-built research tool. The lesson is that how the AI is set up matters as much as which model sits underneath it.

Range of accuracy: from under 7% (asking a model to recall exact case citations from memory) to 99–100% (catching a citation to the wrong case when the model can read the source). Most real-world document tasks landed between 60% and 85%.

Westlaw and Lexis AI: 58% and 64% accuracy on a Stanford statutory survey test, below a custom-built tool at 83–92%.

Biggest single improvement: giving the model the actual documents instead of asking it from memory cut fabricated citations from roughly 15–40% to about 4–15%, and to under 0.2% with a well-built retrieval system.

Key Takeaways

The model to use. For contract review and extraction, start with Gemini 3.1 Pro. It matched the top performer on catching contract errors (74% vs. 75%) at about one-seventh of the cost and in 90 seconds instead of nine minutes. If catching every possible issue matters more than time or cost, GPT-5.5 with reasoning turned on found the most. For checking citations in a brief, the best 2026 results came from GPT-5 running as an agent and from Claude Code with Claude Opus, which was the most precise.

How to Use It

  • Give it the documents. Never ask a model to supply case law or citations from memory.
  • Turn on the model's "reasoning" or "thinking" mode for review work. It improved error-catching by 9 to 11 points in contract review.
  • Use it as a first pass and a second reviewer, not the final reviewer.
  • For research, use a tool that pulls from a full, current database of the law, because weak retrieval, not the model, causes many of the errors.

What to Expect

  • Contract extraction (pulling out dates, parties, termination and liability terms): about 80–84% accuracy for the best models.
  • Final contract proofreading (defined terms, cross-references, inconsistent language): the best models catch about three-quarters of errors. On a 60-page agreement, expect it to miss some.
  • Citation checking: nearly all citations to the wrong case get caught, but wrong pinpoint pages slip through 20% to 60% of the time.
  • Research answers grounded in the right documents: roughly 6–11% of answers still contain an unsupported statement.

What to Look Out For

  • Citations from memory. When asked to recall exact citations without sources, even the best model scored under 7 out of 100, and 20 of 21 models gave confident, wrong answers more than 94% of the time.
  • Right case, wrong page. Models tend to approve a citation because the case is on the right topic, even when the cited page doesn't support the point.
  • Questions with a false premise. If your question assumes something that isn't true, models often go along with it.
  • Legal research tools' marketing. Westlaw AI and Lexis+ AI trailed a custom-built tool by 19 to 25 points on a Stanford test.
  • Studies funded by vendors. Some of the best-looking results come from companies selling legal AI. Check who ran the test.

Best Practices

  • Ground every task in source documents, and require the model to quote the passage it relied on.
  • Check every citation yourself at the pinpoint page before filing. Automated checkers help but don't replace this.
  • Turn on reasoning mode for review tasks and accept that it's slower.
  • Test a model on a few of your own documents before rolling it out. Rankings change by task.
  • Re-test when a new model version arrives; this field moves in months, not years.
  • Keep a human reviewer accountable for anything that goes to a court, a client or a counterparty.

What the Studies Found

Contract proofreading. In August 2026, researchers had experienced lawyers plant errors in contracts (misused defined terms, wrong cross-references, wrong party names, contradictions) and tested ten current models on catching them. GPT-5.5 caught 75% of errors, Gemini 3.1 Pro 74%, Claude Sonnet 4.6 69% and Claude Opus 4.7 62%. GPT-5.5 cost $1.38 per contract and took about nine minutes; Gemini 3.1 Pro cost $0.19 and took about 90 seconds. Turning on reasoning mode added 9 to 11 points. Every model was far cheaper than a lawyer, and none was close to perfect.

Contract extraction. A May 2026 study tested models on pulling 26 standard fields out of contracts. Among the major models, Gemini 3.1 Pro scored highest (82%), with Claude Opus 4.6 (82%) and Claude Sonnet 4.6 (80%) close behind and GPT-5.4 at 78%. A smaller legal-specific model built by the study's authors scored 84% at far lower cost. The authors work for Onit, which makes that model.

Made-up citations and facts. A January 2026 study had expert reviewers check 2,700 legal answers from 12 models. Asked without source documents, the best models (GPT-5.2 and Gemini 3.0 Pro) cited something false about 15–17% of the time, and the worst over 30%. Giving the models the relevant documents cut that to about 4–15%. A more carefully built retrieval system brought it below 0.2% for every model.

Research with sources. A March 2026 study found that when models answer from retrieved legal texts, Gemini 3.1 Pro produced unsupported statements 5.7% of the time versus 11.3% for GPT-5.2, and that the quality of the search step mattered more than the choice of model. Its authors sell the search component that performed best. An August 2026 study of eight research setups found unsupported answers ranging from under 10% for the best to nearly half for the worst, with the worst results on questions built on a false assumption.

Westlaw and Lexis. In a February 2026 Stanford study, researchers tested legal AI tools against a Department of Labor survey of state unemployment insurance laws. Westlaw AI scored 58% and Lexis+ AI 64%, while a custom statutory research tool scored 83%, rising to 92% after the researchers found that some of its "errors" were gaps in the government's own survey.

Citation checking. A June 2026 study found more than 1,000 court filings containing fabricated citations, a number growing every year, and tested AI checkers on catching them. GPT-5, working as an agent that looks up cases, caught 83% of planted errors; Claude Code running Claude Opus 4.8 was the most precise and scored best overall. No model reliably caught wrong pinpoint cites, partly because page numbers often sit behind Westlaw and Lexis paywalls. A separate August 2026 study found models catch 93–100% of citations to the wrong case but miss many citations to the wrong page, and even GPT-5.4 with full reasoning missed 40% of wrong pinpoints in court opinions.

Citations from memory. A May 2026 study built from 1,000 real U.S. judicial opinions asked 21 models to recall exact case citations without any sources. The best, Claude Sonnet 4.5, scored under 7 out of 100.

The Bottom Line

The 2026 research is consistent: today's best models, led by Gemini 3.1 Pro, GPT-5.5 and Claude, are useful and cheap for first-pass contract review and extraction when they work from the documents in front of them. They still invent law when asked from memory and still miss wrong pinpoint citations, so a lawyer has to verify anything that leaves the building.

Sources (All 2026)

  • Bang et al., "ContractScrub: A benchmark for final review of legal contracts" (Aug. 2026), arXiv:2608.20204
  • Lincoln et al., "A Few Good Clauses: Comparing LLMs vs Domain-Trained Small Language Models on Structured Contract Extraction" (May 2026), arXiv:2605.05532
  • Dantart, "Reliability by design: quantifying and eliminating fabrication risk in LLMs" (Jan. 2026), arXiv:2601.15476
  • Butler and Butler, "Legal RAG Bench: an end-to-end benchmark for legal RAG" (Mar. 2026), arXiv:2603.01710
  • Das et al., "How Much Do Legal RAG Systems Still Hallucinate?" (Aug. 2026), arXiv:2608.14210
  • Afane et al., "Benchmarking Legal RAG: The Promise and Limits of AI Statutory Surveys" (Feb. 2026), arXiv:2603.03300
  • Liu, Stammbach and Henderson, "Who Checks the Citations? Benchmarking Legal Hallucination Detection" (June 2026), arXiv:2606.21155
  • Verma, "Is this Citation on Point?" (Aug. 2026), arXiv:2608.12571
  • Chen et al., "LegalCiteBench: Evaluating Citation Reliability in Legal Language Models" (May 2026), arXiv:2605.10186
Commercial

Second Circuit Affirms Fee Award That Treated Litigation Funding Costs as Firm Overhead

The Second Circuit has upheld a $4.8 million attorneys' fee award in a sex trafficking case, endorsing a district court's decision to strike time counsel spent communicating with its litigation funder.

In Moore v. Rubin, decided on September 4, a panel of Chief Judge Lohier and Judges Parker and Chin affirmed the award to six plaintiffs who won a $3.85 million jury verdict against former bond trader Howard Rubin under the Trafficking Victims Protection Act. In rejecting the argument that too many timekeepers had been compensated, the panel noted approvingly that the district court had applied a 15% across-the-board reduction and excluded non-compensable tasks, "such as communications with counsel's litigation funder."

The more consequential ruling for funders came below. In February 2025, Judge Brian Cogan of the Eastern District of New York refused to shift roughly $1.84 million in principal and interest owed to a third-party funder, reasoning that how a lawyer finances a practice is irrelevant to the client and the defendant alike. "Whether it is a bank loan, family loan, personal assets, or a litigation funder," he wrote, "it is overhead."

Judge Cogan also declined to follow the English decision in Essar Oilfield Services v. Norscot Rig Management, which allowed recovery of funding costs, observing that neither the statute nor the local rule hints at such recovery.

The funding cost denial was not before the appellate panel, as Rubin appealed only the fee award. The funder, Pravati Investment Fund IV, later sought unsuccessfully to intervene to protect its interest in the fees after the plaintiffs' firm dissolved.

Commercial

Legalist Asks Manhattan Federal Court to Confirm $108,718 Award Against Funded Claimant

Litigation funder Legalist has asked a federal court in Manhattan to confirm an arbitration award against a claimant it financed, in a rare public dispute between a funder and the plaintiff whose case it paid for.

As reported by Bloomberg Law, Legalist filed its petition on September 8 in the Southern District of New York, seeking to confirm a partial final award of $108,718.45 against Mario Rinaldi. The award, issued on May 18 by JAMS arbitrator the Hon. Elaine Rushing (Ret.), consists of $105,218.45 in attorneys' fees and $3,500 in arbitration costs.

The funding agreement dates to June 2018 and financed Rinaldi's suit against two French champagne producers, which he brought after working to build their brand in New York. A jury returned a $1.5 million verdict in his favor in March 2022, and final judgment with prejudgment interest was entered that December at $2,318,506.85. That judgment has not been collected. Rinaldi told Bloomberg Law he is still pursuing the money with his own resources, having retained French counsel to enforce it abroad.

Legalist alleges in its filing that Rinaldi breached the funding agreement by refusing to cooperate in collection efforts, including by declining to permit communication with his French counsel. According to the memorandum, Rinaldi did not appear in the arbitration at any stage, and has not moved to vacate or modify the award.

The arbitration was held open for Legalist to pursue further relief, indicating the $108,718.45 may not represent the full extent of its claim. No response from Rinaldi appears in the most recent public docket entries.

Commercial Consumer

ClaimAngel Reports $144M Deployed and 30,000 Fundings on Consumer Legal Funding Marketplace

South Florida consumer legal funding marketplace ClaimAngel says it has deployed more than $144 million across over 30,000 individual fundings since launching in April 2023, positioning standardised pricing as its answer to the cost criticisms that dog the consumer funding sector.

As reported by Refresh Miami, the platform runs a marketplace in which 27 funding providers compete for cases, with funders reserving a case in an average of 11 seconds. Advances carry 27.8% simple interest with no compounding and a 2x cap on total repayment, and remain non-recourse — plaintiffs owe nothing if the case is lost.

The company reports serving more than 14,500 plaintiffs and over 750 law firms, with 46 employees. A Case Equity product lets plaintiffs draw against expected case value for living expenses while litigation is pending.

ClaimAngel was co-founded by Jeremy Alters, a trial lawyer of more than two decades who was disbarred by the Florida Supreme Court in 2018 for misusing client funds, and his son Logan Alters. "I did things wrong. They were my fault. I take full responsibility for it," Jeremy Alters said, describing the company as "born out of an ethics issue." He applied for readmission to the Florida Bar in 2025.

Planned expansions include attorney funding, a secondary marketplace for buying and selling existing positions, and AngelScore, a data-driven underwriting system.

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