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Commercial Legal Innovation Special Features

Key Takeaways from LFJ’s Podcast with Steve Shinn

December 13, 2021

Key Takeaways from LFJ’s Podcast with Steve Shinn

On the latest episode of the LFJ Podcast, Steven Shinn, founder of FinLegal, described the solutions his platform provides for both funders and lawyers, and explains his company’s points of differentiation with other third party platform providers.

Q: Why move into litigation funding and after-the-event insurance? Can you explain how FinLegal’s offerings are different than those of traditional funders?

A: Absolutely. I think one of the challenges is that the litigation funding market could grow a great deal. But there are challenges where lawyers don’t necessarily understand litigation funding, and there are a lot more funders that you can go to. So you want to help educate people who are new to litigation funding and ATE about how to access it and how it works.

There are more funders joining, which is increasing the number of claims that get funded. So whereas before you might have only had funders looking to deploy $5 million to a claim, you now find situations where there are funders who want to deploy as little as $100,000 or less. So there’s a much broader range of funders…and it’s hard to go to all of them individually and it’s hard to know who’s in the market.

We thought, let’s build a sticky platform which provides the law firm with visibility and control over those funding requests, and let’s give them an online process (to write the best possible funding request) in terms of how it’s positioned to the funders so that it does get funding. With lots of funders to navigate, let’s build a platform to help lawyers navigate them, help them understand it—and let’s help them put forward the request with the best possible positioning.

Q: You mentioned getting involved in group actions (the UK version of US-style class actions). What got you interested in that space particularly, and does your technology background in any way penetrate that space?

A: Definitely. It started out as me seeing the VW group claim, and also seeing cartel claims, price-fixing on football shirts, and things like this. With my technology background, I thought ‘Well, how are law firms doing this?’

I saw that they had a lot of off-line case management platforms, they use a lot of spreadsheets. You know these systems didn’t talk to each other. There’s a lot of manual effort and no mobile interfaces for claimants to interact with the law firm. So I thought, ‘We can build a platform that will enable that.’ Essentially, we’d be taking a completely fresh look at it. With a technology and software development background and a product development background. How do we build/provide something that enables lawyers to spend the least time possible working with each claim. We know that’s important to the economics of the claim—not having to spend a lot of manual effort on each claim.

So that’s what we produced, a solution that works on a management by exception basis, so essentially the claimant goes through an automated set of steps. And where they fall out of those steps or where they don’t meet certain criteria, only then do they need to get picked up by the law firm.

Q: I know you offer a claim automation solution, can you explain what this solution does?

A: The main benefit of the solution is that it increases the volume of clients. So what you tend to find, is if there’s a bad claimant experience, people fall out of the process. You’ve spent money on acquiring that claimant, you spend advertising pounds or dollars to get them into your funnel, to start working with them. But they become disenfranchised from your process, right? Or they don’t like getting a lot of phone calls, or they feel like the process is insecure and it happens via Email without clear instruction. So if you have a good online process, it increases the volume of clients. That’s the first thing.

And it reduces the amount of time spent per client also, because…the law firm is only working with clients who fall out of the automated process. It’s also plug-n-play, so if you want to start work on a new type of matter it might be that this week you’re building a book of emissions claimants, and the following week you want to launch a shareholder claim.

You can launch that from the platform in a matter of days and start book building. You’re not having to have lots of different contractors and different systems that you have to modify to start doing something new or different. You talk to us, we set it up for you, and then you manage it through an interface that you’re very familiar with.

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Commercial Special Features

How AI-Powered Screening and Monitoring Reduce Duration Risk

By Ankita Mehta |

Written by Ankita Mehta, founder of Lexity.ai - a platform that helps litigation funds automate deal execution and prove ROI.

In litigation finance, you can win the case and still lose money.

This is often due to duration risk – the silent, persistent killer of a fund’s IRR. It’s a primary threat to projected returns, tying up capital for months (or years) longer than planned. In a market where every delay erodes value, monitoring becomes a critical, high-stakes function.

For years, that monitoring process has relied on analysts manually scanning dockets and then logging events in a static spreadsheet. But let’s be clear: this is no longer a sustainable process. It’s a liability.

The true failure of the manual model is twofold. First, the initial diligence (often taking weeks) is too slow and key for preventing loss of deals, and second – when a new development is spotted, analysts have no way to measure its downstream financial impact. By the time a human calculates the damage of a delay, the damage is already done.

This article provides a pragmatic framework for shifting from this reactive, "dead data" model to a proactive, AI-driven workflow.

Early warning signs your team is likely missing

Your expert team is your greatest asset, but they are buried in the grunt work of diligence and shallow monitoring. Ironically, the highest-value insights are lost in this process.

Here’s what that looks like in practice:

  1. A "minor" discovery motion is spotted by an analyst. They note it in an Excel file. What they can't do is instantly model its domino effect on the summary judgment and trial dates, or see that this exact motion by this opposing counsel has historically added 90 more days.
  2. A late expert report is received, which is logged as a single missed deadline. The team lacks a system to immediately see how this one event threatens the entire return profile by breaking a chain of dependencies.

An analyst’s “gut feel” about a jurisdiction is helpful. But a workflow that quantifies that gut-feel by comparing a new case against historical jurisdictional data is infinitely better.

The solution? An AI-powered analytical workflow

No, this isn’t me writing about a "magic" AI tool. This is more about having a disciplined AI-powered workflow that gives your team the right analysis at the right time by pulling out the relevant data for accurate decision making. Here, the value isn't in just finding a new event, but in understanding its impact instantly.

A carefully thought out workflow delivers value on three distinct levels:

  1. Automated diligence and baseline modeling: The system first ingests the initial case documents, automatically extracting critical milestones and deadlines. This alone cuts initial review and diligence time by over 70% and creates an accurate, "live" baseline model of the case before a single dollar is deployed.
  2. Proactive impact analysis: This is the crucial step. When an analyst spots a new development (from a docket or a counsel call) and inputs it, the platform instantly analyzes its impact. It connects that "minor" motion to the entire case timeline and budget, flagging the precise IRR and duration risk. This shifts the team from a "data entry" to a "proactive risk management" role.
  3. Portfolio-level pattern recognition: The system links procedural changes to their impact on case valuation and portfolio returns, flagging delay-patterns that a human analyst under heavy load could otherwise miss.

The ROI of proactive mitigation for your business

Here’s the business case for moving beyond outdated manual processes:

Benefit #1: Protect your projected IRR

Instead of reacting to delays or logging events in a void, you can now start measuring their impact the moment they happen. A modern workflow gives you the foresight to have critical conversations or adjust reserves before a slight delay can escalate into a crisis.

Benefit #2: Save your team the “grunt work”

The experts don’t need to spend a disproportionate amount of time to do data entry or check dockets. Think of it like cutting with a blade: the work will get done eventually, but without a sharp blade it takes far more time and effort. 

Here, having the right AI-powered workflow can sharpen that blade so routine monitoring happens instantly and your team can focus on the actual analysis that drives returns. 

Benefit #3: Create a defensible, data-driven risk model

Move your risk assessment from a subjective “gut feel” to an objective, consistent data-backed model based on facts and verification that your investment committee can rely on every time.

The impact of this shift is tangible. According to our firm’s benchmarks, a $500M litigation fund we work with cut diligence time by 70% while tripling its case throughput.

A pragmatic framework for your first AI workflow

For a non-technical leader, “adopting AI” can sound like a complex, six-month IT project. But it needn’t be this way. Allow me to share with you a clear three-step framework for a successful, low-risk adoption.

Step 1: Identify the grunt work

Start by asking “What repetitive, low-value tasks steal time from real analysis and what would be the value to the firm if we could automate these tasks using technology? Here, the goal isn’t to replace your experts’ judgment, but to empower them to take on more cases while keeping their judgement intact.

Step 2: Start from a single high-value problem

Don’t try to boil the ocean. The goal is not to merely “implement AI” and tick a box. You are doing this because you want to solve one specific business problem (e.g. preliminary case assessment). For many funds, this alone could become a 2-3 day manual bottleneck. With the right workflow, it’s possible to complete this in under half a day. Solve that one piece of the puzzle, prove the ROI, then scale up.

Step 3: Focus on your process and not the tech

When evaluating any solution ask: “How does this fit into our existing workflow?” If it requires your team to abandon current processes and learn from scratch, the adoption rate won’t exactly be high. The right solution should enhance your process – and not just add pile more tech on top of it.

Conclusion

These days, duration risk has shifted from being an unavoidable reality of doing business to yet another variable we can control. Keeping the old approach of manual monitoring could put your value, and your capital at risk. Conversely, by embracing AI in specific processes, you get a pragmatic and provable way of shielding your capital and your IRR, all while empowering your team to do what they do best. Implementing AI the right way will give you a definite boost in efficiency and returns, just depends on implementing it the right way.

But how do you build a business case for this shift? The next step is moving from the operational benefit to assessing ROI. More on this in another article.

Commercial

Insurance Industry Groups Push for Federal Court Rule Requiring Litigation Funding Disclosure

By John Freund |

A coalition of business and insurance organizations is calling on the federal judiciary to adopt a uniform rule requiring disclosure of third-party litigation funding arrangements in civil cases, arguing that the current patchwork of approaches across federal courts undermines fairness and transparency.

As reported by Insurance Journal, the Lawyers for Civil Justice and the U.S. Chamber of Commerce Institute for Legal Reform submitted a joint letter to the Advisory Committee on Civil Rules urging the creation of a disclosure requirement. The American Property Casualty Insurance Association has also thrown its support behind the effort, with executive vice president and chief legal officer Stef Zielezienski stating that "transparency about who has a financial stake in litigation is essential to fairness, accountability, and the effective administration of justice."

The push comes amid growing evidence that the absence of a federal standard has created inconsistent outcomes. A recent study cited in the letter found that federal district judges granted only 40% of motions seeking some form of TPLF disclosure, leaving litigants and courts without clear guidance.

The financial stakes are significant. Research from EY, presented at APCIA's annual meeting, found that average commercial claim costs have risen 10% to 11% annually since 2017. The analysis projects that third-party litigation funding could cost the insurance industry up to $50 billion in direct and indirect expenses over the next five years.

The groups are recommending that current disclosure rules be expanded beyond insurance contracts to include any entity or individual providing funding or holding a financial interest in the outcome of litigation. The Advisory Committee is expected to consider the proposal at its upcoming April meeting.

Commercial Special Features

Smarter Intake for Litigation Finance Firms

By Eric Schurke |

The following piece was contributed by Eric Schurke, CEO, North America at Moneypenny.

From the very first interaction, litigation finance firms and legal teams should be capturing structured, decision-ready information that enables early case assessment, risk evaluation, and efficient routing. 

This typically includes:

• Who the potential claimant or referrer is and their preferred method of communication
• The context of the matter, including jurisdiction and type of claim
• The stage, urgency, and timeline of the case
• Key parties involved and any relevant documentation
• How the opportunity originated

When captured consistently, this information allows for faster triage, more effective screening, and quicker progression from initial enquiry to investment decision. 

What are the most common mistakes organizations make when handling inbound investment or M&A inquiries?

In litigation finance, the most common mistakes are operational but they have direct commercial and reputational consequences:

1. Slow response times
Prospective clients often contact multiple firms at once. Delays can signal lack of availability or interest.

2. Unstructured information capture
Inquiries can come in over the phone, through email, website forms and LinkedIn, resulting in fragmented or incomplete information.

3. Over-automation or under-humanization
Generic automated responses can feel impersonal, while entirely manual processes create inconsistency and delays.

4. Poor routing and follow-up
Without clear ownership, communications can sit in inboxes or be passed between teams meaning opportunities can stall or be lost internally.

Ultimately, the biggest mistake is treating first contact as administrative rather than strategic, when, in reality, it is the starting point of deal quality.

The most effective approach is a hybrid one - using technology for speed, structure, and consistency and people for judgement and relationship-building.

Technology can:
• Capture and structure case data
• Provide immediate acknowledgement
• Ensure questions are routed quickly and consistently
• Create a clear audit trail

People can:
• Understand nuance and context
• Build rapport and trust
• Ask the right follow-up questions
• Represent the funder’s brand and values

At the start of any case or investment journey, relationships matter. Technology should enhance that experience, not replace it.

What measurable impact can better first contact have on pipeline strength, relationships, and deal outcomes?

Stronger first contact directly improves:

  • Pipeline quality: better intake leads to more qualified, investment-ready opportunities
  • Conversion rates: fast, more professional responses increase engagement and exclusivity, as well as the likelihood of securing instructions
  • Investor confidence: structured early-stage data improves decision-making
  • Operational efficiency: less time chasing incomplete information and faster conflict checks
  • Deal velocity: quicker progression from enquiry to evaluation and funding decision.

Small improvements at the top of the funnel compound across the entire investment lifecycle.

If firms could make just one or two changes today to improve their approach to inquiries, what would you recommend?

1. Create a standardized intake framework
Define the essential data needed for case screening and risk assessment, and ensure it is captured consistently across every channel.

2. Treat first contact as a strategic touchpoint
Ensure every enquiry receives a prompt, professional and human response that reflects the firm’s brand and client-care standards.

In litigation finance, early impressions don’t just shape relationships, they shape deal outcomes. These two changes alone can significantly improve conversion, efficiency and client relationships.

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Eric Schurke is CEO, North America at Moneypenny, the world’s customer conversation experts. He works with legal firms, litigation funders, and professional services to transform how they manage and qualify inbound opportunities. Eric is passionate about helping organisations strengthen deal flow, improve first impressions, and deliver exceptional client experiences from the very first interaction.