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An LFJ Conversation with Steve Nober, Founder/CEO of Consumer Attorney Marketing Group

By John Freund |

An LFJ Conversation with Steve Nober, Founder/CEO of Consumer Attorney Marketing Group

Steve Nober, the founder and CEO of Consumer Attorney Marketing Group (CAMG), has been a significant force and innovator in the legal marketing industry for over 15 years. Often hailed as the Mass Tort Whisperer℠, Nober earned his reputation through over a decade of spearheading successful mass tort campaigns and fostering close relationships with top handling firms, showcasing unparalleled expertise in the mass tort arena. He is a sought-after speaker, presenting at over 40 conferences annually, across the United States and globally, covering a range of topics, including best marketing practices, ethics in advertising, and litigation funding. Under Nober’s leadership, CAMG has grown into the largest fully integrated legal marketing agency in the United States, steadfastly committed to its core values of ethics first, transparency, innovation, and efficiency. With a remarkable career spanning over 30 years, Steve Nober has demonstrated executive leadership and innovation in marketing, media management, and digital and computer technologies. His experience includes managing mergers and acquisitions, corporate turnarounds, and startups. In the advertising sector, his specialties include direct response marketing, digital and offline advertising, and lead generation strategies, as well as media buying and analysis, particularly focused on the legal sector. Below is our LFJ Conversation with Steve Nober: CAMG breaks down mass tort claims into early, mid and late stage. These are segmented by expected time to settlement, with early being 30-48 months, mid being 18-30 months, and late being 6-18 months.  How does the value-add of CAMG change as cases make their way from early to mid to late stage?   The value CAMG brings to each stage is a bit different and I will explain. The first value proposition CAMG bring to clients for early-stage cases is similar to the answer to your question 3 below in regards the modeling, leveraging historical data, targeting and projecting what the origination costs will look like is key to being ready to jump into a new and early tort. Also, understanding criteria that leadership handling law firms would like to see used to qualify an injured victim is critical to have knowledge before starting.  Also, in this early stage knowing who the key handling law firms that are going to make a move to be in leadership for the various torts is a key decision that needs to be made as all things are set up to begin.   These are all part of the CAMG process to help our clients begin deploying capital into the early stage torts.
I am often referred to as “The Mass Tort Whisperer®” which really means we are usually very early in hearing about early new torts, late-stage torts that may be settling soon, etc.
This information can be traded on so it’s quite valuable as we can help our clients use much of this information to make capital deployment decisions. The value for mid stage is a combination of value we bring for early and some of the value propositions mentioned in late stage. Knowing the handling firms that have been really serious about the tort and in leadership is key.  The modeling financials can get more detailed with projections and less guessing since the tort will have moved from early to mid-stage.  Following the tort activity in the litigation is key to understanding the direction that leadership sees for each tort and how bullish they are is key to an investor deciding to deploy capital for the tort.    Our value for the mid stage is key being the tort is mid-way thru the life cycle and so many variables need to be considered prior to investing. The value of late stage is knowing which law firms would be considered the best handling firm to work with that can maximize settlement values or which firms are in settlement negotiations and can still take more cases would be two good examples. Also, having the data to model out what fallout/attrition looks like with late-stage cases is key since it may be higher than the earlier stages.   The late-stage torts are a great opportunity but financial modeling and picking the right partners are key.  Also, the marketing/origination of cases needs to be handled very precise and almost scientific like to make sure cases can still be acquired at costs that make sense taking the criteria in mind of the possible handling firms.  There’s quite a bit of value we bring to these late-stage campaigns for our clients. At which stage of the case life are you currently finding the most attention from litigation funders?  Where is there the most room for growth?  The most attention goes to late-stage torts due to the projected shorter time to settlement vs. the early and mid-stage torts.  If there’s more capital to spend annually, we see more diversification with the heavy weight still on late stage and smaller percentages of total capital going to the mid and early stages. We educate our clients on costs and risk for each stage tort.  The late stage is typically higher, but risk of a settlement is much lower since it’s a mature tort, there’s more history and analysis that can be done on how the tort has progressed.   The early torts are just emerging or will have recently passed Daubert so being early the costs are much lower and risk a bit higher since the litigation will be early in starting.  Mid stage gives you a bit of all with costs not as high as late stage and risks a bit lower than the torts just starting out.
There are a limited number of injured victims in each tort, and we always need to be careful not to put more capital than we project we can spend, or costs of a case will drive higher pretty fast.
With larger capital clients we are moving into other torts whether late stage as well or mid and early stages to help diversify. One interesting note as we diversify clients is deploying capital into some torts that are closer to personal injury cases vs. traditional mass torts like Asbestos and Sex Abuse as two examples.  The time to settlement in these are closer to what we see in auto accidents being around 18 months, these are interesting torts to diversity capital and see shorter settlement times that some of the longer mass torts. The answer to the question about where room for growth is would be from the early-stage torts in being that there typically has not been a large amount of marketing yet to acquire cases so the possible total cases available would be quite high and with costs being fairly low.   This is usually where we can deploy the most capital vs. the other stages. When it comes to modeling out the expected costs, timeline and return, you look at a variety of factors here.  Can you explain what those factors are, and how do you weight each of those from case to case (is there a standard algorithm, or is the weighting bespoke to each case?)  When modeling out the expected costs, timeline, attrition and projected return, we consider a variety of factors to ensure a comprehensive analysis. These factors can include:
  1. Historical Data: Past performance and outcomes of similar cases provide a baseline for expectations.
  2. Targeting Data: We subscribe to very sophisticated targeting and demographic syndicated services such as Kantar and Neilson.  Once we have targeting details on who the injured victims are, these targeting services help is see which advertising mediums and channels index the highest to reach them.
  3. Active Campaigns: We are typically running active campaigns for most of the more popular mass torts so building up recent cost details is something we are looking at every day to optimize the performance response data which keeps costs of origination lower by being very quick to move capital where response and quality of cases are best and stop the capital spend in areas that are not showing a response that makes sense to continue.  This is Moneyball for Marketing, and I speak about this often at conferences.
  4. Market Conditions: Current trends in the legal market and any external factors that might affect the case.
  5. Attrition or Fallout: This is key with modeling out costs of originating a real quality case.  We watch very close as the tort matures from early to mid to late stage how the fallout or attrition of the new signed case is trending.  Once a claimant is signed with a law firm, some of these will not turn into a case as all of things are verified.  Medical records for example will always have a percentage of cases where there are no medical records or the records show a different injury, etc.  These need to be projected into the modeling at the very beginning and they vary from tort to tort.
  6. Intel from Leadership Firms: Our relationship with firms in leadership allow us to receive regular updates on the estimated timeline and estimated settlement values.
As for the weighting of these factors, it tends to be bespoke rather than algorithmic. Each case is unique, and while we do use historical data and standard metrics as a starting point, the specific circumstances of each case require a tailored approach.  The key metrics are seeing where the full costs are to originate compensable case and what the projected settlement range looks like so the various torts can be compared from an ROI analysis. You provide a wealth of intelligence through your Legal Marketing Index.  What can law firms and litigation funders expect to find there, and how is this intelligence useful?  We publish what we call the Legal Marketing Index or LMI for short and this is what we use to provide some of the data we collect that we share with the industry.  This data is broken down by each mass tort and includes extensive details that we have aggregated from large case volume so the data tends to be spot on as a baseline on what we see and can be expected if a law firm or fund wants to move to be active in a particular tort.  We are publishing date on topics such as injury details, demographics, geographics, case concentration in cities around the country, media details, call details, etc. Some of the intelligence is useful and some just interesting to review.  An example of how the data is critical to know before moving into acquiring cases for a tort would be the following:  If you wanted to acquire hernia mesh cases but knew that only a few manufactures are defendants and the rest of the hernia mesh devices do not make sense hold onto as a case, knowing what percentage of cases of every 1,000 are which manufacturer’s would be key to calculating the real costs of finding the right hernia mesh cases with the right manuf. Product vs. all others not making sense to keep.    People who have had hernia mesh surgeries usually have no idea which manufacture mesh device was used so when signing these cases there is no way to know how many are actually going to be what you were looking for until medical records are pulled which can me many months down the line.  So, being able to predict before starting what those percentages will be is critical to calculating costs on cases and to see if the ROI is enough to move ahead or not. One more example would be Talc cases which cause ovarian cancer and defendant is Johnson & Johnson.  This litigation has gone on for quite a while so now many of the cases signed end up not being a good case to keep so there’s fallout or what we call attrition after medical records are pulled.  Having this recent fallout data from the medical records with a sampling of a large pool of records is key to the modeling ahead of time and again, to see if ROI makes sense to move ahead given the fallout may be quite high. A third example would be for the litigation PFAS and the leadership handling firms have set a fixed criteria on which cancers they would accept and sign a claimant vs. others they would not sign.  We collect the data on “type of cancer” for thousands of calls and have published the breakdown of each cancer callers have in descending order.  A review of this data would help see for every 10 or 100 calls from victims who may qualify, how many from the total would have a qualifying cancer.  Again, this helps project out costs of a case to sign using the data to help model correctly. These are just a few quick examples of how some of the data we publish is quite valuable to firms looking to move into the various mass torts. What are some of the main questions / concerns you receive from litigation funders, and how do you address these?  Here are a few of the more common questions we get from litigation funders: What are your investment minimums? While we have no minimums, we don’t think the funding program makes sense for less than $2m-$3M as a minimum if that helps the fund with getting started.  Averages tend to be more like $5m-$10M as first run and many come to us with $20M+ as first year to start.   How long does it take for you to deploy capital? That depends on market conditions and performance of each tort but typically we are starting and originating cases within a week of receiving capital so it’s usually quite fast to start.   We have weekly meetings with our clients to discuss the most intelligent deployment strategy taking all things into consideration at that time. We are always sensitive to scaling while keeping acquisition costs within the forecasted range What is your primary role? The primary role is to manage the curated program which includes many pieces.  I would say the actual origination of cases which includes the marketing, call center screening & case signing is primary.   Not to take away from how critical the financial modeling, handling firm choices and leveraging our relationships with these handling firms is key.  There are many key value pieces we bring to a client of ours so tough to answer since we think all are so important. Does a funder client of CAMG have to use a handling law firm CAMG introduces or can we they use their own existing relationships?
We are happy to collaborate with your existing law firm relationships, but we really try to stick to the requirements we think make for a great handling firm and we would want to see if the law firm you may want to use meets the standard.
The key things we look for are the following:
  • Are they in leadership in the MDL for the tort being discussed.
  • Are they a real trial firm with a rich history of litigating cases and a threat to the defendants?
  • Do they have the infrastructure to take on more cases from this program
  • Will they agree to an equity split on the partnership that we think makes sense
  • Are they good people to work with in general
Choosing the right handling firm has never been more important considering how many of the settlements have been structured the last few years.

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John Freund

John Freund

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LFJ Conversation

An LFJ Conversation with Jason Levine, Partner at Foley & Lardner LLP

By John Freund |

Jason Levine is an antitrust and commercial litigation partner in the Washington, D.C. office of Foley & Lardner LLP.  He previously served as the D.C. office head, and head of U.S. antitrust strategy, at Omni Bridgeway, a global commercial litigation finance company.

Jason’s legal background spans over 25 years in private practice as a first-chair trial lawyer and antitrust litigator in several multinational law firms.  He has tried over a dozen cases and served as lead counsel for plaintiffs and defendants in numerous billion-dollar disputes, including defending against two of the nation’s largest antitrust MDLs.  Jason graduated cum laude from Harvard Law School and clerked for Judge Randall Rader on the U.S. Court of Appeals for the Federal Circuit.

Below is our LFJ conversation with Jason Levine:

Where does litigation finance add the most value in antitrust cases, particularly given their scale, duration, and cost profile? 

As in any complex dispute, litigation finance adds significant value in antitrust cases by shifting the risk of fees and legal costs away from the plaintiff or the law firm and to a funder.  Antitrust cases are particularly well-suited to litigation finance because they can be exceptionally costly, require specialized counsel and often multiple expert witnesses, tend to have a long duration, and can involve massive amounts of discovery.

The aspects of the case where a financing arrangement adds the most value will vary depending on the funding mechanism.  If a law firm is handling a matter on a contingent fee basis, then the greatest value from financing typically comes from covering the legal costs the firm would otherwise advance on its own.  Outside a contingent fee scenario, financing is most important in paying counsel’s legal fees, although the funder may also cover legal costs.  The universal point is that, for companies pursuing antitrust litigation, financing can be very attractive because it is non-recourse, permits the company to reserve its legal budget for defensive and compliance matters that are not amenable to financing, and helps convert the legal function from a proverbial “cost center” into a revenue generator.

Funding also increases the client’s options for which counsel to retain, which is particularly important in antitrust cases given their nature.  With outside financing covering legal fees and costs, the client can focus more on the expertise and “fit” of counsel than on their billing rates.  Relatedly, litigation finance can enable a small company to hire a “Big Law” firm that doesn’t offer contingent fee arrangements, rather than potentially being limited to a firm that does.  The same point applies to expert witnesses, making the top echelon available whereas they might otherwise have been prohibitively expensive.

In short, with a meritorious case and litigation financing behind it, a small corporate plaintiff can match a much larger defendant’s litigation resources.  This benefit of leveling the playing field is very clear in antitrust cases, given their scope and cost to litigate, which helps explain why they are funded at a higher rate than most other categories of commercial litigation.

Are there specific types of antitrust claims or procedural postures where you think funding is especially well suited?

Funding is very well suited to antitrust claims where a company has opted out of a class action and is pursuing its claim independently.  This is particularly true if the opt-out occurs after the putative class action has survived motions to dismiss, if not class certification.  At either point, a funder will consider the opt-out case at least partly de-risked.

This benefits the funder because the case is less risky and will have a shorter remaining duration.  It benefits the funding counterparty because the funder’s required return should be lower, given the de-risking, leaving more of the proceeds for the client and the law firm to share.  Substantively, funding is well suited to various kinds of antitrust cases, so long as quantifiable money damages are at stake rather than solely injunctive relief.

What regulatory or legislative developments in litigation finance should antitrust litigators be paying closest attention to right now?

There is significant activity at both the federal and state level that warrants attention, although not specific to antitrust cases.  At the federal level, bills have been proposed that would seek to compel detailed disclosures of the existence and details of litigation financing arrangements, including to the adverse parties.  Another bill would seek to largely shut down the involvement of foreign entities in litigation finance, both by prohibiting the practice by certain state-affiliated actors and also by requiring extremely detailed disclosures by others.

Although it’s fair to say that none of these proposals are a very high legislative priority, they definitely warrant attention, given how far the proposed federal tax on litigation finance proceeds progressed in 2025.  That tax has not been formally re-introduced yet, but that is another possibility that would merit watching.

As the midterm elections in 2026 draw closer, the prospects for movement on any of these proposals will likely decrease, with the exception of a possible “midnight rider” slipped into a year-end Appropriations bill.  That’s something else to watch out for.  In addition, the Advisory Committee on the U.S. Federal Rules of Civil Procedure is considering potential Rule amendments involving disclosure of litigation funding uniformly in federal cases, and this is worth monitoring as well.  Given all these developments, defendants have an increased incentive to seek information about litigation funding arrangements through discovery requests.

At the state level, at least a dozen states are perennially considering different disclosure regimes and regulations that would complicate the use of litigation finance.  Some of this is performative, having failed multiple years in a row in some states.  I would keep a particularly close watch for state-specific versions of the litigation finance tax that failed to pass in the U.S. Senate last year, especially in California, New York, Texas, Florida, and Illinois.

How do you expect evolving disclosure or taxation proposals to affect big firm strategy in funded matters?

Certainly, large law firms that are considering funding arrangements, or that have them already, will be monitoring the regulatory landscape for important developments.  I would anticipate that the imposition of new regulations in general will cause firms to focus closely on compliance, both on their part as either funded counterparties or as counsel to them, and also on the part of funders.  This might lead to a tendency to favor larger, more established funders that have robust internal compliance capabilities.

Law firms and their funded corporate clients will also likely scrutinize funding agreements even more carefully.  Similarly, if any new industry-specific taxes are enacted, law firms will likely focus on funders’ ability to adapt their return structures to minimize the passed-through impact.  Pricing in line with the market is always important, but potential tax changes could highlight this even more.  Greater regulation could also lead to further consolidation in the litigation finance industry, leaving fewer – but likely larger – companies in the space, making it all the more important for law firms to seek out whatever edge a particular funder can provide in a deal.

I would not expect any new disclosure or taxation regimes to change the way law firms actually litigate their cases, with the exception of disclosure requirements giving rise to more discovery efforts aimed at funding arrangements.  It is possible that a new, aggressive disclosure regime could give certain companies pause about pursuing funding, but I also consider this unlikely to change law firm litigation strategy.

Based on your own transition, what advice would you give Big Law partners or senior associates considering a move into litigation finance or a finance adjacent role?

I would advise them to be patient and to focus on relationships.  Litigation finance companies do not have a classic recruiting pattern like law firms do.  Headcounts tend to remain steady, with opportunistic hiring for purposes of expansion or replacement of departing personnel.  I know several people whose transitions from a law firm into litigation finance took over a year because there simply weren’t openings available.  In that situation, it’s important make contacts at one or more companies and check in with them periodically, because expressing interest in a position and staying top of mind can make all the difference.  A warm internal introduction is much more valuable than cold outreach.

I would also recommend gaining direct exposure to litigation finance before seeking out a position.  Funders will favor partners and associates who have previously handled funded litigation or at least negotiated deal terms with a funder.  This not only credentializes the job-seeker’s interest in a role, it also demonstrates some familiarity with the industry and how it operates.  Relatedly, job-seekers should learn as much as they can about the funder as possible before approaching it.  What kinds of cases does it fund?  Does it have geographical limits, or funding amounts that it favors?  This information is often on the company’s website, and knowing it shows diligence and also helps ensure fit.  For the few publicly traded funders, I strongly recommend reviewing investor materials and annual reports before interviewing.

In addition, particularly for partners, I would emphasize the importance of objectively assessing one’s network and prospects for helping to generate deal flow.  Similar to a law firm, at most funders, origination is a key aspect of a more senior role.  What is your base of potential funding clients?  Do you have strong contacts with litigation business generators at multiple law firms, or with well-placed in-house counsel at companies with suitable litigation?  Are your contacts limited to particular kinds of litigation, and if so, are those ones that tend to receive funding?

These are important questions to answer as granularly as possible before approaching a funder for a job.  For more junior lawyers, consider where you would fit in the funder’s structure, and how you can add value, particularly in the nuts and bolts of underwriting cases.  Here, again, subject matter is important.  Expertise in areas of law that don’t yield funded cases is unlikely to support the business care for a new hire.

LFJ Conversation

An LFJ Conversation with Thomas Bell, Founder of Fenaro

By John Freund |

Thomas is the Founder of Fenaro, a modern fund management platform for litigation finance. He holds a law degree from Durham University and has spent his career designing and delivering large-scale, complex financial services platforms. Prior to founding Coremaker's Fenaro product, he spent much of his career at Accenture, PwC, and other management consulting firms, working with global banks, asset managers, and institutional investors.

Below is our LFJ Conversation with Thomas Bell:

The litigation finance industry has grown to over $16 billion, yet your blog notes that many firms still run on spreadsheets. What specific operational pain points do fund managers face with legacy systems, and how does Fenaro address them? 

Despite the industry’s rapid growth, most litigation funders continue to rely on in-house spreadsheets or fragmented systems that are not designed to handle litigation finance. From our conversations with funders across the market, three operational pain points consistently arise.

The first is calculation risk. Funders regularly tell us about issues arising from manual models and fragile data infrastructure, ranging from investor reports needing to be reissued due to errors (surprisingly common), to material budget discrepancies only being identified late in a case lifecycle (less common, but in some cases career-ending). Purpose-built fund management systems substantially reduce this risk by centralising data and automating complex calculations.

The second is friction with law firms after a deal has closed. One funder summarised their biggest challenge as “getting lawyers to think in IRR terms.” In practice, this reflects the lack of efficient processes for tracking budgets, agreeing drawdowns, reviewing invoices, and sharing case updates. Fenaro addresses this through the borrower portal, which provides law firms with a structured and transparent way to work with funders throughout the life of an investment, resulting in a much more positive relationship.

The third is operational complexity limiting scale. Many funders speak candidly about ambitious growth plans being constrained by manual reporting, bespoke processes, and operational bottlenecks. Without greater standardisation and automation, it is difficult to scale portfolios or support increased institutional participation. Fenaro is built from the ground up to reduce the overhead of operational processes, while giving funders all the key information required to focus on growing and managing the fund.

Mass tort portfolios can involve thousands of individual claims with constantly shifting data. How does your platform help funders track, value, and report on these complex portfolios without drowning in manual updates? 

In mass tort strategies, some funders are managing regular updates across tens or even hundreds of thousands of individual claims and many different law firms. Several have told us that keeping this information accurate and up to date is a data nightmare that quickly becomes unmanageable, and worry they’re spending too much time on administrative data-wrangling efforts, and not enough time on actually mining the content for value.

Fenaro is designed to process high volumes of case data from multiple law firms in a consistent format. Updates can be submitted through borrower portals or uploaded directly, allowing funders to see the status, valuation, and history of every claim at a glance. As part of this process, the platform runs validation checks and identifies potential duplicate claimants, a serious and well-known issue in mass tort funding. The same validated data is then used to produce investor and internal reports without the need for manual reconciliation.

You've written about the challenges funders face when lending to law firms—particularly around monitoring how capital is deployed. What visibility does Fenaro provide, and how does that change the funder-firm relationship? 

We frequently hear that fund visibility tends to drop sharply after capital is deployed. Monitoring budgets, drawdowns, and expenditure often relies on periodic reporting and manual review.

Fenaro provides funders with continuous visibility at both the portfolio and case level. At the same time, Fenaro gives law firms access to a free borrower portal. Contrary to the perception that firms resist new technology, many lawyers have told us directly that they are willing to adopt tools that reduce administrative burden and improve clarity. The borrower portal allows firms to track funding, compare spend against budgets, submit updates, and request additional capital, reducing friction on both sides and improving the overall relationship.

You've recently launched complex waterfall and scenario modelling functionality. Can you walk us through a use case—how would a fund manager use this feature when evaluating a potential investment or communicating with LPs about projected returns? 

Funders often tell us that building and maintaining waterfall models in spreadsheets is one of the most time-consuming and error-prone parts of the investment process. Fenaro allows complex waterfalls to be configured in seconds, with multi-step logic based on capital return, interest, IRR, MOIC and other calculation types.

A flow view presents the waterfall logic in plain English, and scenario-modelling functionality allows users to test scenarios and explain outcomes to investment committees and LPs. Once a deal is live, waterfalls update automatically as cashflows occur, removing the need for repeated spreadsheet rework and reducing calculation risk.

Looking ahead, where do you see the biggest opportunities for technology to transform how litigation finance firms operate? Are there capabilities that funders are asking for that don't exist yet?

Many funders we speak to see the biggest opportunities in greater standardisation, which would help unlock institutional capital and support a more liquid secondary market. There is still significant friction in how funders, law firms, investors, insurers, and brokers interact, and we’re tackling this one step at a time, focusing on the most pressing pain points first.

We are also frequently asked about AI and machine learning. Our view is that near-term value lies in decision support rather than decision replacement—particularly in reducing the time spent evaluating the majority of cases that are ultimately declined, while equipping underwriters with better information to make faster, more confident decisions. It will likely be some time before the technology is sufficient to take underwriting decisions on behalf of the funder, given the complexity and variation of the underlying legal cases, but things are moving quickly in the AI space so we continue to test and review various models as they evolve.

LFJ Conversation

An LFJ Conversation with Rory Kingan, CEO of Eperoto

By John Freund |

Rory is the CEO of Eperoto, championing the use of decision analysis to improve clarity around litigation and arbitration risk. Originally from New Zealand, he's worked within legal technology for decades, delivering innovative solutions to the top global firms, government, as well as specialist legal boutiques.

Below is our LFJ Conversation with Rory Kingan:

Eperoto’s approach emphasizes using lawyer judgment rather than AI or data-driven models. Why is that distinction important, and how does it build trust among lawyers, funders, and other stakeholders?

At Eperoto, we believe that lawyer judgement is the foundation of credible litigation and arbitration analysis. High-stakes disputes aren’t like consumer tech problems where large-scale historical data exists and small inaccuracies are insignificant. They're unique, context-dependent situations where experience and nuanced legal reasoning are irreplaceable. In most commercial cases, AI simply doesn’t have the training data or contextual nuance to make defensible predictions. Right now it also struggles with the complexity of jurisdictional variation and the role of precedent. No funder or sophisticated client should rely on a generic model to value a multi-million-dollar dispute.

Litigation and arbitration are inherently grey-zones. Outcomes turn not only on points of law, but also on credibility assessments, witness performance, tribunal psychology, and how fact narratives are perceived. These are areas where AI is weak and where judges and experts routinely disagree. Research across behavioural psychology and negotiation theory shows that human reasoning is still essential in these environments. Lawyers will often use an AI tool as a sounding board to explore different ideas and arguments, but ultimately they rely on their own judgement and reasoning to assess how different elements of the case are likely to unfold.

Eperoto is therefore built around a simple principle: Lawyers make the judgement; the platform helps them to structure and quantify it.

This distinction builds trust for three reasons:

  1. It reflects how top practitioners already work. Clients retain leading counsel for their experience, intuition, and ability to form a reasoned opinion, not for machine-generated answers.
  2. It avoids “false precision.” AI-driven confidence levels often create a misleading impression of certainty. Eperoto keeps the human experts in control.
  3. It aligns with stakeholders’ expectations. Funders, insurers, GCs, CFOs and boards want a lawyer’s professional assessment, but expressed in a structured, decision-analytic way. Eperoto strengthens, rather than replaces, that judgment.

The result is a decision-analysis workflow that is transparent, explainable, and fully grounded in legal expertise. Precisely what stakeholders need to trust the numbers behind a funding or settlement decision.

When litigation funders assess potential cases, they often rely on intuition and experience. How does Eperoto help them quantify risk and likely outcomes in a way that strengthens those investment decisions?

Every litigation funder knows that a case is a contingent asset, and valuing that asset depends on understanding the likelihood of outcomes at trial or arbitration. Yet the process used to reach those views is usually unstructured, highly subjective, and difficult to defend when presented to an investment committee or external partner.

Eperoto addresses this by helping lawyers to apply decision-tree analysis. This is a method used for decades in energy, pharma, finance, and indeed litigation. Instead of relying purely on intuition, lawyers:

  1. Map the key uncertainties. What issues drive liability? Likely quantum outcomes? How might damages be reduced? Where do procedural or evidentiary risks sit?
  2. Assign probabilities grounded in legal judgment. No AI predictions: purely the lawyers’ professional view expressed clearly rather than implied.
  3. Estimate costs & cost-shifting, interest, and any enforcement risk.

From this the tool calculates a visual quantitative risk report, showing funders the likely outcomes, expected value, downside scenarios, tail risk, and more.

This sort of analysis:

  • makes an investment case more rigorous,
  • dramatically improves internal and external defensibility, and
  • surfaces insights impossible to see from narrative memos alone.

Funders, insurers, and counsel repeatedly tell us that this level of clarity is transformative. It sharpens decisionmaking, strengthens underwriting discipline, and improves alignment across stakeholders. Over time, a consistent, structured approach creates a more disciplined portfolio and generates a feedback loop that measurably improves investment decisions.

Clearer communication of risk and value benefits all stakeholders. What are the biggest barriers to achieving that clarity in practice?

The biggest barrier is language ambiguity. A typical merits opinion reads something like:

“It's most likely the defendant will be found liable for X, with only an outside chance the court will accept the argument Y. Damages could be as high as Z.”

Terms such as “very likely,” “little chance,” or “low risk” are interpreted wildly differently by different people, even among seasoned professionals. Research consistently shows a huge disparity in how people interpret such terms. For example "unlikely" can be interpreted as meaning anywhere from below 10% to over 40% likely to occur. Your investment decisions shouldn’t be subject to this margin of error just from internal communications.

A second barrier is complexity overload. Lawyers often present lengthy written analyses where different legal issues are explained sequentially:

“X might happen, but if not then Y. In that case Z will determine…”

Decision-makers are left to combine all these uncertainties mentally, plus litigation costs, insurance, interest, enforcement risks, appeal probabilities, and timing assumptions. Even highly experienced professionals can't intuitively do this correctly.

Eperoto solves these issues in three ways:

a) It forces clarity through quantification. “80% likelihood the contract is valid” is unambiguous, whereas “very likely” may be understood as 65% by one person and 95% by another.

b) It combines the factors automatically. No one needs to mentally integrate legal issues, damages pathways, costs, or conditional dependencies.

c) It presents the analysis visually. Charts and diagrams let stakeholders see the shape of the dispute, rather than reading dense text.

Together these remove unnecessary complexity, leaving stakeholders to focus on the true strategic questions rather than being stuck in ambiguous details.

Many lawyers hesitate to provide quantitative estimates because they fear being “wrong.” How do you encourage practitioners to engage with uncertainty in a more structured, transparent way?

This is a common concern, but it fundamentally misunderstands what quantification achieves. Providing estimates numerically doesn't remove uncertainty, it communicates it transparently. The alternative isn't "not being wrong"; it's being vague, which is far worse for the client or investor.

Sophisticated clients, funders, and boards understand that litigation outcomes are uncertain. What they want is clarity, not perfection. Yes, you should still make clear that a percentage estimate is not a promise; it is a transparent reflection of professional judgement, less ambiguous than vague adjectives. But once everyone accepts that, it allows for greater clarity and indeed honesty.

We encourage lawyers to adopt a mindset similar to experts in other industries:

  • Quantification is not about being right; it’s about making uncertainty explicit.
  • A structured model allows you to compare multiple scenarios, e.g. optimistic vs pessimistic or comparing different counsel’s assessments.
  • Visual decision-trees help practitioners and clients see how different issues interact without needing to commit to one “correct” narrative.

Lawyers often find that once they begin using numeric estimates and decision trees, discussions with clients become easier, expectations align more quickly, and advice becomes more defensible. Many even rely on the visual component alone when presenting paths, strategy, and what truly drives the dispute.

How can tools like Eperoto help bridge the gap between legal reasoning and financial analysis, bringing dispute resolution closer to the standards of decision-making seen in other business contexts?

Business-critical decisions in energy, pharmaceuticals, and corporate strategy have used quantitative decision analysis for decades. A pharmaceutical company wouldn't greenlight a $50M clinical trial based on phrases like "good chance of success" or "strong scientific rationale". They'd model probabilities, conditional outcomes, and expected value. Yet litigation decisions involving similar amounts often rely on purely that kind of qualitative language.

The gap isn't from a lack of judgment. It's that legal reasoning and financial decision-making speak different languages. Lawyers think in terms of arguments, precedents, and likelihoods. Funders think in terms of expected values, downside risk, and portfolio returns. Eperoto translates between these worlds.

Here's a concrete example: A law firm presents a case with "strong liability prospects" and "substantial damages potential." The investment committee sees an attractive headline but struggles to assess the risk. Using Eperoto, counsel maps the decision tree and reveals that while liability looks good at 70%, the real value driver is a secondary issue: whether a contractual damages cap applies. If the cap doesn't apply, a 40% likelihood, it would triple the recovery. The investment thesis becomes clear: this isn't a simple 70% bet on liability; it's a case where the upside scenario creates most of the expected value. That fundamentally changes how you price the funding, structure the terms, and think about settlement strategy.

This kind of insight can easily be buried in a narrative memo but obvious when properly structured.

Specifically, Eperoto enables:

1. A common analytical framework - When counsel says "we have a strong case but quantum is uncertain," Eperoto forces that assessment into a structure funders recognize: probability-weighted scenarios with costs, timing, and enforcement risk factored in. This isn't dumbing down legal analysis; it's making it actionable.

2. Proper treatment of uncertainty - In portfolio management, no one expects point estimates: they expect distributions, scenarios, and sensitivity analysis. Eperoto brings that same rigor to litigation assets, showing not just expected value but the shape of the risk distribution. What's the 10th percentile outcome? How sensitive is the return to different assumptions? This is standard practice in all other asset classes.

3. Defensible investment decisions - Just as a PE firm documents the assumptions behind an acquisition, funding decisions should have the same analytical discipline. Eperoto creates an audit trail showing why a deal was approved or a settlement accepted, based on structured analysis rather than gut feel. Critical for investment committee scrutiny and stakeholder confidence.

4. Portfolio-level insights over time - Applying decision analysis consistently across a portfolio creates compounding benefits. Funders develop better calibration of their judgment, identify patterns of cases that outperform or underperform expectations, and build institutional knowledge about what drives value. Over time, this disciplined approach strengthens underwriting quality and improves portfolio returns. Just like how data-driven decision-making in other industries creates feedback loops that enhance performance.

The result is that litigation funding can be managed with the same analytical rigor as any other alternative asset class. Lawyers retain their essential role as expert judgment-makers, but that judgment gets expressed in a framework that investment committees can understand, stress-test, and defend to stakeholders.