How Algorithms Can Revolutionize the Legal Market

Philipp Popov launched the first litigation funding model in Russia. Under his leadership, scoring technologies changed the approach to assessing legal risks, and startups Konkur and Zakrytie became examples of how digitalization can transform conservative markets—and were sold for nearly $80 million. Philipp discussed how scoring saves companies money and how fintech solutions are making the litigation funding market more transparent and efficient.

Philipp, you have over 20 years of experience, including working in the innovative financial law segment. What companies did you work for, and what were your responsibilities?

I was involved in the development and implementation of my own software solutions. Our task was to build Legal Finance. My team and I created innovative models that connect clients with investors and expand access to justice in Russia. Since 2010, I have managed Russian Credit LLC, and we became pioneers in the field of litigation funding. Also under my leadership, scoring software was developed, which changed the approach to risk assessment in this industry.

How are these two directions connected, and what makes your product unique?

The key problem in litigation funding has always been assessing the prospects of a case. Decisions were made manually, relied on expert experience, and took weeks. We saw that the market couldn't scale without technology and created scoring software that analyzes dozens of factors: case law, the defendant's financial stability, and reputational and procedural risks. The system translates subjective data into an objective forecast: whether or not to fund the process.

Thus, scoring became the core of the entire litigation funding model. He gave investors a tool for making quick and transparent decisions and plaintiffs access to capital they didn't have before. The uniqueness of our product lies in the fact that we were the first to create a technological trust infrastructure for an industry where everything was previously based solely on the intuition of lawyers.

Simultaneously, you were developing two other companies as a founder; the startups KONKUR and ZAKRYTIE were established in 2019. What did this business specialize in?

We initially built both companies as fintech solutions with a strong analytical platform. Konkur developed scoring software to assess borrowers in the litigation finance segment. We created a system that took into account dozens of factors, from the plaintiff's financial standing and the sustainability of their business to their litigation history and reputational risks. This allowed investors and banks to quickly and objectively decide whether to finance a lawsuit. For the plaintiffs, this meant access to capital where it hadn't been available before, and for investors, it meant a reduction in the risk of unsuccessful investments.

Zakrytie was aimed at a different segment—companies looking to exit the business. We developed software that essentially acted as a scoring tool for distressed assets: it assessed liabilities, obligations, and litigation risks so that the deal to close or sell the company could be properly structured.

You sold both of those companies for almost $80 million. What attracted buyers to these startups?

What attracted the buyer to Konkur was precisely the fact that we were the first to be able to structure and automate the litigation funding market, making it more transparent and efficient. The Zakrytie solution interested buyers because it saved time and money, and most importantly, it made processes predictable.

So, you've enriched familiar routine legal processes with digitalization. How did you come up with the idea to dedicate your work to modernizing outdated industries, and why did you choose this direction in business?

When we started, the legal market was truly extremely conservative: deals were financed using old schemes, and risk assessment was done manually and took weeks. We have created a product that allows for the automation of litigation funding: an algorithm assesses the probability of a case's outcome, calculates the optimal investment size, and insures the risks for the client. Essentially, we brought to the legal market what has long been working in fintech: fast scoring, transparent terms, and an understandable product.

How does automated scoring software work? What is its essence, and why is it a breakthrough solution?

The underlying idea is to systematize fragmented information. The software collects data from dozens of sources—court records, financial documents, government databases, and behavioral indicators—and automatically matches them using algorithms. The point is that the decision no longer depends on the human factor: the system provides a transparent and repeatable result. The breakthrough here is in scale—a check that used to take weeks now takes minutes.

What business problems does it solve? How does it simplify and modernize business operations, and how does it impact its profitability?

In litigation funding, assessing the prospects of a case is the biggest bottleneck. Mistakes here are too costly: the company risks investing millions and not getting them back. Our software allows you to quickly and objectively answer the main question: whether or not to fund the process. This reduces the risk of bad investments, speeds up decision-making, and allows for the financing of more deals without increasing the number of analysts. For clients, this means access to capital where it wasn't available before, and for businesses, it means predictable returns and portfolio growth.

How do you explain the value of scoring to clients if they are skeptical of algorithms?

I always emphasize: an algorithm doesn't replace an expert; it enhances them. A lawyer or analyst has experience and intuition, but they can't process thousands of documents and court cases in a day. The system does this in minutes and shows probabilities, but the final decision remains with the person. In practice, even the most skeptical clients are convinced when they see that the speed increases significantly and the proportion of unsuccessful investments decreases.

What data is considered the most "valuable" for scoring accuracy?

In litigation finance, three data blocks are particularly valuable:

1. Legal: court decisions in similar cases.
2. Financial: the defendant's solvency and their ability to actually pay compensation.
3. Behavioral: dynamics of previous processes, lawyers' working style, review timelines.

The combination of these factors allows for a significantly more accurate prediction of the case outcome compared to manual analysis.

Are there situations where a human decision is more reliable than an algorithm?

Yes. Algorithms are trained on past data and can fail if the market changes abruptly. In such cases, a person is able to compare different facts, consider the context, apply critical thinking, and rely on experience. Thanks to this, his decision is often more reliable.

How do you assess your role as CEO and founder of the companies? In your opinion, what is the key mission of an entrepreneur?

For me, the role of a founder has always gone beyond creating technology or a business model. The true mission of an entrepreneur is not only to introduce innovations but also to create jobs and provide opportunities for people to realize their potential. When we launched projects in the areas of litigation funding or proptech, I always saw the task more broadly: to build an ecosystem where skilled jobs are created, where specialists can grow and develop alongside the company. This is what creates long-term value for both the market and society as a whole.

What are your plans and future career ambitions, and in which area do you want to further develop your expertise?

My goal is to focus on the development of the creator economy and social marketplaces, where I see tremendous potential for transformation. Today, traditional social media only offer monetization opportunities to a narrow group of influencers, while the next stage in the industry's development is the democratization of the creator economy. I am confident that every person can turn their skills, passions, and experience into a source of income.

My ambition is to build solutions that make this process as simple, safe, and scalable as possible. I see huge potential in the creator market. Speaking about the creator market, it's currently accessible mainly to large influencers who sell advertising. But there's a huge field of opportunities for those with a small audience but skills that can be monetized. Everyone has skills; it's just difficult to sell them in the current model. That's what needs to be changed.