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Exploring AI Data Extraction Technology for Litigation Funding: Benefits and Potential Pitfalls

Miranda Hartley
August 14, 2023

Litigation funding relies on fast and informed decision-making. In 2018, a leading litigation firm funder accepted just 87 out of 1470 applications. The process of identifying the cases worth investment is a process that relies on human acuity - but can be expedited via automated AI.

What is AI-based data extraction for litigation funding?

AI solutions for data extraction - or intelligent data extraction - is a widely deployed document processing technology. AI data extraction involves two distinct abilities: the technology can understand the semantic meanings of words and learn from its mistakes. AI’s superior capacity for comprehension comes from its deployment of natural language processing (NLP).

Older and less sophisticated data extraction tools struggle to discriminate between word meanings. For example, these technologies can confuse words with the same spelling but different meanings such as ‘settlement’ (which has a different meaning in financial and legal contexts). Correcting the captured data constitutes a waste in employee time.

AI’s ability to understand language means it can connect and correctly contextualise the meaning of information. Consequently, the technology can extract data from complex tables, noisy (or poor-quality) scans and documents of any length. AI can also extract from unstructured data, unlocking insights from long documents. For dense documentation such as adjuster notes, AI’s intelligent processing abilities can make life significantly easier.

In sum, integrating AI technology into the funding process ensures that specific, relevant data is instantly extracted from PDFs of the funding application documents.

Example use case

Litigation funding firm A receives approximately 500 applications for funding per annum. These applications include bank statements and financial statements (showing the applicant's revenues, expenses, and net income in their business or personal finances).

These documents require batch extraction from the PDFs supplied by the customers.

Firm A requires its team of analysts to extract and cross-validate the data manually. The process takes approximately half an hour per document (longer for lengthy financial statements).

Over a year, Firm A loses a minimum of 1000 hours, or 125 days on data extraction. The lost hours - plus missed opportunities from clients - cost the firm hundreds of thousands of dollars.

As the litigation funding market is estimated to be worth around $13.5 billion in the US alone, examples like these demonstrate how firms are limiting their growth. Even deploying a simple AI-powered workflow solution can deliver quick, accurate results, as our client LitFin discovered. The infographic below visualises their transformed workflow:

Benefits of using financial data extraction software in litigation funding

  • Significant cost savings. Data capture software is priced per page, starting from as little as £0.02. Compared to the cost of traditional data extraction services or ineffective technology, the cost of AI data extraction software is negligible.
  • Reduced time-to-decision. Automated data extraction from PDFs allows instantaneous decision-making. Instantaneous decision-making allows funders to sift through applications, identifying the high-value propositions and enabling a competitive advantage.
  • Greater productivity. Expert legal and financial analysts can focus on advanced decision-making and analysis rather than the mundanities of financial data extraction. Investment managers have greater insights into trends and patterns in portfolio management. Risk managers benefit from valuable insights into the risk profiles of different cases based on historical data.

Other uses of AI for litigation funding

There are other ways that AI may be able to assist the litigation funding process. Using current and historical data, AI can also generate predictive analytics, anticipating the outcome of a case with superior accuracy. Add in AI’s ability to read legal documents and contribute to real-time case monitoring, and it’s clear that AI is poised to make a massive impact on the litigation funding landscape.

However, it is worth noting that many of these analytical technologies are still in development and may require a lengthy training and configuration process. It is also currently unclear how issues of transparency and bias may affect the use of complex generative and predictive technologies in litigation finance.

Potential drawbacks of data extraction using AI

  • Confidentiality and transparency. The laws around AI are constantly evolving, so if in doubt, it’s worth consulting the relevant intellectual property protection laws.
  • Training the software. For more complex litigation documents (say, credit reports or tax returns compared to invoices or bank statements), an AI model will require training on their unique data fields. The training process involves submitting a few representative documents and allowing up to two days for the AI data extraction model to process them.


Overall, AI-powered data extraction is the low-hanging fruit of litigation funding. Though advanced technologies are rapidly surging forward with complex applications, many are highly unpredictable and may experience bias. Intelligent data extraction software is fast, well-developed and highly accessible document management technology with high-value applications in the litigation finance industry.

Interested in exploring our litigation funding solution? Book a demo to speak to one of our experts or email us at

For more information, check out our other resources:

Our litigation funding solution

How to extract financial data from PDFs

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