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.
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.
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:
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.
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 hello@evolution.ai
For more information, check out our other resources:
Our litigation funding solution
How to extract financial data from PDFs
