Supercharging Mass Claims: Leveraging AI and LLMs in UK Group Litigation

From Research to Resolution: A New Paradigm for Claimant Firms

Introduction

As the UK's collective redress regime continues to evolve, law firms face novel challenges at every turn. Building and managing mass claims in this environment demands not just legal acumen, but also exceptional efficiency and strategic insight. The traditional, largely manual processes of research, data collection, fact preparation, and claim management are simply not sustainable when dealing with thousands, or even millions, of claimants.

The sheer volume of data involved can be overwhelming. Identifying eligible claimants, establishing commonality, assessing economic impact and liability, building a robust claim inventory matrix, and processing claims, while identifying fraud, are all incredibly time-consuming and resource-intensive tasks. In this context, speed and accuracy are not just desirable; they are essential for securing funding, attracting claimants, and achieving a successful outcome.

This is where the transformative power of Artificial Intelligence (AI), and specifically Large Language Models (LLMs), comes into play. LLMs, with their ability to understand, analyse, and generate human language at scale, offer a significant advantage for law firms. This isn't about replacing legal expertise; it's about providing the tools to significantly enhance every stage of the mass claims process, from initial research to final resolution. It's about moving from laborious workflows to data-driven, AI-assisted efficiency. It's about gaining a crucial competitive edge over those who are late to adopting AI tools and their myriad benefits. 

Part 1: The Bottleneck – Overcoming Traditional Limitations

The early stages of a mass claim, and indeed the entire lifecycle, present significant operational hurdles. Law firms typically grapple with:

• Massive Data Ingestion and Analysis: Gathering and analysing relevant documents – contracts, emails, financial statements, regulatory reports – is a monumental undertaking. Manual review is slow, costly, and prone to error.
• Claimant Identification and Recruitment: Finding, vetting, and onboarding eligible claimants is a major logistical challenge. Traditional methods can be inefficient, and identifying claimants with multiple law firms presents coordination issues.
• Establishing Commonality and Building Cohorts: Demonstrating that claimants share a common harm and legal standing is crucial for securing funding and achieving class certification.
• Economic Impact and Liability Assessment: Quantifying damages and establishing liability often involves complex economic modeling and analysis of vast datasets.
• Claim Inventory Matrixing: Organising and categorising all claims, including their characteristics and damages, is essential for settlement or trial.
• Cost and Time Constraints: The upfront costs and time investment are often prohibitive, particularly for smaller firms.
• Fraud Detection and Prevention: Identifying fraudulent claims within a large pool is critical, yet resource-intensive.

Part 2: AI and LLMs – Assisting at Every Stage

AI, and specifically LLMs, offer tools to overcome these traditional limitations, significantly improving the mass claims process:

• AI-Powered Research
  • Legal Research: LLMs rapidly analyse legal databases, case law, regulatory guidance, contracts, license agreements, and other legal documents to identify relevant precedents, statutes, and potential legal arguments, accelerating the initial research phase.
  • Fact Finding: LLMs can sift through news articles, social media, and other public information to uncover relevant facts helping to build a stronger case or support legal strategies.
• Streamlined Data Collection and Processing
  • Data Extraction: LLMs can automatically extract key information from unstructured documents (names, dates, amounts, clauses), as well as audio files like call recordings and transcriptions, reducing manual data entry and improving efficiency across various data formats.
  • Data Classification and Organisation: AI categorises and organises documents, making it easier to find relevant information.
  • Data Cleansing and Validation: AI identifies and flags potential errors in data, improving accuracy.
• Enhanced Claimant Identification and Book Building
  • Claimant Profiling: LLMs analyse claimant information to identify common characteristics and assist in grouping claimants into coherent cohorts.
  • Claim Viability Assessment: Machine Learning models can assess the likelihood of success for individual claims, helping prioritise resources.
  • Dual Representation Identification and Resolution Assistance: AI can analyse claimant databases and communications to identify potential instances of duplicate legal representation. By flagging these instances early, AI facilitates prompt communication and coordination between law firms and claimants to resolve the issue efficiently and ethically.
• AI-Assisted Analysis for Economic Impact and Liability
  • Supporting Damage Model Development: AI can efficiently process and analyse large volumes of data, which can be useful in developing complex economic models to quantify damages.
  • Liability Assessment: LLMs can analyse legal documents, witness statements, and other evidence to assist in identifying and organising information relevant to liability arguments. By quickly processing large amounts of complex information, AI can help legal teams to identify key evidence and potential lines of argument. 
  • AI-Assisted Causation Exploration: While establishing causation remains a complex legal determination, AI can assist in exploring potential causal links between events and alleged losses. AI algorithms can analyse data to identify correlations and patterns that may contribute to a better understanding of causation issues.       
• Fact Development and Preparation
  • Information Extraction and Summarisation: LLMs rapidly identify and summarise key facts and events from various sources, saving significant time.
  • Timeline Creation: LLMs analyse documents and communications to assist in constructing chronological timelines.
  • Drafting Assistance: LLMs can assist in drafting factual sections of legal documents.
  • Evidence Organisation: LLMs can categorise and link pieces of evidence, creating a searchable database.
• Assisted Claim Inventory Matrixing
  • Data Extraction and Population: LLMs assist with extracting relevant data from claim forms and documentation, automatically populating the claim inventory matrix.
  • Categorisation and Classification: AI can assist in categorising and classifying claims based on various criteria, such as the type of injury, the severity of damages, the legal basis for the claim, the applicable limitation period, and the jurisdiction.
  • Damage Calculation Assistance: LLMs can help calculate damages based on pre-defined formulas and extracted data.
• Fraud Detection and Prevention
  • Anomaly Detection: AI algorithms identify unusual patterns in data that may indicate fraudulent activity.
  • Predictive Modeling: Machine learning models can be used to assess the risk of fraud for each claim based on historical data and identified patterns.
  • Network Analysis: AI can help identify and analyse connections between claimants, uncovering patterns that may indicate fraudulent activity.

Part 3: How Ankura Can Help

Ankura is at the forefront of applying AI, and specifically LLM capabilities, to the challenges of mass claims litigation. We understand that technology alone isn't enough; it requires a combination of deep legal domain expertise and cutting-edge AI solutions. Our AnkuraAI platform and services are designed to empower law firms at every stage:

• AnkuraAI Platform: This proprietary platform provides a secure and scalable environment for managing and analysing massive datasets. It incorporates advanced Natural Language Processing and Machine Learning capabilities, including state-of-the-art LLMs, specifically tailored for legal investigations and group litigation.
• AI-Powered Document Review and Analysis: Our platform accelerates document review, automatically identifying key clauses, extracting relevant information, summarising content, and flagging potential issues.
• Intelligent Data Extraction: AnkuraAI leverages advanced algorithms and LLMs to efficiently extract structured data from unstructured sources, enhancing data accuracy and accessability.
• Advanced Analytics and Data Visualisation: AnkuraAI transforms raw data into actionable insights, including robust claim inventory matrices.
• Custom AI Solutions: Our team of technologists and legal experts can configure and deploy tailored AI solutions, including selecting, training, and integrating the most appropriate LLMs and machine learning techniques for your specific needs.
• Data Security and Compliance: Ankura prioritises data security and compliance. Our AnkuraAI platform adheres to stringent data protection protocols, including GDPR, while employing robust encryption, access controls, and data segregation to safeguard sensitive information.

Ankura's AI solutions empowers law firms to work smarter, faster, and more effectively, achieving better outcomes for their clients. Contact us to learn how AnkuraAI can transform your approach to group litigation.

Conclusion

The future of mass claims in the UK is being shaped by AI and LLMs. By embracing these technologies, law firms can unlock new levels of efficiency and accuracy. However, it's crucial to carefully vet AI vendors and their capabilities. The rapid rise of AI has led to a proliferation of providers, many with limited experience in the complexities of integration and the specific requirements within the mass claims domain. Ankura stands apart with its deep expertise in both AI and the legal domain, offering proven solutions and a commitment to responsible and effective AI implementation.

This article was first published with ThoughtLeaders4 Disputes Magazine.

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^{© Copyright 2025. The views expressed herein are those of the author(s) and not necessarily the views of Ankura Consulting Group, LLC., its management, its subsidiaries, its affiliates, or its other professionals. Ankura is not a law firm and cannot provide legal advice.}