UK-CLAD is the digital hub of the first comprehensive empirical study of private competition law enforcement and access to justice before the UK Competition Appeal Tribunal (CAT). The project examines the complete population of damages litigation before the Tribunal since its inception: individual claims under section 47A of the Competition Act 1998 and collective proceedings under section 47B. Every case is coded across a wide set of variables — parties, claim and claimant type, legal basis, procedural trajectory, duration, costs, and outcomes — and linked to corporate registry data identifying who actually litigates.
Aims
Competition law promises that any person harmed by anti-competitive conduct can obtain full compensation. Whether that promise is kept cannot be read from case counts alone. This project systematically analyses more than twenty years of judicial records to answer a deceptively simple question: does the current framework effectively serve those harmed by cartels and abuses of dominance? By combining legal analysis with data science and empirical methods, it moves the debate beyond doctrine and anecdote to a documented evidence base.
Our database tracks the structural, procedural, and financial realities of the CAT from 2004-2025. By coding unstructured judicial decisions, cost awards, and corporate registries, the study maps the life cycle of 454 cases.
The study is organised around five linked datasets, each of which will be released openly together with its codebook.
Limitations: CAT proceedings only (High Court claims are out of scope); most cases settle confidentially, so the data captures litigated outcomes rather than all disputes. See the codebook for detail.
The study is designed as a full-population analysis rather than a sample: every damages action before the Tribunal since its inception is included, coded case by case from the public register against a published codebook, so that the findings describe the regime as a whole rather than a selection of prominent disputes. Structured fields such as parties, dates, and procedural milestones are combined with variables coded from unstructured judicial text — claim and claimant type, legal basis — and linked to external corporate and costs data, producing an integrated dataset that can be interrogated, replicated, and extended by others. This quantitative foundation drives the project’s Cost Estimator.
Estimates are indicative, built from published rulings, official guidance, and professional heuristics.
The research codes all available final judgments on the merits and all published costs rulings, mapping the relationship between what parties claim — in damages, interest, and costs — and what they are ultimately awarded. Because a small number of very large collective claims dominate the aggregate figures, recovery measures are reported in multiple forms, including with and without outlier proceedings. Detailed results are presented in the accompanying paper and on the Datasets page.
Litigants are geocoded from registered addresses, mapping where claimants and defendants are based across the UK and beyond — a spatial dimension of access to justice that written judgments never reveal.
Use the checkboxes to filter by entity, region, and industry. Hover over a circle to see a breakdown for that area.
Lecturer in Law, University of Aberdeen, Scotland
Dr. Lombardi's research focuses on the intersection of competition law and empirical legal studies.
This project bridges the gap between theoretical competition law frameworks and the financial realities of litigation, providing policymakers, practitioners, and scholars with open-access, data-driven insights into the functioning of the UK's primary competition court.
This project was made possible by an Agile grant from the University of Aberdeen (Project ID 12073249). The website was designed and built by the Aberdeen Software Factory.
Research assistance on data collection and coding was provided by Boglarka Vincze and Khan Phoung Le. The study draws on public records published by the Competition Appeal Tribunal and on company information from UK Companies House.
The views expressed here are those of the author and do not represent the University of Aberdeen, the Competition Appeal Tribunal, or any other body. Any errors are the author's own - corrections are welcome via the Contact page.
