On April 30, 2026, the Department of Justice’s Civil Division launched the Fraud Oversight through Careful Use of Statistics, or “FOCUS,” initiative to strengthen its relationship with “data miners” who file qui tam actions based on publicly available data rather than traditional insider information. For sophisticated data miners, FOCUS is both an opportunity and a warning: DOJ is inviting analytically rigorous relators into a closer working relationship, but it is also making clear that data miners will be held to a high standard.
This initiative makes the relator’s selection of counsel imperative in data-based cases. The government has made clear that data miners “should look to partner with others who can aid their understanding of program eligibility requirements and regulatory frameworks,” and they must understand particular legal frameworks.
The FOCUS initiative arrives at a moment of breakneck growth in False Claims Act qui tam complaints: 980 in FY 2024, nearly 1,300 in FY 2025, and already over 780 in FY 2026. According to DOJ, much of this growth has been driven by data miners, who have filed more than 45% of all qui tam complaints since 2024.
A mismatch between volume and perceived quality of cases has led DOJ to introduce the FOCUS initiative. The initiative has two important features for potential data mining whistleblowers.
First, DOJ has created a centralized point of contact for data mining whistleblowers to demonstrate their claims and the underlying methodology. This will allow DOJ to evaluate data mining qui tam suits using a common methodology and more quickly identify sophisticated data miners with promising claims. It will also offer benefits to repeat players, both data miners and their counsel, who can establish credibility with the Department.
Second, DOJ has offered guidance on what separates the wheat from the chaff in presenting a compelling data mining qui tam claim:
- providing “valuable leads through high-quality, reliable, and predictive data analyses and signals and a thorough understanding of the relevant legal obligations”;
- understanding the “heightened pleading standard of Rule 9(b) of the Federal Rules of Civil Procedure,” including “the obligation to state with particularity the circumstances constituting fraud” and the “program eligibility requirements and relevant regulatory frameworks and articulate them in their complaints”; and
- assessing potential alternative explanations for the observed conduct and articulating how the data, in combination with other available evidence, indicates both falsity and knowledge of wrongdoing (i.e., scienter).
The FOCUS initiative reinforces the importance of partnership between sophisticated data miners and experienced FCA relators’ counsel. Data miners must be able to identify statistical anomalies, rule out alternative exculpatory explanations, and concretely identify the nature of the fraud. In selecting counsel, data miners should look for firms with experience and facility in complex and data-driven cases, legal acumen, and the resources and skill to develop the evidence beyond the data and to turn a data-driven investigation to a full-fledged record for a jury.
About Lieff Cabraser’s Qui Tam Practice and Background in Complex Litigation
Lieff Cabraser represents whistleblowers who uncover fraud on the government in a wide range of Qui Tam / False Claims Act cases, including Medicare and healthcare fraud, defense contractor fraud, securities and financial fraud, insurance fraud, and many other false claims.
Lieff Cabraser’s successes in False Claims Act cases include a $78.5 million settlement in the University of Phoenix litigation, the largest settlement ever in a qui tam case involving the U.S. Department of Education, and the successful representation of relators in a lawsuit against Gold Coast Health Plan for knowingly misusing funds it received from the federal government and California State Government, resulting in a $70.1 million settlement.
Lieff Cabraser also brings unparalleled experience in the litigation and trial of large and complex cases. These typically involve expert battles over statistics and data inferences, disputed issues of causation, sophisticated damage modeling, and generally—whether mass tort, antitrust, discrimination, or other—the imperative to tell stories with data. Such cases include the recent JUUL and Opioids trials which ended in signal victories for plaintiffs (JUUL Labs, Inc. Marketing, Sales Practices & Products Liability Litigation, Case No. 19-md-02913-WHO, and City and County of San Francisco, et al., v. Purdue Pharma L.P., et al., Case No. 3:18-cv-07591-CRB).
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