Report | February 25, 2026
Trends in AI-Related Securities Class Actions Through 2025
Bilal Shah, Chris Riper and Lauren Nasta examine the accelerating wave of securities litigation tied to artificial intelligence.
Dr. Du is an economist with expertise in labor economics, computational economics, public finance, and macroeconomics.
San Diego
Dr. Du is an economist with expertise in labor economics, computational economics, public finance, and macroeconomics.
Dr. Du’s research focuses on developing rich models of unemployment and income risk using advanced computational methods. In one paper, conditionally accepted at Quantitative Economics, he builds a general equilibrium model of consumption and unemployment risk to demonstrate that unemployment benefit extensions generate more stimulus and greater welfare gains compared to stimulus checks and tax cuts.
In related work, published as a Bank of Canada Staff Working Paper, Dr. Du employs machine learning methods to impute households’ perceptions of their risk of unemployment and to generate real-time machine forecasts of the actual risk of unemployment. His findings reveal a systematic underreaction: households tend to adjust their perceptions sluggishly in response to changes in their true unemployment risk.
Before joining Secretariat, Dr. Du worked as a PhD intern at the Bank of England and as a developer for an economic modeling Python package. He also served as a teaching assistant and section instructor at Johns Hopkins University.
Trends in AI-Related Securities Class Actions Through 2025
Bilal Shah, Chris Riper and Lauren Nasta examine the accelerating wave of securities litigation tied to artificial intelligence.
Football’s Financial Regulation—Towards Convergence?
This article examines the current financial regulation frameworks, trends in compliance and recent UEFA settlements, the proposed PSR reforms, and the associated financial and legal risks for clubs.
From Discovery to Intelligence: The Next Phase of Digital Investigations
The article outlines the shift from reactive, volume-led processes to analytics-driven, intelligence-focused approaches. Early insights from digital evidence increasingly shapes legal strategy and case outcomes. As analytics and AI adoption increases, expert judgment, transparency, and defensibility have become critical as courts and regulators apply increasing scrutiny to investigative methods and proportionality.