Smith And Amazon Explore Current and Future Paths in Collaborative Research
Leaders from Amazon Research Initiatives and AWS visited UMD’s Smith School on Nov. 10, 2025, to explore research collaborations. Faculty shared innovative projects in AI, logistics, sustainability, and digital marketing, strengthening Smith’s partnership with Amazon and highlighting opportunities for future funding.
Biodiversity Entrepreneurship
We study an emerging class of start-up organizations focused on biodiversity conservation and the challenges they face in financing these ventures. Using a novel machine learning method, we identify 630 biodiversity-linked start-ups in PitchBook and compare their financing dynamics to other ventures. Biodiversity start-ups raise less capital but attract a broader coalition of investors, including not only venture capitalists (“value investors”) but also mission-aligned impact funds and public institutions (“values investors”).
In-person Site Visits Matter, Even In the Age of AI
Smith School Associate Professor Sean Cao’s research shows investor site visits do more than gather information. On-site interactions also monitor managers, improving efficiency—an essential human role that artificial intelligence, he argues, cannot replace.
Analytics for Finance and Accounting: Data Structures and Applied AI
Analytics for Finance and Accounting: Data Structures and Applied AI bridges the gap between technical data science education and domain-specific applications in accounting and finance. Designed for students and instructors seeking practical exposure to AI-driven financial analytics, the book prioritizes understanding real-world business data—structured and unstructured—before introducing machine learning techniques.
From Man vs. Machine to Man + Machine: The Art and AI of Stock Analyses
An AI analyst trained to digest corporate disclosures, industry trends, and macroeconomic indicators surpasses most analysts in stock return predictions. Nevertheless, humans win “Man vs. Machine” when institutional knowledge is crucial, e.g., involving intangible assets and financial distress. AI wins when information is transparent but voluminous. Humans provide significant incremental value in “Man + Machine”, which also substantially reduces extreme errors. Analysts catch up with machines after “alternative data” become available if their employers build AI capabilities.
Blockchain Technology Could Bring Benefits to the Auditing Industry
Sean Cao, director of the Smith AI Initiative, has researched blockchain’s role in financial auditing for six years. His study, published in Management Science (2024), explores how permissioned blockchains enhance reporting integrity, reduce costs by 70%, and improve data privacy.
How to Talk When a Machine Is Listening: Corporate Disclosure in the Age of AI
Growing AI readership (proxied for by machine downloads and ownership by AI-equipped investors) motivates firms to prepare filings friendlier to machine processing and to mitigate linguistic tones that are unfavorably perceived by algorithms. Loughran and McDonald (2011) and BERT available since 2018 serve as event studies supporting attribution of the decrease in the measured negative sentiment to increased machine readership. This relationship is stronger among firms with higher benefits to (e.g., external financing needs) or lower cost (e.g., litigation risk) of sentiment management.
Distributed Ledgers and Secure Multi-Party Computation for Financial Reporting and Auditing
To understand the disruption and implications of distributed ledger technologies for financial reporting and auditing, we analyze firm misreporting, auditor monitoring and competition, and regulatory policy in a unified model. A federated blockchain for financial reporting and auditing can improve verification efficiency not only for transactions in private databases but also for cross-chain verifications through privacy-preserving computation protocols.
Applied AI for finance and accounting: Alternative data and opportunities
Big data and artificial intelligence (AI) have transformed the finance industry by altering the way data and information are generated, processed, and incorporated into decision-making processes. Data and information have emerged as a new class of assets, facilitating efficient contracting and risk-sharing among corporate stakeholders. Researchers have also increasingly embraced machine learning and AI analytics tools, which enable them to exploit empirical evidence to an extent that far surpasses traditional methodologies.
Site Visits and Corporate Investment Efficiency
Site visits allow visitors to physically inspect productive resources and interact with on-site employees and executives face to face. We posit that, by allowing visitors to acquire investment-related information and monitor the management team, site visits offer disciplinary benefits for corporate investments. Using mandatory disclosures of site visits in China, we find that corporate investments become more responsive to growth opportunities as the intensity of site visits increases, consistent with the notion that site visits yield disciplinary benefits.