Boyang Wang
PhD Candidate in Accounting · Essex Business School, University of Essex
📍 Colchester, Essex, UK
PhD Candidate in Accounting · Essex Business School, University of Essex
📍 Colchester, Essex, UK
I am a PhD Candidate in Accounting at Essex Business School, University of Essex, with a strong interest in the applications of Artificial Intelligence (AI) and Machine Learning (ML) in accounting and financial analysis. My research investigates how AI is transforming corporate disclosure practices, most notably through the concept of Algorithmic Disclosure Management, which explores whether corporate managers strategically adapt language to influence algorithmic readers such as LLMs. I also study AI-driven changes in financial reporting quality and NLP-based textual analysis of annual reports. I hold a First Class Honours BSc in Accounting and Finance from the University of Essex.
In preparation
This paper investigates whether corporate managers strategically adapt disclosure language to influence algorithmic readers, particularly Large Language Models (LLMs) such as ChatGPT and DeepSeek. I introduce the concept of Algorithmic Disclosure Management and construct a novel LLM-Targeting Score that aggregates three measurable dimensions: structural prompt-like features, sentiment optimisation features, and embedding alignment with LLM-preferred prototypes.
Under preparation for submission, 2026
This paper examines how the widespread adoption of AI has transformed the textual characteristics of annual reports produced by Chinese listed companies. Using large-scale textual analysis of corporate disclosures, the study investigates structural shifts across four key dimensions: readability, similarity (cross-firm boilerplate homogeneity), forward-looking content, and tone. Findings contribute to the growing literature on AI-driven changes in corporate communication within an emerging-market context.
MRes Dissertation · Essex Business School, University of Essex · Supervised by Dr. Ricardo Malagueno De Santana & Dr. Hao Lan
This dissertation examines how regional religiosity and political ideology jointly shape firm-level ESG performance in the United States, using a large-scale panel dataset of listed firms from 2012 to 2022. Grounded in institutional theory, the study finds that both higher religiosity and greater political conservatism independently suppress ESG scores, and that their interaction effects vary categorically across liberal and conservative states.
University of Essex, Colchester, UK · 18 June 2026
University of Essex · 12 May 2026
Presentation: How do religious background and political affiliation affect firms' ESG performance? A quantitative panel study on the case of the United States.
Essex Business School, University of Essex, Colchester, UK
University of Essex, Colchester, UK
Guangdong University of Foreign Studies, Guangzhou, China