In today’s hyperconnected world, where instant translation tools make information accessible across borders, a widely held belief persists: all investors, regardless of their origin, have equal access to corporate data. However, groundbreaking research conducted by Professor Forester Wong Yu-ting of the City University of Hong Kong challenges this notion, revealing that multinational companies strategically design communication to favor local stakeholders, thereby creating a “home court advantage” that systematically disadvantages foreign investors.
Professor Wong’s research introduces a pioneering concept termed “differential communication,” which uncovers how companies craft bilingual disclosures with intentional disparities. This subtle yet impactful stratagem is designed to provide local investors with richer, more insightful information than their foreign counterparts. The study, recently published in The Accounting Review, employs innovative machine learning techniques to expose these crafted informational inequalities, fundamentally altering our understanding of investor relations in multinational markets.
The catalyst for this research was a seemingly mundane encounter: Professor Wong observed notable translation discrepancies in the Chinese and English versions of a retail store’s return policy. Intrigued by this inconsistency, he hypothesized that similar tactics could be employed in corporate disclosures, potentially skewing information availability. This insight spurred a rigorous investigation into how companies translate— and more importantly, selectively transform—their financial narratives across languages.
Historically, detecting such strategic disparities was elusive. Companies’ biased communication often transpired in private, off-the-record conversations or internal emails, places inaccessible to outsiders and regulators alike. To overcome this opacity, Professor Wong and his team adopted an innovative approach—directly comparing the Chinese and English versions of the same annual reports. This direct comparison sidesteps the conventional practice of translating documents into a third “pivot” language, which typically introduces noise and reduces analytical precision.
The team developed a state-of-the-art joint-language machine learning model complemented by an AI methodology that can differentiate substantive translation gaps from trivial stylistic variances. By filtering out superficial differences, this technology isolates discrepancies with material significance to firm performance. This nuanced approach ensures that only politically and economically consequential disparities are identified, advancing beyond earlier, cruder methods.
One of the most remarkable aspects of this breakthrough is its generalizability. Since it operates without an intermediate translation step, this methodology can detect hidden divergences in any bilingual or multilingual high-stakes environment. Legal treaties, government contracts, and other official documents stand to benefit from this technology, enabling stakeholders to root out covert informational asymmetries and enforce greater transparency.
The research reveals that these discrepancies, termed “translation gaps,” are not offhand mistakes or translation errors but deliberate, systematic strategies. When a company’s English report conveys markedly different information from its Chinese counterpart, it fuels increased information asymmetry. This imbalance profoundly affects market fairness, with foreign investors routinely receiving lower-quality disclosures, which in turn hampers their ability to produce accurate financial forecasts.
Moreover, this strategic withholding is not limited to casual information but focuses on complex, relationship-based content intrinsic to local market knowledge. Companies emphasize straightforward accounting details in English to cater to foreign investors’ specific governance concerns but obscure nuanced insights that local investors naturally access. This dynamic deepens the structural disadvantage embedded within the global financial ecosystem.
To validate these findings, Professor Wong’s team undertook a bold field experiment, posing as investors engaging directly with companies. The results were unequivocal: firms exhibiting larger translation gaps were significantly less responsive to inquiries from foreign investor personas. This deliberate reluctance to engage highlights an intentional strategy aimed at maintaining informational barriers rather than simple oversight or incompetence.
This body of research has immediate and significant implications for global regulators. While cutting-edge AI tools can bring hidden translation biases to light, they cannot by themselves enforce equitable disclosure practices. Without regulatory mandates requiring companies to provide identical information across languages, these translation gaps persist, benefiting domestic stakeholders at the cost of international market fairness.
Professor Wong’s extensive experience in market supervision bolsters the policy relevance of this work. His prior studies have informed pivotal rulings by the United States Securities and Exchange Commission (SEC), including the 2023 Final Rule on Modernization of Beneficial Ownership Reporting and the 2024 Final Rule concerning Short Position and Short Activity Reporting. His expertise has also contributed to addressing climate-related data gaps, notably cited by Deutsche Bundesbank.
Supported by prestigious programs such as the Google Cloud Research Credits, this research merges advanced technological innovation with profound regulatory insight. It surfaces critical evidence showing that, despite technological progress, bridging global equity markets’ informational divides ultimately hinges on regulatory intervention. Such reforms are vital to preserving market integrity and ensuring that foreign capital can compete on a genuinely level playing field.
As financial globalization advances, the findings from this study underscore the urgency of transparency reforms. Investors, regulators, and academics alike must recognize that language and culture are not mere barriers but tools wielded strategically within corporate communication. Unlocking truly global finance requires dismantling these engineered informational silos, using both technology and policy to uphold equity across borders.
Subject of Research:
Article Title: Lost in translation: CityUHK research unveils hidden “home court advantages” in the market
News Publication Date: 25-Mar-2026
Web References: http://dx.doi.org/10.2308/TAR-2023-0274
Image Credits: City University of Hong Kong
Keywords: Economics, Business, Information Asymmetry, Translation Gaps, Machine Learning, Artificial Intelligence, Financial Disclosure, Corporate Communication, Regulatory Policy, Investor Relations
