Prof. Liangliang Jiang, Associate Professor at the School of Accounting and Finance (AF), led an industry-focused knowledge transfer research project with MSc in Accounting and Finance Analytics (MAFA) students Yuyan Wang and Yue Zheng.
The project was initiated by the Hong Kong Monetary Authority (HKMA) in collaboration with HSBC. The team was invited to present their findings at the HSBC Centre to its global Data Analytics team on 22 Apr 2026, with over 60 participants joining both in person and online.
The study develops a data-driven framework to predict the overseas expansion success of Chinese Small and Medium-sized Enterprises (SMEs), focusing on firms in the automotive and new-generation information technology (NGIT) industries. For financial institutions such as HSBC, the framework provides a practical screening tool to identify high-potential SME clients prior to their international expansion.
By integrating forward-looking indicators such as patent portfolios, overseas sales growth, and managerial readiness alongside traditional financial metrics, the framework enhances credit risk assessment, mitigates adverse selection, and supports more effective capital allocation.
The project was initiated by the Hong Kong Monetary Authority (HKMA) in collaboration with HSBC. The team was invited to present their findings at the HSBC Centre to its global Data Analytics team on 22 Apr 2026, with over 60 participants joining both in person and online.
The study develops a data-driven framework to predict the overseas expansion success of Chinese Small and Medium-sized Enterprises (SMEs), focusing on firms in the automotive and new-generation information technology (NGIT) industries. For financial institutions such as HSBC, the framework provides a practical screening tool to identify high-potential SME clients prior to their international expansion.
By integrating forward-looking indicators such as patent portfolios, overseas sales growth, and managerial readiness alongside traditional financial metrics, the framework enhances credit risk assessment, mitigates adverse selection, and supports more effective capital allocation.
