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Muhammad Usman Bilal Sufi

Muhammad Usman Bilal Sufi is a Teaching and Research Fellow at the Innovation and Technology Centre, Lahore School of Economics. He holds an MPhil in Business Administration from the Lahore School of Economics and has over three years of teaching and research experience. His expertise lies in finance-related subjects, including Financial Management, Banking, Financial Institutions and Markets, and Investments. Usman is committed to providing students with a strong foundation in financial concepts, while also exploring their real-world applications in an ever-evolving financial landscape.

His research interests center on corporate governance, risk management, and the application of machine learning in financial prediction models. Usman has contributed to several impactful publications in these areas. Through his research, he seeks to advance innovative methodologies—particularly machine learning—to strengthen financial prediction models and enhance corporate governance practices, with a specific focus on emerging economies.

  1. Hasan, A., Sufi, U., & Hussainey, K. (2023). Risk committee characteristics and risk disclosure in banks: Evidence from an emerging economy. Journal of Applied Accounting Research, 24(5), 910-932.
  2. Sufi, U., Hasan, A., & Hussainey, K. (2024). Improving the prediction of firm performance using nonfinancial disclosures: A machine learning approach. Journal of Accounting in Emerging Economies, 14(5), 1223-1251.
  3. Hasan, A., Sufi, U., Elmarzouky, M., & Hussainey, K. (2025). The impact of corporate governance on narrative disclosure tone: A machine learning approach. Journal of Applied Accounting Research, 26(3), 577-602.