Professor Mark Cummins
Accounting and Finance
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Publications
- Multimodal AI for Scaling Targeted Support : Navigating the FCA Advice–Guidance Boundary
- Zhang Hao, Bowden James, Cummins Mark
- Financial Regulation Innovation Lab White Paper Series Financial Regulation Innovation Lab White Paper Series (2026)
- https://doi.org/10.17868/strath.00095463
- From Crisis to Prosperity : AI and Open Finance for Holistic Financial Health and Smart Future Planning
- Bukovski Kal, Jain Kushagra, Cummins Mark, Bowden James, Tetteh Godsway Korku, Khang Zi
- Financial Regulation Innovation Lab White Paper Series Financial Regulation Innovation Lab White Paper Series (2025)
- https://doi.org/10.17868/strath.00094718
- How do corporate factors affect price discovery process between equity and credit markets?
- Zhou Xinquan, Bagnarosa Guillaume, Cummins Mark
- Accounting and Finance (2025)
- https://doi.org/10.1111/acfi.70116
- Supply Chain Intelligence : Actionable Risk Assessment of Brazilian Commodity Supply Chains Using Geospatial Data
- Owens Steve, Bowden James, Cummins Mark
- Financial Regulation Innovation Lab White Paper Series Financial Regulation Innovation Lab White Paper Series (2025)
- https://doi.org/10.17868/strath.00094187
- A multimodal sentiment classifier for financial decision making
- Todd Andrew, Bowden James, Cummins Mark, Su Yang
- International Review of Financial Analysis Vol 105 (2025)
- https://doi.org/10.1016/j.irfa.2025.104322
- Appraising model complexity in option pricing
- Cummins Mark, Esposito Francesco
- Journal of Futures Markets Vol 45, pp. 455-472 (2025)
- https://doi.org/10.1002/fut.22575
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Professional Activities
- 2025 Responsible Finance Workshop - "Responsible Business and AI"
- Organiser
- 22/5/2025
- Generative AI in Financial Services
- Organiser
- 10/10/2023
- Financial Regulation Innovation Lab: Barclays Stakeholder Workshop
- Participant
- 12/9/2023
- Financial Regulation Innovation Lab: Morgan Stanley Stakeholder Workshop
- Participant
- 23/6/2023
- Climate Finance Innovation: Connecting Financial Technology, Space Data and Resilient Timing
- Organiser
- 9/5/2023
- Space Meets FinTech (Joint FinTech Scotland / Space Scotland Event)
- Invited speaker
- 11/1/2023
Projects
- Fintech - Centre of Innovation in Financial Regulation (Glasgow City Region - Extension)
- Cummins, Mark (Principal Investigator) Basu, Devraj (Co-investigator) Bowden, James (Co-investigator) Shaw, Eleanor (Co-investigator) Tapinos, Efstathios (Co-investigator)
- 01-Jan-2025 - 31-Jan-2026
- Reaching New Heights: Strengthening the Scotland Ireland Partnership with Satellite Data (Strathclyde UCD research feasibility study)
- Owens, Steven Robert (Principal Investigator) Bowden, James (Co-investigator) Cummins, Mark (Co-investigator) Macdonald, Malcolm (Co-investigator) McKee, David (Co-investigator) White, Chris (Co-investigator)
- 01-Jan-2024 - 31-Jan-2025
- Transparent Textual-Audio Analysis via eXplainable AI (XAI) and Natural Language Processing (NLP) for improved ESG and Impact Measurement
- Bowden, James (Principal Investigator) Cummins, Mark (Principal Investigator)
- This project is funded by a Research Excellence Award (REA) for approximately £74,000 under the Strathclyde Research Studentship Scheme (SRSS).
Environmental, Social and Governance (ESG) credentials are of growing strategic importance for businesses, with ESG investing being increasingly prioritised by investors. Accurate ESG scoring of corporations is of paramount importance. ESG scoring systems in practice, however, have major weaknesses: (1) opaqueness in the proprietary methods used by private ESG scoring agencies; (2) observed inconsistencies in the ESG scores reported by alternative private ESG scoring systems (Berg et al., 2019); and (3) the extent of missing ESG scores across the population of corporations. Our proposed research directly addresses these weaknesses.
We seek to develop cutting-edge methods that offer transparency, consistency, and wide applicability in ESG measurement. We will leverage the power of Artificial Intelligence (AI), while addressing the ‘black-box' constraint of the underlying algorithms. State-of-the-art eXplainable Artificial Intelligence (XAI) techniques will be used, providing explainable outcomes. Such ‘white-box' XAI techniques will lead to transparent measurement of firms’ ESG performance, reconciliation of inconsistencies in existing ESG scoring systems, and wider application to the base of corporations.
The main contribution of our work will be the novel development and application of Natural Language Processing (NLP) based XAI approaches (Danilevsky et al., 2020) for textual-based measurement of ESG. Further contribution will be made by extending this work through the augmentation of textual analysis with audio characteristics of corporate earnings calls (such as manager pitch, tone and hesitancy), thus establishing an NLP classifier based on multiple modes of communication that may further enhance the reliability of our explainable ESG scoring approaches. - 02-Jan-2023 - 01-Jan-2026
- Fintech. Centre of Innovation in Financial Regulation (Innovation Accelerator)
- Cummins, Mark (Principal Investigator) Basu, Devraj (Co-investigator) Bowden, James (Co-investigator) Revie, Matthew (Co-investigator) Shaw, Eleanor (Co-investigator)
- 01-Jan-2023 - 31-Jan-2025
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Contact
Professor
Mark
Cummins
Accounting and Finance
Email: mark.cummins@strath.ac.uk
Tel: Unlisted