November 10, 2021, by lizst4

UK SMEs: quantifying their pandemic risk and credit risk exposures in the wake of the COVID-19 crisis

The COVID-19 pandemic is posing significant challenges to the economic activities of small and medium enterprises (SMEs) in the UK representing 75% of all job placements among directly affected sectors. A recent statistical insight from the Organization for Economic Cooperation and Development (OECD) reveals that several countries, including the UK, were ill-equipped to cope with the negative economic effects and prolonged lockdown measures that have increased UK SMEs’ exposure to credit risk.

UK SME credit risk exposure

There is little detailed attention to SMEs’ risk exposures and resilience towards funding shortages and how to support them in their economic activities during systemic crises, such as pandemics. The urgency of emergency funding for UK SMEs increased substantially due to several regional lockdowns and the three-tier system of COVID-19 restrictions.

Constructing a Pandemic Risk Index

In partnership with the Bank of England, Confederation of British Industry (CBI) and Experian, this project will address these issues and will construct a novel Pandemic Risk Index (PRI) to quantify the pandemic risk exposure of each SME and develop a novel Python programme suite (AI_CREDIT) to assess SMEs’ credit risk accurately and efficiently.

These innovative tools will offer much needed help for all types of lenders and provide the basis for policy interventions by HM Treasury, the Bank of England, Department for Business, Energy & Industrial Strategy (BEIS) and the CBI to support SMEs through COVID-19 disruption

Measuring UK SMEs credit risk exposure

We are using Artificial intelligence (AI) techniques including Machine Learning (ML), Deep Learning (DL), and Big Data to:

1) quantify the pandemic risk exposure of each SME by constructing a novel Pandemic Risk Index (PRI); and

2) assess SMEs’ credit risk accurately and efficiently by developing a novel Python programme suite (AI_CREDIT).

Both PRI and AI_CREDIT will rapidly fill an urgent need – helping policymakers and lenders to make funding decisions based on a comprehensive quantitative analysis of pandemic risk and credit risk exposures at the firm level.

Project Updates

• The industry-level market reactions to regional and national lockdown announcements represent a crucial factor in predicting the impact of the COVID outbreak on SMEs.
• The pandemic risk exposure of SMEs materialises mostly in the form of a reduction in the number of employees, a drop in domestic revenues, an increase in cash holdings (mainly due to lower operating and investing cash flows), and an increase in gearing and leverage.
• The drop in creditworthiness of many SMEs is most likely caused by a higher amount of non-current liabilities and borrowing.
• The preliminary version of our PRI has a strong predictive power of post-COVID changes in variables such as the number of employees, cash holdings, gearing, and leverage. In addition, we plan to develop a dynamic version of our PRI that can be updated daily, using market movements in industry-level indices and newly reported COVID cases and COVID-related deaths at the regional level.
• We have employed several models of machine learning to AI_CREDIT to estimate firms’ credit status before and during COVID-19. Our methods obtained reasonable performance, around 70%-90%, after fine-tuning parameters.

Team       

Principal investigator

Professor Meryem Duygun FAcSS

Meryem Duygun is a Professor of Banking and Finance at Nottingham University Business School. She holds an endowed chair in Risk and Insurance funded by the UK’s largest insurance company, Aviva. Meryem is a Fellow of the Academy of Social Sciences. She co-directs the Global Centre for Banking and Financial Innovation (GCBFI). Meryem is the Founding President of IFABS-International Finance and Banking Society, and she directs the University of Nottingham Fintech Research Network. Her expertise is in the areas of risk, financial technologies (FinTech) and Insurtech, and her research attracted funding from UK Research and Innovation, ESRC, and the British Academy.

Co-investigators

Dr Ahmed Barakat

Dr Ahmed Barakat is an Assistant Professor in Banking at Nottingham University Business School. Dr Barakat is a member of the leadership team of the Global Centre for Banking and Financial Innovation (GCBFI) and the Nottingham Fintech Research Network at the University of Nottingham.

Throughout his career, Dr Barakat has been a successful leader in several academic and professional projects in risk management, corporate governance, banking, insurance, audit, and financial reporting. In addition to his outstanding academic achievements, Dr Barakat has more than 15 years’ experience of professional consultancy engagements with commercial banks, investment banks, Islamic banks, insurance companies, oil and gas companies, and audit firms.

Dr Maurizio Fiaschetti

Maurizio is a Lecturer in Banking and Finance at the UCL Institute of Finance and Technology. Before joining UCL, he was an Assistant Professor in Finance, Risk and Banking at Nottingham University Business School where he was Director of the MSc in Banking. Previously, he was a Lecturer in Banking and Finance and Director of the MSc in Finance (major: Banking) at the School of Oriental and African Studies, University of London and he held research positions at Oxford University and at Universita’ di Roma – Tor Vergata. He has non-academic experience working as advisor and research officer with the Italian Bankers Association, the think tank Fondazione Manlio Masi, the Italian National Institute of Statistics and at the Ministry of the Environment.

Dr Tian Han

Tian Han is a postdoctoral research fellow at Nottingham University Business School. He obtained a PhD degree in Management from Henley Business School, University of Reading. Tian has published papers in leading journals such as British Journal of Management. He is interested in using big data analysis, network analysis textual analysis in addressing finance- and management-related issues.

Professor Enrico Onali

Enrico Onali is a Professor of Finance and the Head of Finance and Accounting Department at the University of Exeter Business School.

He serves as an Associate Editor for The British Accounting Review and is a Fellow of the Higher Education Academy (UK). He has received funding for his research from the European Commission (SHIFT project), ESRC (UKRI project) and the Deutsche Bundesbank. He has published in leading academic journals, such as the Review of Financial Studies, the Journal of Financial and Quantitative Analysis, the Journal of Financial Intermediation, and the Journal of Corporate Finance.

Dr Afshin Sabri

Afshin is a postdoctoral research fellow at Experian PLC*. He holds a PhD in Finance from Aston University and an MSc in Finance and Management from Cranfield University.

His research focuses on the banking sector and systemic risk. He has presented his work in several international academic conferences and events and taught finance and economics modules at Aston Business School.

Professor Mike Tsionas

Mike Tsionas is a Professor at Lancaster University Management School. Previous positions include the University of Toronto, Athens University of Economics and Business, and the Economic Policy Committee of the EU. Mike has published extensively in such journals as Review of Economic Studies, Journal of Econometrics, Journal of Applied Econometrics, Journal of the American Statistical Association, European Journal of Operations Research, International Journal of Production Economics.
Mike is a Fellow of the Journal of Econometrics, a Distinguished Author of the Journal of Applied Econometrics, and the Lancaster University Management School Dean’s Research Excellent Reward. His scientific interests include applied econometrics, Bayesian analysis and operations research.

Dr Huamao Wang

Huamao Wang is an Associate Professor in Finance, Risk and Banking at Nottingham University Business School. He obtained a PhD degree at the Centre for Advanced Studies in Finance at the University of Leeds.
Dr Wang publishes papers in journals including European Journal of Operational Research, European Journal of Finance, Quantitative Finance, Journal of Mathematical Economics, and Technological Forecasting and Social Change.
Dr Wang is a reviewer for UKRI Future Leaders Fellowships. He is a guest editor for Technological Forecasting and Social Change (ABS 3*, SSCI Q1, IF 5.846). He acts as a referee multiple times for European Journal of Operational Research, Journal of Banking & Finance, Journal of Economic Dynamics and Control, European Journal of Finance, Quantitative Finance, Journal of the Operational Research Society, Oxford University Press.

This project is funded by UK Research and Innovation (UKRI-ESRC) UK SMEs: quantifying their pandemic risk and credit risk exposures in the wake of the COVID-19 crisis

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