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

Small and medium-sized enterprises (SMEs) constitute a critical pillar of the UK economy. More than 99% of the roughly 6 million businesses in the UK are SMEs and they employ more than 16 million workers in 2019. As the impact of COVID-19 pandemic becomes clearer, it is evident that SMEs are faced with serious and unprecedented challenges, including declining revenues, defaulting on loans, inability to retain employees and postponing growth plans. There is, however, little detailed attention to their risk exposures and resilience towards funding shortages and how to urgently support them in their economic activities. The project is in collaboration with the Bank of England and Confederation of British Industry (CBI), leading business lobby group, that promotes business interests with government and deals with the impact of policy on businesses in the UK. We will use Artificial intelligence (AI) techniques including Machine Learning (ML), Deep Learning (DL), and Big Data: 1) to quantify the pandemic risk exposure of each SME through constructing a novel Pandemic Risk Index (PRI); and 2) to 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 by helping policymakers and lenders to make funding decisions based on a comprehensive quantitative analysis of pandemic risk and credit risk exposures at the enterprise level. Overall, this project is directly aligned with the UKRI Priority Area: "Modelling, AI, digital and data approaches to understanding of the COVID-19 pandemic and mitigating its effect".