The past few years have seen considerable interest in developing credit models to include new data sources. This is particualrly valuable in developing economies where most people have no relevant data associated with them, which means they cannot currently access credit and other financial services.

The scope of use of people's scores is also expanding, and nowhere more so than in China, where the state and private enterprises are attempting to introduce 'social credit systems' in to support the economic and political system.

What is the truth about these systems and these practices? What can we learn from recent experiments, and what are the benefits and risks of using data-based metrics in calculating social risk and entitlement.

Jonathan is Professor of Business Economics, Deputy Dean and Director of Research at the University Business School, and director of the Credit Research Centre which he has led for a number of decades.He concentrates on two research areas:

1. Modelling of credit risk and operational risk. The former includes survival and multistate modelling, modelling of loss given default, of exposure at default and stress testing. I am particularly interested in using novel predictors, issues concerning variation over time, capital requirements issues and the use of very large datasets. I am interested in models for retail credit of all types as well as credit to SMEs and large corporates.
2. Economics of the consumer credit including the demand (consumption and finance models), the supply of credit and credit constraints using household level data.