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:
- 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.
- Economics of the consumer credit including the
demand (consumption and finance models), the supply of credit and credit
constraints using household level data.