Use of Social Media Big Data for Enhancing the Effectiveness of Credit Allocation to Companies
Leonie's research proposes a new method to more accurately predict the probability that a company will suffer financial distress. For this, she will exploit the vast increase in social media data put out by companies that should enable the development of more predictive models than those developed in the past. This will be done by relating a completely new type of information than has been considered in literature so far, that contained in company tweets put out on Twitter, to the incidence of distress. The work will be done with Experian, one of the largest data companies in the UK.
- Stochastic modelling
- Statistics for finance
- Nonlinear optimisation
- Econometrics of financial markets
- Forecasting in finance & marketing
- Financial econometrics
- Mathematical finance
- Big data analytics
- Behavioural finance
- Digital innovation
- Data mining
- Data analytics
- Credit risk modelling
Leonie is a first year PhD student at the University of Edinburgh Business School, in the Management Science and Business Economics research group. She has been awarded an ESRC Industry aligned Scholarship from the Scottish Graduate School of Social Science (SGSSS).
Leonie did her MSc in Statistics at Imperial College London in 2016/17 and she holds a BSc in Statistics from Ludwig-Maximilians-Universität München.