The aims and objectives of the Statistics in Finance Research Group are:

  • To apply statistical methods to problems in the financial industry
  • To develop new statistical methodology arising from the novel challenges presented by these applications

It is very apparent that the level of sophistication of the methods and tools used by banks and financial institutions to control their operations is increasing rapidly, and we aim to continue to be in the vanguard of this development. Our research involves all aspects of mathematics and statistics relating to the finance industry, including fraud detection, portfolio modelling, volatility, systemic risk and risk management.

We have numerous links with organisations within the retail banking sector, and are always involved in discussions with banks and other financial bodies about possible collaborations or research sponsorships.  Previous projects have been sponsored by Fair Isaac, Link Financial, and other bodies.

Further info

Specific areas of research interest within the Statistics in Finance research group

  • Limit order books and market microstructure (Pakkanen, Veraart)
  • Energy markets (Veraart)
  • Volatility modelling and forecasting (Pakkanen, Veraart)
  • Systemic risk (Gandy)
  • Evaluating scorecards (Hand,  Adams)
  • Fraud detection (Adams)
  • Applications of machine learning in credit risk modelling
  • Model risk in retail finance (Adams, with Yazhe Li)
  • Credit loss estimation and Loss-given-default

Impact / Industrial Collaborations / Consultancy

The Statistics in Finance Research Group are active collaborators with the finance industry and have been involved in many successful consultancy projects with several financial institutions over the past thirty years. We usually work through Imperial Consultants (ICON). Some types of consultancy projects we have undertaken are:

  • Credit risk model development
  • Model validation and evaluation
  • Data network analysis
  • Fraud detection models

Researchers involved