Professor Jamal Ouenniche

Event details

Venue: Business School Concourse

17:30- Lecture start

18:20 - Q&A

18:45 - Drinks Reception. - A small drinks reception will follow the lecture. All guest are welcome to attend.

Lecture abstract

Nowadays, the fields of data analytics, in general, and predictive analytics, in particular, are witnessing an unprecedented interest from a variety of stakeholders across many industries.

This talk is concerned with a new class of high-performance classifiers to predict risk class belonging and proposes a generic classification framework with plug-and-play implementation options.

The empirical performance of the proposed classifiers is tested on a data set of UK firms listed on the London Stock Exchange in predicting bankruptcy.

Numerical results demonstrate an outstanding predictive performance, which is robust to implementation decisions’ choices.

This exceptional predictive performance of the proposed new classifiers makes them real contenders in actual applications in areas such as finance and investment, internet security, fraud, medical diagnosis, and profiling of criminals to name a few, where the accuracy of the risk-class predictions has serious consequences for the relevant stakeholders.