About
Dr Katarzyna (Kasia) Bijak is Lecturer in Management Science within 天发娱乐棋牌_天发娱乐APP-官网|下载 Business School at the University of 天发娱乐棋牌_天发娱乐APP-官网|下载.
Research
Research groups
Research interests
- Application of statistical methods (including Bayesian inference)
- Data mining?
- Artifical intelligence
- Stochastic processes
- Econometrics
Current research
Kasia's research interests focus on applying quantitative methods in credit scoring. In particular, she is interested in the applications of statistical methods (including Bayesian inference), data mining, artificial intelligence, stochastic processes and econometrics.
Among other things, Kasia's research concentrates on introducing dynamics into consumer risk models (e.g. by using Kalman filters and random effects), as this is recognised as one of the current challenges in credit scoring. Kasia has also been working on the following topics:
- dynamic affordability assessment
- evaluating performance of LGD models
- application of scoring in other areas, especially in intensive care.
Publications
Teaching
Kasia has taught on a variety of modules, including
MANG6321 Introduction to Business Analytics and Management Sciences
Biography
Kasia obtained an MSc in Quantitative Methods and Information Systems from the Warsaw School of Economics in 2004. She subsequently started working in banking industry: first in a leading bank and then in a credit reference agency, where she developed application, behavioural, credit bureau and propensity scoring models.
In 2009, Kasia moved to the UK to pursue a PhD programme in the 天发娱乐棋牌_天发娱乐APP-官网|下载 Business School at the University of 天发娱乐棋牌_天发娱乐APP-官网|下载. She was awarded her PhD in 2013 for a thesis on selected modelling problems in credit scoring: segmentation, modelling Loss Given Default (LGD) and affordability assessment.
In September 2013, Kasia took up the post of Lecturer in Management Science in the 天发娱乐棋牌_天发娱乐APP-官网|下载 Business School.