MINING CREDIT, LOYALTY AND PRICING DATA
EPSRC CASE PhD Studentship
Department of Mathematics, Imperial College
and Shell Research Ltd, Chester
Supervised by David Hand (IC) and Philip Jonathan (Shell)
We are seeking a student to undertake research, leading to a PhD, on the
data mining project outlined below. The successful candidate will have
statistical and computational skills and will join a successful team working
in the area of data mining.
The project:
The huge quantities of data accumulating in the retail sector present
opportunities and challenges for statistics. This project seeks to adapt
and develop statistical tools for modelling and pattern detection in retail
transaction databases. The following areas are of especial interest:
1) Credit scoring: to establish predictive models for high and low credit
risk.
2) Attrition modelling: to identify the key drivers and predict the
probability that an individual will decline or cease to participate in a
particular credit or loyalty scheme.
3) Behavioural modelling: predicting individual customer behaviour from
entry characteristics and behaviour so far.
4) Champion/Challenger strategies: evaluating relative performance of
competing approaches to credit and loyalty programme management in real
time, and managing transitions from one strategy to another.
5) Pricing modelling: of current and future movement/volume and sales
margin for a portfolio of products.
6) Cross-selling: optimisation of added value of cross-selling marketing
campaigns.
The studentship:
The studentship will be jointly supervised by Prof David Hand and Dr Philip
Jonathan. It will be based at Imperial College in London, but the student
will spend periods at Shell Research and within Shell's retail and financial
services organisations.
The standard EPSRC grant will be supplemented by a contribution from Shell.
The studentship will start on 1st October 2000.
Please address enquiries to Professor David J. Hand, Department of
Mathematics, Imperial College, 180 Queen's Gate, London SW7 2BZ or
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