SEMINAR: Imperial College London
Wednesday 8th August 2007, 3.00 - 4.00PM
Institute for Mathematical Sciences
53 Prince's Gate, South Kensington Campus
MODELLING CONSUMER ACCEPTANCE PROBABILITIES
Gimun Jung and Lyn Thomas
University of Southampton
Quantitative Financial Risk Management Centre
Abstract: This paper investigates how to estimate the likelihood of a customer
accepting a loan offer as a function of the offer parameters and how to choose
the optimal set of parameters for the offer to the applicant in real time.
There is no publicly available data set on whether customers accept the offer
of a financial product-the features of which are changing from offer to offer.
Thus, we develop our own data set using a Fantasy Student Current Account. In
this paper, we suggest three approaches to determine the probability that an
applicant with characteristics will accept offer characteristics using the
Fantasy Student Current Account data. Firstly, a logistic regression model is
applied to obtain the acceptance probability. Secondly, a linear programming is
adapted to obtain the acceptance probability model. To build a model, we assume
there is a dominant offer characteristic, where the probability of accepting the
offer increases (or decreases) monotonically as this characteristic’s value
increases. Finally, an accelerated life model is applied to obtain the
probability of acceptance in the case where there is a dominant offer
characteristic.
ALL WELCOME.
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