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Multi-Armed Bandit to optimize the pricing strategy for consumer loans

Nilsson, Joachim (2022)
Department of Automatic Control
Abstract
This thesis explores the possibility of framing the problem of setting prices for consumer loans on loan comparison sites as a Multi-Armed Bandit Problem. The problem is solved by creating a Multi-Armed Bandit environment based on SEB:s expert knowledge of the problem. Different Multi-Armed Bandit algorithms are then compared in a stationary environment after which the best performing algorithm is modified to handle a non-stationary environment. We found that the Sliding-Window Thompson Sampling is the best choice of algorithm for the problem. Furthermore, we show that this method is not sensitive to the assumptions made when generating the non-stationary environment, thus making it a promising method for real-world application.
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author
Nilsson, Joachim
supervisor
organization
year
type
H3 - Professional qualifications (4 Years - )
subject
report number
TFRT-6183
ISSN
0280-5316
language
English
id
9101766
date added to LUP
2022-10-14 10:48:05
date last changed
2022-10-14 10:48:05
@misc{9101766,
  abstract     = {{This thesis explores the possibility of framing the problem of setting prices for consumer loans on loan comparison sites as a Multi-Armed Bandit Problem. The problem is solved by creating a Multi-Armed Bandit environment based on SEB:s expert knowledge of the problem. Different Multi-Armed Bandit algorithms are then compared in a stationary environment after which the best performing algorithm is modified to handle a non-stationary environment. We found that the Sliding-Window Thompson Sampling is the best choice of algorithm for the problem. Furthermore, we show that this method is not sensitive to the assumptions made when generating the non-stationary environment, thus making it a promising method for real-world application.}},
  author       = {{Nilsson, Joachim}},
  issn         = {{0280-5316}},
  language     = {{eng}},
  note         = {{Student Paper}},
  title        = {{Multi-Armed Bandit to optimize the pricing strategy for consumer loans}},
  year         = {{2022}},
}