Multi-Armed Bandit to optimize the pricing strategy for consumer loans
(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.
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9101766
- author
- Nilsson, Joachim
- supervisor
- organization
- year
- 2022
- 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}}, }