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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence, 32

Adapting to Concept Drift in Credit Card Transaction Data Streams Using Contextual Bandits and Decision Trees

March 15, 2023

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Published Date: 2018-02-08

Registration: ISSN 2374-3468 (Online) ISSN 2159-5399 (Print)

Copyright: Published by AAAI Press, Palo Alto, California USA Copyright © 2018, Association for the Advancement of Artificial Intelligence All Rights Reserved.

Authors

Dennis Soemers

Vrije Universiteit Brussel


Tim Brys

Vrije Universiteit Brussel


Kurt Driessens

Maastricht University


Mark Winands

Maastricht University


Ann Nowé

Vrije Universiteit Brussel


DOI:

10.1609/aaai.v32i1.11411


Abstract:

Credit card transactions predicted to be fraudulent by automated detection systems are typically handed over to human experts for verification. To limit costs, it is standard practice to select only the most suspicious transactions for investigation. We claim that a trade-off between exploration and exploitation is imperative to enable adaptation to changes in behavior (concept drift). Exploration consists of the selection and investigation of transactions with the purpose of improving predictive models, and exploitation consists of investigating transactions detected to be suspicious. Modeling the detection of fraudulent transactions as rewarding, we use an incremental Regression Tree learner to create clusters of transactions with similar expected rewards. This enables the use of a Contextual Multi-Armed Bandit (CMAB) algorithm to provide the exploration/exploitation trade-off. We introduce a novel variant of a CMAB algorithm that makes use of the structure of this tree, and use Semi-Supervised Learning to grow the tree using unlabeled data. The approach is evaluated on a real dataset and data generated by a simulator that adds concept drift by adapting the behavior of fraudsters to avoid detection. It outperforms frequently used offline models in terms of cumulative rewards, in particular in the presence of concept drift.

Topics: AAAI

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HOW TO CITE:

Dennis Soemers||Tim Brys||Kurt Driessens||Mark Winands||Ann Nowé Adapting to Concept Drift in Credit Card Transaction Data Streams Using Contextual Bandits and Decision Trees Proceedings of the AAAI Conference on Artificial Intelligence, 32 (2018) .

Dennis Soemers||Tim Brys||Kurt Driessens||Mark Winands||Ann Nowé Adapting to Concept Drift in Credit Card Transaction Data Streams Using Contextual Bandits and Decision Trees AAAI 2018, .

Dennis Soemers||Tim Brys||Kurt Driessens||Mark Winands||Ann Nowé (2018). Adapting to Concept Drift in Credit Card Transaction Data Streams Using Contextual Bandits and Decision Trees. Proceedings of the AAAI Conference on Artificial Intelligence, 32, .

Dennis Soemers||Tim Brys||Kurt Driessens||Mark Winands||Ann Nowé. Adapting to Concept Drift in Credit Card Transaction Data Streams Using Contextual Bandits and Decision Trees. Proceedings of the AAAI Conference on Artificial Intelligence, 32 2018 p..

Dennis Soemers||Tim Brys||Kurt Driessens||Mark Winands||Ann Nowé. 2018. Adapting to Concept Drift in Credit Card Transaction Data Streams Using Contextual Bandits and Decision Trees. "Proceedings of the AAAI Conference on Artificial Intelligence, 32". .

Dennis Soemers||Tim Brys||Kurt Driessens||Mark Winands||Ann Nowé. (2018) "Adapting to Concept Drift in Credit Card Transaction Data Streams Using Contextual Bandits and Decision Trees", Proceedings of the AAAI Conference on Artificial Intelligence, 32, p.

Dennis Soemers||Tim Brys||Kurt Driessens||Mark Winands||Ann Nowé, "Adapting to Concept Drift in Credit Card Transaction Data Streams Using Contextual Bandits and Decision Trees", AAAI, p., 2018.

Dennis Soemers||Tim Brys||Kurt Driessens||Mark Winands||Ann Nowé. "Adapting to Concept Drift in Credit Card Transaction Data Streams Using Contextual Bandits and Decision Trees". Proceedings of the AAAI Conference on Artificial Intelligence, 32, 2018, p..

Dennis Soemers||Tim Brys||Kurt Driessens||Mark Winands||Ann Nowé. "Adapting to Concept Drift in Credit Card Transaction Data Streams Using Contextual Bandits and Decision Trees". Proceedings of the AAAI Conference on Artificial Intelligence, 32, (2018): .

Dennis Soemers||Tim Brys||Kurt Driessens||Mark Winands||Ann Nowé. Adapting to Concept Drift in Credit Card Transaction Data Streams Using Contextual Bandits and Decision Trees. AAAI[Internet]. 2018[cited 2023]; .


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
Copyright 2022, Association for the Advancement of
Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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