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Scalable and Imbalance-Resistant Machine Learning Models for Anti-money Laundering: A Two-Layered Approach

Crossref DOI link: https://doi.org/10.1007/978-3-030-64466-6_3

Published Online: 2020-11-26

Published Print: 2020

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Tertychnyi, Pavlo

Slobozhan, Ivan

Ollikainen, Madis

Dumas, Marlon
License Information

Text and Data Mining valid from 2020-01-01

Version of Record valid from 2020-01-01

Text and Data Mining valid from 2020-01-01

Version of Record valid from 2020-01-01
More Information

Chapter History

First Online: 26 November 2020

Conference Information

Conference Acronym: FinanceCom

Conference Name: International Workshop on Enterprise Applications, Markets and Services in the Finance Industry

Conference City: Helsinki

Conference Country: Finland

Conference Year: 2020

Conference Start Date: 18 August 2020

Conference End Date: 18 August 2020

Conference Number: 10

Conference ID: financecom2020

Peer Review Information (provided by the conference organizers)

Type: Double-blind

Conference Management System: none

Number of Submissions Sent for Review: 14

Number of Full Papers Accepted: 6

Number of Short Papers Accepted: 1

Acceptance Rate of Full Papers: 43% - The value is computed by the equation "Number of Full Papers Accepted / Number of Submissions Sent for Review * 100" and then rounded to a whole number.

Average Number of Reviews per Paper: 3

Average Number of Papers per Reviewer: 3

External Reviewers Involved: No

Additional Info on Review Process: planned to take place in Helsinki, Finland but due to COVID-19 held online