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    Anti-money laundering detection and customer segmentation

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    hdip_kuvaeva_n_2020.pdf (1.061Mb)
    Author
    Kuvaeva, Nadezda
    Date
    2020
    Degree
    Higher Diploma in Science in Data Analytics
    URI
    https://esource.dbs.ie/handle/10788/4001
    Publisher
    Dublin Business School
    Rights holder
    http://esource.dbs.ie/copyright
    Rights
    Items in Esource are protected by copyright. Previously published items are made available in accordance with the copyright policy of the publisher/copyright holder.
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    Abstract
    In this project we going to cover best practices of the anti-money laundering techniques and methods, such a customer segmentation based on suspicious behaviour and fraud detection machine learning algorithms. The goal of the project is to define what payment instrument used for the money laundering the most, so financial institution can reinforce their fraud detection process for this specific payment method and work closely with the bank provider. We going to implement and compare different machine learning classification and clustering algorithms and find out what method is more accurate and suits better for crime detection problem on the specific financial instrument.
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