IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1912.07701.html
   My bibliography  Save this paper

Exploring Multi-Banking Customer-to-Customer Relations in AML Context with Poincar\'e Embeddings

Author

Listed:
  • Lucia Larise Stavarache

    (IBM Global Business Services)

  • Donatas Narbutis

    (IBM Lithuania, Client Innovation Center Baltic)

  • Toyotaro Suzumura

    (IBM T.J. Watson Research Center)

  • Ray Harishankar

    (IBM Global Business Services)

  • Augustas v{Z}altauskas

    (IBM Lithuania, Client Innovation Center Baltic)

Abstract

In the recent years money laundering schemes have grown in complexity and speed of realization, affecting financial institutions and millions of customers globally. Strengthened privacy policies, along with in-country regulations, make it hard for banks to inner- and cross-share, and report suspicious activities for the AML (Anti-Money Laundering) measures. Existing topologies and models for AML analysis and information sharing are subject to major limitations, such as compliance with regulatory constraints, extended infrastructure to run high-computation algorithms, data quality and span, proving cumbersome and costly to execute, federate, and interpret. This paper proposes a new topology for exploring multi-banking customer social relations in AML context -- customer-to-customer, customer-to-transaction, and transaction-to-transaction -- using a 3D modeling topological algebra formulated through Poincar\'e embeddings.

Suggested Citation

  • Lucia Larise Stavarache & Donatas Narbutis & Toyotaro Suzumura & Ray Harishankar & Augustas v{Z}altauskas, 2019. "Exploring Multi-Banking Customer-to-Customer Relations in AML Context with Poincar\'e Embeddings," Papers 1912.07701, arXiv.org, revised Jun 2020.
    • Handle: RePEc:arx:papers:1912.07701
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1912.07701
    File Function: Latest version
    Download Restriction: no
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1912.07701. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: arXiv administrators (email available below). General contact details of provider: http://arxiv.org/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.