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Model for Identification of Politically Exposed Persons

  • Zane Miltina
  • Arnis Stasko
  • Ingars Erins
  • Janis Grundspenkis
  • Marite Kirikova
  • Girts Kebers
Conference paper
Part of the Lecture Notes in Business Information Processing book series (LNBIP, volume 295)

Abstract

Due to increasing strength of regulatory requirements in area of money laundering and terrorism financing prevention, financial institutions are looking for ways to retrieve, analyse and interpret relevant information on politically exposed persons (PEPs). Task addresses complex decision making over distributed data. Manual PEP identification is labour and time consuming, therefore, IT solutions are necessary to support and enhance the process. This paper highlights the complexity of regulatory demands inherent in the PEP definition, reveals a number of requirements for PEP identification and proposes a model for PEP status identification. The model follows a multi-agent paradigm enabling several scenarios of PEP identification with involvement of software and human agents. Although the proposed PEP status identification model is created in accordance with the regulatory requirements and countries specific data sources for the Republic of Latvia, still, the model can be adjusted for use also in other EU countries.

Keywords

Politically exposed person Multi-agent approach Data and business analytics Conceptual modelling 

Notes

Acknowledgment

The research leading to these results has received funding from the research project “Competence Centre of Information and Communication Technologies” of EU Structural funds, contract No. 1.2.1.1/16/A/007 signed between IT Competence Centre and Central Finance and Contracting Agency, Research No. 1.14 “Development of Data Processing Algorithm Flow Optimisation Model for Identification of Politically Exposed Persons”.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Zane Miltina
    • 1
  • Arnis Stasko
    • 1
  • Ingars Erins
    • 1
  • Janis Grundspenkis
    • 1
  • Marite Kirikova
    • 1
  • Girts Kebers
    • 2
  1. 1.Riga Technical UniversityRigaLatvia
  2. 2.SIA “Lursoft IT”RigaLatvia

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