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.
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References
Johannesson, P., Perjons, E.: A method framework for design science research. In: Johannesson, P., Perjons, E. (eds.) An Introduction to Design Science, pp. 75–89. Springer, Cham (2014). doi:10.1007/978-3-319-10632-8_4
Wieringa, R.J.: Design Science Methodology for Information Systems and Software Engineering. Springer, Heidelberg (2014). doi:10.1007/978-3-662-43839-8
Law on the Prevention of Money Laundering and Terrorism Financing (in Latvian - Noziedzīgi iegūtu līdzekļu legalizācijas un terorisma finansēšanas novēršanas likums). https://likumi.lv/doc.php?id=178987. Accessed 23 Feb 2017
FATF Guidance politically exposed persons (recommendations 12 and 22). http://www.fatf-gafi.org/media/fatf/documents/recommendations/guidance-pep-rec12-22.pdf. Accessed 30 Mar 2017
Recommendations for Credit Institutions and Financial Institutions to Establish and Research Politically Exposed Persons, their Family Members, and Closely-related Persons and to Monitor Transactions. http://www.fktk.lv/en/law/credit-institutions/fcmc-regulations/5652-recommendations-for-credit-institutions-and-financial-institutions-to-establish-and-research-politically-exposed-persons-their-family-members-and-closely-related-persons-and-to-monitor-tr. Accessed 30 Mar 2017
Reduce Time Spent Screening Politically Exposed Persons. https://www.casewareanalytics.com/events/webinar-reduce-time-spent-screening-politically-exposed-persons. Accessed 30 Mar 2017
Reduce Time Spent Screening Politically Exposed Persons, Webinar. https://www.youtube.com/watch?v=10bbVf1pEsI. Accessed 30 Mar 2017
Schiffer, M.A.: Method of Ranking Politically Exposed Persons and Other Heightened Risk Persons and Entities, US 8069126 B2, US20080281765, WO2008141161A1 (2008)
Lawrence, D.: Automated political risk management, CA2437310A1, EP1358606A2, EP1358606A4, US7181428, US7711637, US8099357, US20020103747, US2007027675, US20100138262, US20120284186, WO 2002061663 A2, WO2002061663A3 (2001)
Lawrence, D., Nitze, P., MacDonald, A.: Method, system, apparatus, program code and means for identifying and extracting information, US8996481, US20150278289 (2004)
Roland, B., Swim, D.C., Messina, T., Conolly, W.P.: Evaluating customer risk, US20070288355A1 (2006)
Regulations on the Latvian Population Registration System Classifier (in Latvian - Noteikumi par Latvijas iedzīvotāju reģistrācijas sistēmas klasifikatoru). https://likumi.lv/doc.php?id=187420&from=off. Accessed 23 Feb 2017
Kastrati, Z., Imran, A.S.: Yayilgan, S.Y.: An improved concept vector space model for ontology based classification. In: 2015 11th International Conference on Signal-Image Technology and Internet-Based Systems (SITIS), pp. 240–245 (2015)
Protégé. http://protege.stanford.edu/. Accessed 30 Mar 2017
Llinas, J., Hall, D.L.: An introduction to multi-sensor data fusion. In: Proceedings of the 1998 IEEE International Symposium on Circuits and Systems, ISCAS 1998 (Cat. No. 98CH36187), vol. 6, pp. 537–540 (1998)
Blasch, E., et al.: Issues and challenges in situation assessment (level 2 fusion). J. Adv. Inf. FUSIO 1(2), 122–139 (2006)
Ingersoll, G.S., Morton, T.S., Farris, A.L.: Taming Text: How to Find, Organise, and Manipulate It. Manning, Greenwich (2013)
Riga Technical University: Deliverable 1 “Data Validation Method and their Algorithm, Statistical and Mathematical Model Evaluation on the Basis of Available Data Sources, Aimed to Assess the Most Appropriate Methods to be Used (including Algorithms) for the Development of Optimal Algorithm Execution Flow Model.” of research project “Development of Data Processing Algorithm Flow Optimisation Model for Identification of Politically Exposed Persons” developed for IT Competence Centre and Central Finance and Contracting Agency (2017)
Padgham, L., Winikoff, M.: Developing Intelligent Agent Systems: A Practical Guide. Wiley, Hoboken (2004)
Jennings, N.R.: An agent-based approach for building complex software systems. Commun. ACM 44(4), 35–41 (2001)
With a view to identify politically exposed persons, banks will start customer interrogation (in Latvian - Nolūkā identificēt politiski nozīmīgas personas bankas sāks klientu izvaicāšanu | Financenet | TVNET). http://financenet.tvnet.lv/finansu_zinas/605924-noluka_identificet_politiski_nozimigas_personas_bankas_saks_klientu_izvaicasanu. Accessed 30 Mar 2017
Riga Technical University: Deliverable 2 “Selection of the Most Appropriate Methods for the Development of Model for Politically Exposed Persons Identification” of research project “Development of Data Processing Algorithm Flow Optimisation Model for Identification of Politically Exposed Persons” developed for IT Competence Centre and Central Finance and Contracting Agency (2017)
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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Miltina, Z., Stasko, A., Erins, I., Grundspenkis, J., Kirikova, M., Kebers, G. (2017). Model for Identification of Politically Exposed Persons. In: Johansson, B., Møller, C., Chaudhuri, A., Sudzina, F. (eds) Perspectives in Business Informatics Research. BIR 2017. Lecture Notes in Business Information Processing, vol 295. Springer, Cham. https://doi.org/10.1007/978-3-319-64930-6_10
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DOI: https://doi.org/10.1007/978-3-319-64930-6_10
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