Identifying Money Laundering Risk in the United Kingdom: Observations from National Risk Assessments and a Proposed Alternative Methodology
Two National Risk Assessments (NRA) of money laundering (ML) have now been published in the United Kingdom (see HM Treasury 2015 and 2017 ). While both represent an attempt to identify the risks of ML, there are limitations in relation to the conceptual framework and the methodology used. This paper...
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description | Two National Risk Assessments (NRA) of money laundering (ML) have now been published in the United Kingdom (see HM Treasury
2015
and
2017
). While both represent an attempt to identify the risks of ML, there are limitations in relation to the conceptual framework and the methodology used. This paper reviews the UK NRAs and considers whether revision of the methodology employed could help to both remedy these limitations and generate more robust findings. Drawing upon the findings of the UK strand of project Identifying and Assessing the Risk of Money Laundering in Europe (IARM), it outlines how a composite ML risk indicator was developed through analysis of threats and vulnerabilities across 43 police areas. The findings demonstrate that risks are highest in the City of London and the Metropolitan Police area, which is largely explained by the presence of organised crime groups, connections to risky jurisdictions and the cash intensity of businesses. Although the findings should be treated with caution, it is posited that this methodology could be used to help future NRAs develop a more robust framework to understand ML risk and ultimately develop more effective preventative strategies. |
doi_str_mv | 10.1007/s10610-018-9390-5 |
format | Article |
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2015
and
2017
). While both represent an attempt to identify the risks of ML, there are limitations in relation to the conceptual framework and the methodology used. This paper reviews the UK NRAs and considers whether revision of the methodology employed could help to both remedy these limitations and generate more robust findings. Drawing upon the findings of the UK strand of project Identifying and Assessing the Risk of Money Laundering in Europe (IARM), it outlines how a composite ML risk indicator was developed through analysis of threats and vulnerabilities across 43 police areas. The findings demonstrate that risks are highest in the City of London and the Metropolitan Police area, which is largely explained by the presence of organised crime groups, connections to risky jurisdictions and the cash intensity of businesses. Although the findings should be treated with caution, it is posited that this methodology could be used to help future NRAs develop a more robust framework to understand ML risk and ultimately develop more effective preventative strategies.</description><identifier>ISSN: 0928-1371</identifier><identifier>EISSN: 1572-9869</identifier><identifier>DOI: 10.1007/s10610-018-9390-5</identifier><language>eng</language><publisher>Dordrecht: Springer Netherlands</publisher><subject>Criminology ; Criminology and Criminal Justice ; Laundering of money ; Law and Criminology ; Money ; Money laundering ; Organized crime ; Police ; Political Science ; Prevention ; Research methodology ; Risk assessment</subject><ispartof>European journal on criminal policy and research, 2019-03, Vol.25 (1), p.63-82</ispartof><rights>The Author(s) 2018</rights><rights>European Journal on Criminal Policy and Research is a copyright of Springer, (2018). All Rights Reserved. © 2018. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c359t-f2463b23075cb8d1e6922272ef8dece044348e1d4d8e0f152737e441912dd06a3</citedby><cites>FETCH-LOGICAL-c359t-f2463b23075cb8d1e6922272ef8dece044348e1d4d8e0f152737e441912dd06a3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s10610-018-9390-5$$EPDF$$P50$$Gspringer$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s10610-018-9390-5$$EHTML$$P50$$Gspringer$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,27321,27843,27901,27902,33751,41464,42533,51294</link.rule.ids></links><search><creatorcontrib>Hopkins, Matt</creatorcontrib><creatorcontrib>Shelton, Nikki</creatorcontrib><title>Identifying Money Laundering Risk in the United Kingdom: Observations from National Risk Assessments and a Proposed Alternative Methodology</title><title>European journal on criminal policy and research</title><addtitle>Eur J Crim Policy Res</addtitle><description>Two National Risk Assessments (NRA) of money laundering (ML) have now been published in the United Kingdom (see HM Treasury
2015
and
2017
). While both represent an attempt to identify the risks of ML, there are limitations in relation to the conceptual framework and the methodology used. This paper reviews the UK NRAs and considers whether revision of the methodology employed could help to both remedy these limitations and generate more robust findings. Drawing upon the findings of the UK strand of project Identifying and Assessing the Risk of Money Laundering in Europe (IARM), it outlines how a composite ML risk indicator was developed through analysis of threats and vulnerabilities across 43 police areas. The findings demonstrate that risks are highest in the City of London and the Metropolitan Police area, which is largely explained by the presence of organised crime groups, connections to risky jurisdictions and the cash intensity of businesses. Although the findings should be treated with caution, it is posited that this methodology could be used to help future NRAs develop a more robust framework to understand ML risk and ultimately develop more effective preventative strategies.</description><subject>Criminology</subject><subject>Criminology and Criminal Justice</subject><subject>Laundering of money</subject><subject>Law and Criminology</subject><subject>Money</subject><subject>Money laundering</subject><subject>Organized crime</subject><subject>Police</subject><subject>Political Science</subject><subject>Prevention</subject><subject>Research methodology</subject><subject>Risk assessment</subject><issn>0928-1371</issn><issn>1572-9869</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><sourceid>C6C</sourceid><sourceid>7TQ</sourceid><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>BHHNA</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNp1kMtKA0EQRRtRMD4-wF2D69Gq7nm1uyC-MD4QXTeTdI2OTrpj1ySQb_CnnTiCK1dFFfdciiPEEcIJAhSnjJAjJIBlYrSBJNsSI8wKlZgyN9tiBEaVCeoCd8Ue8zsAYparkfi6ceS7pl43_lXeBU9rOamW3lHcHJ4a_pCNl90byRffdOTkbX93YX4mH6ZMcVV1TfAs6xjm8v5nqdoBGzMT87xvZ1l5Jyv5GMMicN8xbjuKvk-vSN5R9xZcaMPr-kDs1FXLdPg798XL5cXz-XUyebi6OR9PkpnOTJfUKs31VGkostm0dEi5UUoViurS0YwgTXVaErrUlQQ1ZqrQBaUpGlTOQV7pfXE89C5i-FwSd_Y9LPt_WrYKstxAaXTRp3BIzWJgjlTbRWzmVVxbBLtxbgfntnduN85t1jNqYHix8Ufxr_l_6BsRcIXe</recordid><startdate>20190301</startdate><enddate>20190301</enddate><creator>Hopkins, Matt</creator><creator>Shelton, Nikki</creator><general>Springer Netherlands</general><general>Springer Nature B.V</general><scope>C6C</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>0-V</scope><scope>3V.</scope><scope>7TQ</scope><scope>7U4</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>87Z</scope><scope>88J</scope><scope>8AM</scope><scope>8BF</scope><scope>8BJ</scope><scope>8FK</scope><scope>8FL</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ALSLI</scope><scope>AXJJW</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGRYB</scope><scope>BHHNA</scope><scope>CCPQU</scope><scope>DHY</scope><scope>DON</scope><scope>DPSOV</scope><scope>DWI</scope><scope>DWQXO</scope><scope>FQK</scope><scope>FREBS</scope><scope>FRNLG</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HEHIP</scope><scope>JBE</scope><scope>K60</scope><scope>K6~</scope><scope>K7.</scope><scope>KC-</scope><scope>L.-</scope><scope>M0C</scope><scope>M0O</scope><scope>M0Q</scope><scope>M2L</scope><scope>M2O</scope><scope>M2R</scope><scope>M2S</scope><scope>MBDVC</scope><scope>PQBIZ</scope><scope>PQBZA</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope><scope>WZK</scope></search><sort><creationdate>20190301</creationdate><title>Identifying Money Laundering Risk in the United Kingdom: Observations from National Risk Assessments and a Proposed Alternative Methodology</title><author>Hopkins, Matt ; Shelton, Nikki</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c359t-f2463b23075cb8d1e6922272ef8dece044348e1d4d8e0f152737e441912dd06a3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Criminology</topic><topic>Criminology and Criminal Justice</topic><topic>Laundering of money</topic><topic>Law and Criminology</topic><topic>Money</topic><topic>Money laundering</topic><topic>Organized crime</topic><topic>Police</topic><topic>Political Science</topic><topic>Prevention</topic><topic>Research methodology</topic><topic>Risk assessment</topic><toplevel>online_resources</toplevel><creatorcontrib>Hopkins, Matt</creatorcontrib><creatorcontrib>Shelton, Nikki</creatorcontrib><collection>Springer Nature OA Free Journals</collection><collection>CrossRef</collection><collection>ProQuest Social Sciences Premium Collection</collection><collection>ProQuest Central (Corporate)</collection><collection>PAIS Index</collection><collection>Sociological Abstracts (pre-2017)</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ABI/INFORM Global (Alumni Edition)</collection><collection>Social Science Database (Alumni Edition)</collection><collection>Criminal Justice Database (Alumni Edition)</collection><collection>European Business Database (Alumni Edition)</collection><collection>International Bibliography of the Social Sciences (IBSS)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ABI/INFORM Collection (Alumni Edition)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Social Science Premium Collection</collection><collection>Asian & European Business Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Criminology Collection</collection><collection>Sociological Abstracts</collection><collection>ProQuest One Community College</collection><collection>PAIS International</collection><collection>PAIS International (Ovid)</collection><collection>Politics Collection</collection><collection>Sociological Abstracts</collection><collection>ProQuest Central Korea</collection><collection>International Bibliography of the Social Sciences</collection><collection>Asian & European Business Collection (Alumni)</collection><collection>Business Premium Collection (Alumni)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>Sociology Collection</collection><collection>International Bibliography of the Social Sciences</collection><collection>ProQuest Business Collection (Alumni Edition)</collection><collection>ProQuest Business Collection</collection><collection>ProQuest Criminal Justice (Alumni)</collection><collection>ProQuest Politics Collection</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Global</collection><collection>Criminal Justice Database (ProQuest)</collection><collection>European Business Database</collection><collection>Political Science Database</collection><collection>Research Library</collection><collection>Social Science Database</collection><collection>Sociology Database (ProQuest)</collection><collection>Research Library (Corporate)</collection><collection>One Business (ProQuest)</collection><collection>ProQuest One Business (Alumni)</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><collection>Sociological Abstracts (Ovid)</collection><jtitle>European journal on criminal policy and research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hopkins, Matt</au><au>Shelton, Nikki</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Identifying Money Laundering Risk in the United Kingdom: Observations from National Risk Assessments and a Proposed Alternative Methodology</atitle><jtitle>European journal on criminal policy and research</jtitle><stitle>Eur J Crim Policy Res</stitle><date>2019-03-01</date><risdate>2019</risdate><volume>25</volume><issue>1</issue><spage>63</spage><epage>82</epage><pages>63-82</pages><issn>0928-1371</issn><eissn>1572-9869</eissn><abstract>Two National Risk Assessments (NRA) of money laundering (ML) have now been published in the United Kingdom (see HM Treasury
2015
and
2017
). While both represent an attempt to identify the risks of ML, there are limitations in relation to the conceptual framework and the methodology used. This paper reviews the UK NRAs and considers whether revision of the methodology employed could help to both remedy these limitations and generate more robust findings. Drawing upon the findings of the UK strand of project Identifying and Assessing the Risk of Money Laundering in Europe (IARM), it outlines how a composite ML risk indicator was developed through analysis of threats and vulnerabilities across 43 police areas. The findings demonstrate that risks are highest in the City of London and the Metropolitan Police area, which is largely explained by the presence of organised crime groups, connections to risky jurisdictions and the cash intensity of businesses. Although the findings should be treated with caution, it is posited that this methodology could be used to help future NRAs develop a more robust framework to understand ML risk and ultimately develop more effective preventative strategies.</abstract><cop>Dordrecht</cop><pub>Springer Netherlands</pub><doi>10.1007/s10610-018-9390-5</doi><tpages>20</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Criminology Criminology and Criminal Justice Laundering of money Law and Criminology Money Money laundering Organized crime Police Political Science Prevention Research methodology Risk assessment |
title | Identifying Money Laundering Risk in the United Kingdom: Observations from National Risk Assessments and a Proposed Alternative Methodology |
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