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CINA Distinguished Speakers Series 2019: The Business of Transnational Crime, Channing Mavrellis
March 5, 2019 @ 12:00 pm - 1:30 pm
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Channing Mavrellis is a Certified Anti-Money Laundering Specialist (CAMS), transnational crime analyst, and author of the March 2017 report, “Transnational Crime and the Developing World,” which explores 11 different criminal markets, and their dynamics and impact on developing countries.
Join us on Tuesday March 5th in Exploratory Hall 3301 from 12:00 pm- 1:30 pm for food, refreshments, and learning about the business of transnational organized crime (TOC), focusing on the professionalization of different sectors and roles, the interplay between legal and illegal trades, and the need to change the lens through which we view, discuss, and combat TOC.
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Transnational crime is business, and business is good.
Most of the organized criminal groups and networks engaged in transnational crime share many similarities with the companies found on the Fortune 500 list: they are overwhelmingly profit-motivated; they are always looking for a better way to do business; they closely follow and adopt technological advances; they employ the best of the best gatekeepers—lawyers, accountants, and company formation agents; they have benefited considerably from globalization and the greater connectivity between buyer and seller; they diversify into new markets and products. Of the few major differences that separate them, most glaring are the products they deal in, the methods they use to obtain goods and services, and/or the violence used to obtain and maintain a competitive advantage. For transnational crimes that also have legal trades, particularly environmental crimes, there is a strong overlap between legal and illegal actors with a fine line, often just a piece of paper, separating them.
Despite all of the similarities with business, transnational crime has frequently been viewed and combated through a moral lens that overlooks basic economic and business principles and treats organized crime groups and networks as unique actors. This approach will never produce meaningful results.