Financial Crime World

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Anti-Money Laundering/Combating the Financing of Terrorism (AML/CFT) Risks in Cambodia

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Introduction

This report assesses the AML/CFT risks in various sectors in Cambodia, including financial institutions, designated non-financial businesses and professions (DNFBPs), and terrorism financing.

Financial Institutions

Overview of Financial Institutions in Cambodia

  • There are 6 mobile payment services providers, 3 money remittance operators, 8 licensed money changers, and 2,010 authorized money changers.
  • Pawnshops have 284 legal companies/firms, and leasing companies have 9 leasing companies.
  • The operations of these institutions are generally conducted face-to-face, with some operating domestically and internationally.

Vulnerability Level of Financial Institutions

  • The vulnerability level of financial institutions is rated as Medium Low due to size, operation, and laws and regulations requirements.

Designated Non-Financial Businesses and Professions (DNFBPs)

Overview of DNFBPs in Cambodia

  • DNFBPs assessed include real estate agents, dealers of precious metals and stones, accountants, lawyers, and trust and company service providers.

Risk Assessment of DNFBPs

Real Estate Sector

  • Rated at Medium risk due to the growth of population, regionalization, and global market influence.
  • Has contributed 17.5% to GDP in 2015 with approximately USD 1,674,842,300.

Casino Sector

  • Rated at Medium level due to the liberalization of trade and services.

Financial Trust Sector

  • Rated at Low risk due to the legal frameworks and supervision by MEF.

Terrorism Financing

Government Efforts in Combating Terrorism Financing

  • The Government of Cambodia has been providing trainings and showing determination in combating terrorism and terrorist financing.
  • The harmonizing policy of the government has allowed for full integration of all minority groups (ethnic and religious).

Conclusion

  • The overall vulnerability level of other financial institutions is assessed as Medium Low, while the degree of ML vulnerabilities in the financial trust sector is Low.