AMLC approves Second National Risk Assessment Report
To further reinforce the Philippines’ anti-money laundering and combating the financing of terrorism (AML/CFT) regime, the Anti-Money Laundering Council (AMLC) approved the Second (2nd) National Risk Assessment (NRA) Report on Money Laundering and Terrorism Financing (ML/TF) on 20 December 2017.
In its Forty (40) Recommendations, the Financial Action Task Force (FATF) requires countries to identify, assess, and understand ML/TF risks, and to take action in mitigating those risks. FATF, an international standard-setting body, develops and promotes policies to protect the global financial system against money laundering, terrorist financing, and the financing of proliferation of weapons of mass destruction. The 40 FATF Recommendations set out a comprehensive framework of measures which countries should then implement.
As the country’s financial intelligence unit, the AMLC led the 2nd NRA, which covered the years 2015 and 2016. Participants included stakeholders from government and law enforcement agencies, and private sector institutions. The first assessment in 2016 covered 2011 to 2014.
The 2nd NRA evaluated the overall threat and effectiveness of the country’s AML/CFT mechanisms. ML/TF threats identified include proceeds-generating predicate offenses, such as drug trafficking, smuggling, violations of the Intellectual Property Law, environmental crimes, estafa, and plunder.
To further address the susceptibility of the banking, money service business, and casino sectors, policies were introduced. In 2017, the Bangko Sentral ng Pilipinas issued Circular No. 942, imposing stricter entry controls for MSBs. Similarly, on 14 July 2017, President Rodrigo Roa Duterte signed Republic Act No. 10927, designating casinos as covered persons under the Republic Act No. 9160 or the Anti-Money Laundering Act of 2001, as amended. The recently effected Casino Implementing Rules and Regulations as well as the guidelines to be issued in the implementation of the law are also expected to address the ML/TF vulnerabilities of the sector.
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