National Money Laundering and Terrorism Financing Risk Assessment 2017

National Money Laundering (ML) & Terrorism Financing (TF) Risk Assessment (NRA) 2017

Agenda  Overview of National Risk Assessment  Results of Threat/Crime & Terrorism Financing Assessment  Results of Sectoral Assessment  Results of Non-Profit Organisation Assessment  Post NRA 2017 2

National Risk Assessment – Why? 3 International Standards Malaysia National Risk Assessment  Conducted on a 3-year cycle - effective system in identifying, assessing and understanding ML/TF risks for the country  Foundation for robust risk-based national strategies and policies to combat ML/TF risk • Coordinated actions and efficient allocation of resources among domestic stakeholders • Enhancement of risk based approach across public and private sectors FATF Recommendation 1  Identify, assess, and understand the ML and TF risks for the country, and should take action, including designating an authority or mechanism to coordinate actions to assess risks, and apply resources, aimed at ensuring the risks are mitigated effectively.  Apply a Risk Based Approach to ensure that measures to prevent or mitigate ML and TF are commensurate with risks identified.  Require FIs and DNFBPs to identify, assess and take effective action to mitigate their ML and TF risks. FATF Immediate Outcome 1  ML and TF risks are understood and, where appropriate, actions coordinated domestically to combat ML and the financing of terrorism and proliferation.

Overview of Assessment Scope & Methodology Non-Profit Organisation Data Points I. Domestic Threat (ML) II. Foreign Threat (ML) III. Terrorism Financing Threat Case Studies Independent Reports Statistical Data Perception Surveys Expert Views Threats Risk Assessment Sectoral Risk Assessment I. Financial Sector II. Non-Financial Sector III. Legal Persons & Arrangements Interconnection between threat and sectoral vulnerabilities Labuan Offshore Risk (by Labuan FSA) Proliferation financing (Iran, North Korea) Results : Net Risk after considering effectiveness of control measures Scope Ongoing 2018 initiatives 4

Threat (Crime), Terrorism & Terrorism Financing Risk Assessment Results 5 Control Effective Measures Ineffective Increasing Inherent Risk Net Risk High Medium High Medium Low 21 Serious Crimes + T & TF Control effectiveness is relative to the inherent risk : higher risk requires greater control measures

Weak  Onshore Money Brokers*  Insurance Intermediaries*  Labuan Capital Market*  Labuan Money Brokers (TF)  Other Financial Services Providers*  Labuan Money Brokers (ML)  Jewelers (TF)  Jewelers (ML) Marginal  Labuan Insurers*  Labuan Banks*  Estate Agents (TF)  Cosecs (TF)  Trust Companies (TF)  Labuan Trust Companies (TF)  Lawyers (TF)  Accountants (TF)  E-Money and Non￾Bank Cards*  Non-Bank Financial Institutions*  Estate Agents (ML)  Cosecs (ML)  Trust Companies (ML)  Labuan Trust Companies (ML)  Lawyers (ML)  Accountants (ML) Acceptable  Gaming Outlets (TF)  Insurers*  Capital Market (TF)  Gaming Outlets (ML)  Banks (TF)  Capital Market (ML)  Money Services*  Banks (ML) Strong  Casino (TF)  Casino (ML) Low Medium Medium High High Sectoral risk assessment results: Net ML & TF Risk Rating

• Both ML & TF Control Measures Inherent Risk 6 Net Risk Low Medium Medium High High

NPO Assessment Results 2,040 367 31 0 1,000 2,000 3,000 4,000 LFSA (As at 2016) BHEUU (As at 2014) SSM (As at 2016) ROS (As at 2015) 60,286 (95.5%) (0.58%) (0.05%) (3.8%) Number of NPOs according to regulators Risk Focus: Sub-sectors and Characteristic Possible usage of NPO for TF purposes (based on Suspicious Transaction Report (STR) information) • Donations from public to NPOs • Cash courier • Fund transfer • Possible funding individuals to conflict zone • Funds were transferred to various individuals RAISING MOVING USING Total No. of NPOs: 62,724 Charity Fraternal Others Assets Religious Cultural Educational % of GDP Population 31.3 million 17,614 2,877 292 RM34 bil 11,957 544 29,331 3.1% Classification No. of NPOs Risk Ratings Sub-sectors Religious • Worshippers Society • Management Committee 9,035 MH MH M Charity • Members Welfare • Societal Welfare 9,075 M MH M Sub-sets Characteristics • Received TF intelligence • High cash intensity in asset • High cash transaction • Have operations in HiRA • Have transactions with HRA 10 2,924 3,545 26 42 7 Malaysia NPO Landscape HRA : High Risk Area

8 High Risk Crimes, Terrorism & Terrorism Financing

High Risk Crime - Fraud 9 Inherent Risk (High) Control Effectiveness (Marginal) Ranked 1st of 21 serious crimes Ranked 1st of 21 serious crimes. However, not commensurate with high inherent risk  Ranked either 1st or 2nd in 11 out of 13 risk indicators involving:  Investigations  STRs  Foreign threats Main driving factors  Ranked either 1st or 2nd in 10 out of 14 AML indicators involving:  Enforcement actions  Prosecutions  Judiciary  Perceived to be relatively ineffective in combating the crime (10th)  International nature of fraud cases – challenges for domestics and cross jurisdiction coordination  Illegal financial scams operators exploit gap in enforcement – various legislations overseen by different law enforcers  Abuse of financial systems – rampant use of bank accounts and mule account holders in committing fraud and laundering of proceeds Observations

High Risk Crime - Smuggling 10 Inherent Risk (High) Control Effectiveness (Marginal) Ranked 2nd of 21 serious crimes Ranked 5th of 21 serious crimes.  High investigation:  3 rd in both number and amount involved in cases  Large amount involved in STRs reported by RIs (2nd)  Perceived to be high risk (4th), high connection with other crimes (3rd) and foreign threat (3rd) Main driving factors  High ML enforcement actions:  5 th in amount involved in ML cases  6 th in ML investigation  High ML prosecution actions (4th)  Perceived to be relatively ineffective (11th)  Common items being smuggled:  Into Malaysia – consumables & electronic goods, alcohol, tobacco, mobile phones, firecrackers, rice  Out of Malaysia – electronic products, rubber tyres  Mostly perpetrated by crime syndicates – abused the long and porous border & possibly assisted by complicit officials Observations

High Risk Crime - Corruption 11 Inherent Risk (High) Control Effectiveness (Marginal) Ranked 3rd of 21 serious crimes Ranked 4th of 21 serious crimes.  High investigation:  6 th in number and 5 th in amount involved in cases  High STRs reported by RIs  4 th in number and 5th in amount involved  Perceived to be the highest risk crime & most connected with other crimes Main driving factors  High ML enforcement actions:  1 st in amount seized & 3rd in amount frozen  2 nd in amount involved in ML cases  5 th in ML investigation  High ML prosecution actions (2nd)  Perceived to be 2nd most ineffective  Offenders of corruption crime (2014-2017) : proportional ratio between public officials (48%) and civilians (52%)  2014 – 2016 : Approximately 50% of arrested civil servant below 40 year-old  Weakening perception of corruption in the country – Transparency International : 2014 (51st), 2015 (54th), 2016 (55th), 2017 (62nd) Observations

High Risk Crime – Illicit Drug Trafficking 12 Inherent Risk (Medium High) Control Effectiveness (Weak) Ranked 4nd of 21 serious crimes Ranked 8th of 21 serious crimes.  High amount involved in cases investigated (6th)  Perceived to be high risk (5th) and foreign threat (1st) Main driving factors  High ML investigation (1st)  Absence of ML prosecution and conviction  Perceived to be most effective  Geographical location of Malaysia - foreign source of drugs transiting into and/or from the country  Expanding drugs market in Malaysia – number of new users detected daily: 2016 (64), 2017 (49)  Perpetrated by domestic or international organised crime syndicates Observations

High Risk Crime – Organised Crime 13 Inherent Risk (Medium High) Control Effectiveness (Marginal) Ranked 7th of 21 serious crimes Ranked 7th of 21 serious crimes.  Relatively high investigations (5th) and amount involved in STRs (7th) Main driving factors  High ML enforcement actions:  4 th in ML investigations  2 nd in IP with freezing & 6th in amount frozen Net risk qualitatively raised from Medium High to High due to: • Most of the serious crimes are perpetrated by organised crime groups. • Lower data indicators which do not reflect actual risk level due to enforcement actions taken against individuals within an organized crime syndicate for their corresponding predicate crimes instead of the relevant regulation on organized crimes.  Main challenges faced in combating the crime:  Enforcement scope limited by definition of law: Serious offence of organised crime = offence punishable by imprisonment of 10 years or above (international standard is 4 years)  Complicity of public officials : case of senior police officers offering protecting racket to crime groups  Fear instilled in law enforcers : burning of property/vehicles, shootings Observations

14 Inherent Risk (Medium High) Control Effectiveness (Acceptable) •Porous land and sea border enable transiting of value and terrorists between Malaysia and neighboring countries. •Large and potentially sympathetic Muslim population •Increased IS threat due to affiliation of Malaysia’s militants with the Salafi Jihadi/Wahhabi ideology Main driving factors  Intense enforcement by PDRM’s Special Branch  Success in preventing terrorist attacks and dismantling terrorist groups • No evidence of terrorist financing being linked to extortion, robbery, smuggling, fraud or drugs • Pew Research Centre : 11% Malaysian show favourable attitude towards IS (Lebanon 1%, Jordan 3%, Palestinian 6%, Turkey 5%, Indonesia 9%). • 95-98% of Malaysians recruited via social media and online messaging apps. • Malaysian response to the ideological threat posed by jihadist-Salafism has not been as equally vigorous or successful as its operational responses. (The evolution of jihadist-Salafism in Indonesia, Malaysia and The Philippines, and its impact on security in Southeast Asia, 2016). Observations T & TF No. of IP (predicate) 76 No. of attempted attacks 15 Value of STRs RM643m No. of STR; No. of STR foreign 534 ; 80 No. of arrests 260 No. of designations 45 No. of IP (TF) 25 No. of prosecution 20 No. of conviction 6 T & TF Terrorism & Terrorism Financing – Medium High Risk

15 Main Sectors

Sectoral Summary Report: Banking Net TF Risk Medium High Net ML Risk High Inherent TF Risk Medium High Inherent ML Risk High Acceptable Control

1. Acceptable level of market entry control and procedures.
2. Acceptable level of RIs’ Internal Controls i.e. improved quality and quantity of STRs and minor gaps in compliance and risk management functions for some RIs Key Contributors (Controls): Observations:
3. Highest value of transactions (188 billion transactions amounting to RM356 quadrillion).
4. Highest cash transactions (737 million transaction valued at RM260 trillion).
5. Provides high risk products/ services (e.g. CASA, trade finance, IFT, foreign exchange).
6. Highest number of customers (72 million). Note: • Banking sector has the largest asset size (RM2.9 trillion) across all sectors • TF risk rated at Medium High due to lower score on ‘likelihood of TF occurring” compared to ML Key Contributors (Inherent Risk): Control Measures Conv FO A Islamic FO A Islamic LO A Conv LO A Investment A DFI A Int Islamic A Labuan Banks M Inherent Risk ML TF Conv LO H H Conv FO H MH Islamic LO H H Investment MH MH DFI MH MH Islamic FO M M Labuan Banks L L Int Islamic L L Net Risk ML TF Conv LO H H Conv FO H MH Islamic LO H H Investment MH MH DFI MH MH Islamic FO M M Labuan Banks M M Int Islamic L L Source: 2016 data from RIs, Supervisors and FIED Source: 2014 – 2016 data from Supervisors and FIED 16
7. Highest number and value involved in relation to both ML and TF investigations and prosecutions: • ML: Current and savings accounts most commonly frozen & seized in investigations. • TF: Noticeable increase in the usage of bank accounts to raise and move funds.
8. As at 2016, losses involving mule accounts = RM500 million (>13,500 cases investigated)
9. Associated with fraud, corruption, tax evasion, illicit drug trafficking, smuggling, and insider trading/market manipulation.

Sectoral Summary Report: Capital Market Intermediaries Net TF Risk Net ML Risk Medium High Inherent TF Risk Inherent ML Risk Acceptable Control

1. Acceptable level of market entry control and procedures.
2. Acceptable level of internal controls by RIs reflected by minor gaps in established AML/CFT compliance programme for some RIs in subsector Key Contributors (Controls): Observations:
3. All products offered by capital market intermediaries are assessed as higher ML/TF risk exposure.
4. Access to capital market products via non-face-to￾face channels i.e agents and electronic delivery channels increase ML / TF vulnerabilities
5. High number of transactions facilitated (82% of total transactions) by capital market intermediaries to both local and global clients.
6. Relatively high number of customers identified as higher ML risk; while TF risk is assessed as low. Key Contributors (Inherent Risk): Control Measures FMUTC A Stockbroking A Derivative Broking A Inherent Risk ML TF FMUTC MH M Stockbroking MH M Derivative Broking M M Net Risk ML TF FMUTC MH M Stockbroking MH M Derivative Broking M M Source: 2016 data from RIs, Supervisors and FIED Source: 2014 – 2016 data from Supervisors and FIED 17
7. ML threats generally lower than other financial sectors.
8. Mostly associated with insider trading/market manipulation and fraud. Isolated case of corruption proceeds laundered through stockbroking firm. Medium High Medium Medium FMUTC: Fund Management and Unit Trust Companies

Sectoral Summary Report: Insurance and Takaful Operators (ITO) Net TF Risk Medium Net ML Risk Medium Inherent TF Risk Medium Inherent ML Risk Medium Acceptable Control

1. Acceptable level of market entry control and procedures.
2. Acceptable level of RIs’ internal controls i.e. minor gaps in established AML/CFT compliance programme for some RIs in subsector.
3. Lower number of transactions as compared to banks at 102.2 mil. transactions amounting to RM91.48 billion.
4. Extensive local network i.e. highest number of agents at 215,552.
5. Lowest value of cash transactions at 12.3 million transactions amounting to RM4.4 billion;
6. Low number of higher risk customers (less than 1% of total customer).
7. High number of ML-related STRs reported on life and composite insurer, but low for other sub-sectors Control Measures Life A Comp Ins A Comp T A Family T A Gen ReT A Comp ReT A Gen Re A General A Life Re A Comp Re A Labuan ITO M Inherent Risk ML TF Life MH MH Family T M M Comp T M M Comp Ins M M Comp Re L L Comp ReT L L Labuan ITO L L Life Re L L General L M Gen Re L L Gen ReT L L Net Risk ML TF Life MH MH Family T M M Comp T M M Comp Ins M M Labuan ITO M M Comp Re L L Comp ReT L L Gen ReT L L Gen Re L L General L L Life Re L L Key Contributors (Controls): Observations: Key Contributors (Inherent Risk): Source: 2016 data from RIs, Supervisors and FIED Source: 2014 – 2016 data from Supervisors and FIED 18
8. Generally lower threat as compared with other financial sectors. • Mainly ML risks rather than TF risks.
9. Several cases of civil servants purchasing insurance policies using proceeds from corruption.
10. Also associated with fraud and tax evasion.

19 Sectoral Summary Report: Money Services Businesses Net TF Risk Medium High Net ML Risk Medium High Inherent TF Risk Medium High Inherent ML Risk Medium High Acceptable Control

1. Acceptable level of market entry control and procedures
2. RIs’ internal control assessed as Marginal i.e. reflected by major gaps in established AML/CFT compliance programme for most RIs in subsector i.e. Quality of STR
3. Approx 99% of its transactions are cash-based.
4. All products offered by MSB sectors are identified as high risk for ML and TF
5. At-risk local network is relatively high for ML and TF
6. Relatively high number and value of STRs reported on the sector: • ML (220): amounting to RM2,214 million • TF (1): amounting to RM254 million in ‘14
7. 2 incidences of TF investigations. Control Measures Remittance A Money Changing A MC&R, MC&R&W M MC&W M Inherent Risk ML TF Money Changing MH MH Remittance MH MH MC&R, MC&R&W MH MH MC&W M M Net Risk ML TF Money Changing MH MH Remittance MH MH MC&R, MC&R&W H H MC&W MH MH Key Contributors (Controls): Observations: Key Contributors (Inherent Risk): Source: 2016 data from RIs, Supervisors and FIED Source: 2014 – 2016 data from Supervisors and FIED
8. Some licensed MSB involved in illegal remittance activities.
9. Some delicensed MSB continued to carry on illegal remittance activities. • Facilitating cross border funds transfer related to fraud, tax and smuggling.
10. Investigations also revealed MSB being abused to transfer funds in TF activities.

Sectoral Summary Report: E Money, Non Bank Affiliated Charge & Credit Card Net TF Risk Medium High Net ML Risk Medium High Inherent TF Risk Medium Inherent ML Risk Medium Marginal Control

1. Marginal level of market entry control and procedures.
2. Marginal internal controls by RIs due to poor quality of STR reported by sector and major gaps in AML/CFT compliance programme for most of the RIs’ in subsector.
3. Types of products offered are identified as high risk for ML and TF
4. Products are offered through higher risk delivery channels via agents and electronic channels.
5. Less than 1% of customers in 2016 identified as higher risk (7,600 customers).
6. Relatively low number and value of STR reported on the sector: • ML: 31 STRs amounting to RM240 million • TF: None
7. 1 case of ML investigations; none for TF. Control Measures E-money (Large) M Non-bank Credit Card W Charge Card W E-money (Small) W Inherent Risk ML TF E-money (Large) MH MH Non-bank Credit Card M M Charge Card M M E-money (Small) M L Net Risk ML TF E-money (Large) H H Non-bank Credit Card H H Charge Card H H E-money (Small) H MH Key Contributors (Controls): Observations: Key Contributors (Inherent Risk): Source: 2016 data from RIs, Supervisors and FIED Source: 2014 – 2016 data from Supervisors and FIED 20
8. E-money accounts created using fictitious identification. • Used for criminal activities, e.g. selling counterfeit goods & pornographic materials.
9. Peer to peer fund transfer can be abused for ML & TF • Terrorist received funds transfer through e￾money account.

Sectoral Summary Report: Labuan Banking Net TF Risk Medium Net ML Risk Medium Inherent TF Risk Low Inherent ML Risk Low Marginal Control

1. Marginal level of market entry control and procedures
2. Marginal internal controls by RIs reflected by low number of STRs and major gaps in established AML/CFT compliance programme for most RIs in subsector. Despite having high product and delivery channel risks, inherent risks remain low due to: 1.Prohibition on cash transactions (LFSSA 2010) • Total transactions less than 1% of the Malaysian banking sector. 2.Low number of higher ML/TF risk customers • Less than 1% of Malaysian banking sector. 3.Low number of at-risk ML/TF global networks • 1% for ML; 5% for TF due to corresponding banking relationships in higher risk countries. 4.Low incidences of ML cases and none for TF. Control Measures Banks A L Conv Inv Bank M L Islamic Bank M Labuan Com Banks M L Islamic Inv Bank M Inherent Risk ML TF Banks H MH Labuan Com Banks M M L Islamic Inv Bank L Islamic Bank L Conv Inv Bank L L Net Risk ML TF Banks H MH Labuan Com Banks MH MH L Islamic Inv Bank M M L Islamic Bank M M L Conv Inv Bank M M Key Contributors (Controls): Observations: Key Contributors (Inherent Risk): Source: 2016 data from RIs, Supervisors and FIED Source: 2014 – 2016 data from Supervisors and FIED 21
3. Pose lower ML and TF risks compared with onshore counterparts, mainly due to • Low volume of transactions facilitated (< 1% of that for onshore banking sector) • Prohibition of cash transactions • Low occurrence of ML and TF activities
4. No TF threat observed during period under review.
5. Proceeds from fraud in several investigations flew through Labuan Banks.

Sectoral Summary Report: Dealers in Precious Metals & Stones Net TF Risk High Net ML Risk High Inherent TF Risk Medium Inherent ML Risk Medium High Weak Control

1. Weak level of market entry control and procedures.
2. Weak internal controls by RIs reflected by absence of STRs reported and significant gaps in established AML/CFT compliance programme for all RIs’ in subsector.
3. Unable to determine number of higher risk customers due to absence of data.
4. Higher risk products identified, i.e. gold and diamond are of high value, easily transferrable and non-traceable.
5. Large local presence with high number of firms at local higher risk areas (77%).
6. High number of STR reported on – 2 nd highest within the DNFBPs sector.
7. No STR reported on the sector involving TF. Control Measures DPMS W Inherent Risk ML TF DPMS MH M Net Risk ML TF DPMS H H Key Contributors (Controls): Observations: Key Contributors (Inherent Risk): Source: 2016 data from RIs, Supervisors and FIED Source: 2014 – 2016 data from Supervisors and FIED 22
8. Jewelleries are one of the most commonly seized or frozen assets in investigations, mainly fraud & illicit drug trafficking.
9. No TF activities associated with DPMS during the period under review. However, there was past case where sanctioned individual used gold products as collateral for loans.

Sectoral Summary Report: Casino Net TF Risk Low Net ML Risk Medium Inherent TF Risk Medium Inherent ML Risk Medium High Strong Control

1. Acceptable level of market entry control and procedures.
2. Acceptable internal control observed in Casino reflected by minor gaps in established AML/CFT compliance programme i.e. Quality of STR
3. Total cash transaction value made by casino account for 24% of total cash transactions value transacted by DNFBPs (2nd highest)
4. Higher risk delivery channels, i.e. use of agents (junkets from various jurisdictions) and offering of external advice electronically (provides anonymity to the sources of funds)
5. Higher risk products and services identified, i.e. 4 out of 16 products/ services
6. Higher risk customers account for 0.37% out of total customer.
7. No investigation / prosecution on casino
8. No STR reported on the casino for TF. Control Measures CASINO S Inherent Risk ML TF CASINO MH M Net Risk ML TF CASINO M L Key Contributors (Controls): Observations: Key Contributors (Inherent Risk): Source: 2016 data from RIs, Supervisors and FIED Source: 2014 – 2016 data from Supervisors and FIED 23
9. Limited case studies related to ML activities during the period under review.
10. Minimal likelihood of casino being abused for TF activities.
11. Junket operators utilised over 90% of higher risk facilities.

24 NPO Assessment

Observations – Inherent Risks (Perception Survey and SRA 2017 Data) 1 2 C 3 B A High number of accounts Very high number of NPO accounts across the banks may signal multiple accounts held, the possibility of inactive NPOs continues undertaking financial transactions Classification of HR Classification of high risk NPO includes, religious, charity, social/welfare Perception of Donation and NPO as vulnerable to TF abuse Conservative Risk Approach Banks are viewed to have conservative approach to classification of risks for NPO (14 out of 61 banks rated 100% of NPO as high risks) . SRA DATA *based on 722 response based on 61 banking institutions data PERCEPTION SURVEY 25 Overall – Medium High Rating Financial institutions generally view NPOs as high risk The perception of risks for other group of respondents are mixed *Other group of respondents: DNFBPs, LEAs, prosecutor, supervisors/regulators, judge/magistrate, others

Observation – Control Measures ADEQUACY OF LAWS STRENGTH OF MONITORING/SUPERVISON LEVEL OF COMPLIANCE EFFECTIVENESS OF ENFORCEMENT • Most international standards requirements met • Rectification of gaps from MER 2015 necessary • The need to comply with the new revision of Recommendation 8 of FATF Standards • No of supervisors over no of higher risk NPOs/ NPO population varies across regulators • No of onsite/ of site monitoring varies • Based on current no of supervisors, coverage on higher risk NPOs may have been met by certain regulator • Spectrum of annual compliance (50- 100%) • Level of enforcement actions vis-à-vis non compliance varies across regulators, depending on agencies’ approach 26

27 Post NRA – Recalibration of National Strategic Plan

28 Post NRA 2017 : Recalibration of NSP Legal Framework Include additional serious offences under the Act Centralised enforcement framework for serious crimes & assets management Exempt low risk sectors/product from AMLA regime Policy & Implementation Framework Review AML/CFT policies for reporting institutions Increase supervisory activities and monitoring of at risk sectors Enhance data collection and sharing Resources & Structure Joint enforcement for high risk crimes Enhance supervisory resources & tools Awareness & Training Develop AML/CFT certification programme Enhance engagement between supervisors and law enforcement officers Strategic awareness programmes Potential initiatives – examples

29 NRA & The Industry

30 Institution Level ML/TF Risk Robust Communication & Training Informed Business Decision Efficient Allocation of Resources Guided Policy & Procedures Formulation Products Markets Front liners Management Compliance Management Information System Business units Risk Management

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