Elements of Customer Risk: Profiles and Relationships
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The document outlines the elements of customer risk pertaining to anti-money laundering (AML) compliance, emphasizing customer due diligence and the importance of accurately categorizing and measuring risk. It details various risk factors associated with individual and business clients, including their profiles, relationships, and transaction behaviors. Additionally, it provides case studies to illustrate potential risks and offers insights on how financial institutions can effectively manage customer risk profiles.
Elements of Customer Risk: Profiles and Relationships
- 1. https://www.alessa.caseware.com/ Elements of Customer Risk: Profiles and Relationships
- 2. https://www.alessa.caseware.com/ 2 Alessa: Integrated AML Compliance Solution Customer Due Diligence Transaction Monitoring/ Screening Regulatory Reporting Sanctions Screening AML Capabilities Data Management, Workflows, Case Management, Fraud Detection & Prevention (Advanced Analytics) Traditional FIs FinTechs Gaming and Casinos MSBs Markets Questions? Email us at alessa@caseware.com
- 3. https://www.alessa.caseware.com/ Agenda 3 1. What is risk, and why do we care about it? 2. Customer Due Diligence vs. CIP 3. Categorizing, quantifying and measuring customer risk 4. Profile and Relationships risk factors for individuals/consumers and businesses/legal entity clients 5. Relationships in context of customer risk 6. Key Takeaways and Q & A
- 4. https://www.alessa.caseware.com/ 4 What is risk? The intentional interaction with uncertainty Uncertainty is a potential, unpredictable, and uncontrollable outcome Risk is an aspect of action, taken despite uncertainty A subjective judgment made about the severity and probability of a risk Risk Perception: Risk:
- 5. https://www.alessa.caseware.com/ FinCEN CDD Rule: Customer Risk Profile Challenge for compliance professionals: Not so much WHY, but HOW? Certain elements of customer risk scoring only you can determine: • How you build your institution’s scoring model – which risk factors you choose, and if/how you assign weights to different factors • How you incorporate customer risk scores into your transaction monitoring software 5 Why a Customer Risk Score/Rating? “A financial institution should establish an understanding of the money laundering and terrorist financing risks of its customers.” Department of the Treasury, Financial Crimes Enforcement Network (2016)
- 6. https://www.alessa.caseware.com/ 6 Customer Due Diligence vs. CIP Customer Due Diligence is: Detailed analysis of a customer from a money laundering risk perspective Assessment of risk factors involving demographic data, products/services, anticipated transaction behavior, and geography May expand into enhanced due diligence Ongoing, continuously evolving over life of customer relationship CIP + CDD = KYC CIP is: Identity verification For new customers For beneficial owners of legal entity customers Government photo ID, address, date of birth for individuals OFAC screening One and done
- 7. https://www.alessa.caseware.com/ 7 Categorizing Risk Elements Profile & Relationships Products/ Services, Activities & Behaviors Geographic Risks Where Who What
- 8. https://www.alessa.caseware.com/ • Customer risk scoring model: Keep it simple • Need to quantify risk objectively, but be able to modify for judgement • Most models are way too complex • Will never be perfect 8 Quantifying and Measuring Risk Important: Risk scores should be dynamic
- 9. https://www.alessa.caseware.com/ Customer Profile and Relationship Risk Factors: Individuals/Consumer Clients
- 10. https://www.alessa.caseware.com/ 10 Risk Factors: Individual/Consumer Clients Risk Factor Why? Channel – online or third party Anonymity factor - collusion Depth & length of relationship Mitigating factor – longer/deeper is lower risk Employment status –Unemployed ask why Cash basis – placement risk; potential undocumented status Assets & sources of wealth Higher than expected for stated employment; unusual or irregular sources – red flags Citizenship status & residence Non-resident alien; potential money mule Politically Exposed Person (PEP) Higher risk of involvement in money laundering, bribery, corruption or terrorist financing Joint account – no familial relationship Red flag for potential fraud or funnel account Anticipated risky transaction activity Cross border transfers, frequent cash deposits are high risk indicators – risk of comingling, fraudSelf-employed
- 11. https://www.alessa.caseware.com/ 11 Individual/Consumer Clients: Case Study Mr. Talal Chahine: • Naturalized citizen, native of Lebanon • Prominent businessman, self-made • Founded a chain of restaurants in greater Detroit area • Highly respected in the community, family man • Deep customer relationship with his bank: personal and business accounts, commercial and personal loans, investment services Risky?
- 12. https://www.alessa.caseware.com/ • Four-year period: skimmed $20 million in cash proceeds from the restaurants • Maintained double set of computerized books – computer generated • Altered books artificially reduced amount of cash receipts • Employees converted millions of dollars in cash into cashier’s checks, sent to people in Lebanon • Employees converted cash from smaller to larger denominations – smuggled to Lebanon • Paid employees in cash • Strong ties to high-level leaders of Hezbollah terrorist organization • Currently a fugitive, believed to be in Lebanon • Wife pled guilty, served 18 months in prison 12 Individual/Consumer Clients: Case Study cont’d
- 13. https://www.alessa.caseware.com/ Profile/Relationships Risk Factors: Businesses/Legal Entity Customers
- 14. https://www.alessa.caseware.com/ 14 Business/Legal Entity Clients – ML Risk Risk Factor Lower Risk Higher Risk Ownership Transparent, easily verifiable Beneficial owners hidden behind trusts or layers of LLCs/other entities Entity legal structure Simple — sole proprietorship, general partnership, or publicly traded corporation Complex — less transparency, such as LLCs, trusts, joint ventures, limited partnerships Third party oversight Regulatory or licensing oversight required No independent oversight Cash Intensive No Yes Foreign business activities None Extensive, especially involving higher risk countries Length and depth of customer relationship Over 5 years; multiple accounts & services Less than 5 years; one or two accounts
- 15. https://www.alessa.caseware.com/ 15 Risk Factors: Business/Legal Entity Clients Risk Factor Lower Risk Higher Risk Ownership Transparent, easily verifiable Beneficial owners hidden behind trusts or layers of LLCs/other entities Entity legal structure Simple — sole proprietorship, general partnership, or publicly traded corporation Complex — less transparency, such as LLCs, trusts, joint ventures, holding companies, limited partnerships Third party oversight Regulatory or licensing oversight required No independent oversight • Less transparency/oversight = greater risk • Money laundering risk associated with certain entity types and related ownership structures is based on: • Ability to disguise human (beneficial) owners • Potential to hide actual business purpose and activities • Lack of external/internal oversight of business activities
- 16. https://www.alessa.caseware.com/ Nominee incorporation services (NIS) firms • AKA corporate formation agents • Can legally form a business entity in any state • Provides Resident Agent, mail forwarding, and “corporate office service packages” - gives a shell company the illusion of legitimacy • Establishes “nominee” officers, directors, stockholders, or bank signatories - hides true owners’ identities from public records 16 Red Flags – Ownership/Legal Structure
- 17. https://www.alessa.caseware.com/ Domicile location - higher risk: • Not domiciled where business operations located • Domicile state known to promote anonymity: Delaware, Wyoming, Nevada • Physical address: nominee incorp service? • Off-shore domicile 17 Red Flags – Ownership/Legal Structure cont’d
- 18. https://www.alessa.caseware.com/ Cash Intensive Risks • Ability to easily comingle dirty cash with legitimate receipts • Large cash deposits are routine – may be exempt from CTR reporting • Examples: 18 Cash Intensive Businesses: Risks Risk Factor Lower Risk Higher Risk Cash Intensive No Yes Convenience store Car wash Nail/hair salon Restaurant Private ATM operator Tavern/bar/nightclub Marijuana dispensary Thrift/retail store Liquor store Parking lot/garage Money service business Vending company Pawnbroker
- 19. https://www.alessa.caseware.com/ Cross border activity • Export/import businesses: foreign payments typical, especially wire transfer • Involves frequent transportation of goods across southwest US border – land or air • Money service business in southwest border region – Casas de Cambio 19 Foreign Business Activities: Risks Risk Factor Lower Risk Higher Risk Foreign business activities None Extensive, especially involving higher risk countries
- 20. https://www.alessa.caseware.com/ Consider that: Money laundering: Introduces criminal $$ into legitimate/respectable business Uses techniques developed for legitimate business purposes Uses service providers: attorneys, accountants, financial advisors The more profitable organized crime becomes, more important to shift profits into legitimate activities Conclusion: “Family owned and operated” respectability now a red flag Closely-held entity with few or no controls/oversight Money laundering & fraud increasingly committed through: Legit businesses with strong reputations Traditional or well-respected industries In perceived “safe” rural/small urban areas 20 The “Respectability Factor” and Customer ML Risk The perfect hiding places for illegal activities?
- 21. https://www.alessa.caseware.com/ 21 Business/Legal Entity Clients: Case Study CATT International Inc. • Yuma, Arizona • Husband and wife team with two other employees • Cattle broker: arranges for live cattle to be driven from Chihuahua, Mexico into the US. Chihuahua: • Just south of New Mexico/Texas • Largest cattle producing state in Mexico • Major center of the illicit Mexican drug trade • Ciudad Juarez: heavy drug cartel violence; political/law enforcement corruption
- 22. https://www.alessa.caseware.com/ 22 Business/Legal Entity Clients: Case Study #2 Business model: • Individuals in Mexico paid a per-head fee to drive herds into US • Payments: $10,000 to $20,000 per person • US dollar wire transfers through Mexican casas de cambio • Report gross income of $20 million + annually What makes this small, “family owned” business a high-risk customer? • Massive cattle herds - convenient vehicle for drug smuggling? • Business dealings primarily with unidentifiable Mexican individuals • Large payments through Mexican casas de cambio • High-intensity drug trafficking region
- 23. https://www.alessa.caseware.com/ Length of customer relationship to the institution: risk mitigator • Established pattern of normal activity • 5 years is a common threshold Individuals: Two or more unrelated individuals are owners or authorized signers • Possible funnel account • Potential indicator of human trafficking or elder abuse 23 Customer Relationships and Risk
- 24. https://www.alessa.caseware.com/ 24 Customer Relationships and Risk cont’d Businesses: • Look for hidden connections: Bob Smith Logistics LLC Salon Pro LLC NuChem LLC Magic Nails LLC Speedy Cleaners LLC LoDo Trucking Inc 100% 100% 100% Customers: Not Customers: Not a Customer: • Foreign subsidiaries, parent or affiliates – in what countries
- 25. https://www.alessa.caseware.com/ • Keep the customer risk scoring model as simple as possible • DOCUMENT the how/why of your model • Educate front line staff • Ensure customer information and resulting risk factors are regularly updated • Customer risk profiles: continuously evolving • Address change • Ownership change (business) • New foreign payment sources/destinations • Changes in behavior • SAR filing 25 Concluding Comments
- 26. https://www.alessa.caseware.com/ • Use technology built into your AML systems – machine learning • No one risk factor exists in a vacuum • Risk profile has limited value unless consider customer behavior as well 26 Concluding Comments
- 27. https://www.alessa.caseware.com/ Elements of Customer Risk: Profiles and Relationships