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Risk based approach

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Presentation on the risk based approach during ACOA Seminar organised by the Aruban Compliance Officers' Assocation (ACOA) on August 22, 2012.

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Risk based approach

  1. 1. RISK BASED APPROACH Pierre Simon, Managing Director Simon Legal & Compliance ACOA Seminar August 22, 2012
  2. 2. I. AML Compliance: Elements of success II. Assessment of Risk - Four Measures - Analysis III. Due Diligence and Monitoring Controls - Customer Risk Rating - Risk Rating Methodology - What can Financials Institutions Do? IV. Customer Risk Rating Model - Customers with a Pre-defined Risk Rating - All Other Customers Copyright © 2012 Simon Legal & Compliance. All rights reserved. TOPICS 2
  3. 3. I.AML COMPLIANCE
  4. 4. Financial Institutions need to address several aspects of AML to mitigate regulatory and reputational risks 4 AML COMPLIANCE: ELEMENTS OF SUCCESS Copyright © 2012 Simon Legal & Compliance. All rights reserved.
  5. 5. II.ASSESSMENT OF RISK
  6. 6. Institutions typically identify, measure and consider four main risk measures when assessing the quantity of AML risk. 6 ASSESSMENT OF RISK: FOUR MEASURES Copyright © 2012 Simon Legal & Compliance. All rights reserved.
  7. 7. 7 ASSESSMENT OF RISK: FOUR MEASURES Copyright © 2012 Simon Legal & Compliance. All rights reserved.
  8. 8. A well-developed risk assessment can enable a financial institution to assess and apply appropriate controls to mitigate the risks. Below is an approach for conducting an AML risk assessment. 8 ASSESSMENT OF RISK: ANALYSIS Copyright © 2012 Simon Legal & Compliance. All rights reserved.
  9. 9. III. DUE DILIGENCE AND MONITORING CONTROLS
  10. 10. Primary purpose: to identify the population of higher risk customers and to further design/modify existing due diligence processes, monitoring procedures and business process flows to address the risk associated with the customers of different risk levels :  Enhanced Due Diligence: – Varying EDD procedures/standards to be applied to customers of different risk levels  Enhanced Transaction Monitoring: – Leveraging risk ranking in monitoring of customer activities helps develop an effective transaction monitoring as well as STR filing program • Adjusted monitoring thresholds • A low risk client would be permitted to deviate more from its range of normal/expected activity than would a high risk client  Modified Business Process Flows: – Varying levels of new account opening procedures dependent upon initial risk assessment of client – Strengthened approval/signoff requirements for new accounts opened for high risk customers – Increased KYC verification requirements for high risk customers DUE DILIGENCE CONTROLS: CUSTOMER RISK RATING 10 Copyright © 2012 Simon Legal & Compliance. All rights reserved.
  11. 11. In the optimal theoretical setting, all relevant KYC and transactional information would be available and utilized during the risk rating process. Under this assumption of a perfect information set, the following indicators would be considered to identify risk in each category: 1. Customer Demographic Risk - evaluate demographic attributes to indicate higher AML risk. 2. Product/Transaction Risk – Banking products and transaction types vary significantly in the level of AML risk they represent. Categorizing the products and services offered helps identify those that posing higher AML risk. 3. Geographic Risk – Geographic risk is captured primarily at the country level when transactions originate or terminate in countries that have been linked to certain types of money laundering/terrorist financing behavior. As part of risk rating, evaluate AML risk of customers based on associated jurisdictions. DUE DILIGENCE CONTROLS: RISK RATING METHODOLOGY 11 Copyright © 2012 Simon Legal & Compliance. All rights reserved.
  12. 12. 1. Customer Demographic Risk - evaluate demographic attributes to indicate higher AML risk DUE DILIGENCE CONTROLS: RISK RATING METHODOLOGY 12 Risk Indicator Example Higher Risk Customer Types • Higher Risk Industries - foreign financial institutions; non-bank financial institutions (MSBs, casinos, brokers/dealers in securities, and dealers in precious metals, stones or jewels); off-shore corporations; deposit brokers; cash intensive businesses (convenience stores, restaurants, retail stores, liquor stores, cigarette distributors, privately-owned ATMs, vending machine operators, and parking garages), non-governmental organizations & charities; asset management • Higher Risk Occupations - student, unemployed, professional service providers (attorneys, accountants, doctors, real estate brokers) • PEPs (Politically Exposed Persons) and senior foreign political figures • Foreign individuals Customer’s Investigative History • STR Suspect • Judicial Foreclosures • Court Rulings Account Maturity • Client relationship < 1 year Copyright © 2012 Simon Legal & Compliance. All rights reserved.
  13. 13. 2. Product/Transaction Risk – Banking products and transaction types vary significantly in the level of AML risk they represent. Categorizing the products and services offered helps identify those that posing higher AML risk. DUE DILIGENCE CONTROLS: RISK RATING METHODOLOGY 13 Risk Indicator Example Transaction Types • International Wire Transfers - Customers that exceed the 90th percentile of number and/or aggregate florin or dollar value of international wire transactions within their peer group (e.g., individual, small business, and large business accounts) • High Cash Users - Customers that exceed the 90th percentile of number and/or aggregate florin or dollar value of cash transactions within their peer group (e.g., individual, small business, and large business accounts). Alternatively, can be based on the number of currency reports filed • Other higher-risk transaction types including internet banking, transactions in which the primary beneficiary or counterparty is undisclosed, transactions involving large amounts of monetary instruments, and certain types of electronic transactions. All present risk due to the anonymity they provide Product Types • Large number of different product types held by a customer. Allows for movement of funds and complex transactional patterns • Private Banking – can pose higher AML risk because of the variety, complexity, geographic scope, and high florin or dollar value of many transactions typically taking place through these accounts under especially high privacy and confidentiality circumstances; also, greater customer service can increase risk • Other higher-risk banking functions incl. offshore international activity, deposit-taking facilities, pouch activity (as opposed to domestic courier), and international correspondent banking Copyright © 2012 Simon Legal & Compliance. All rights reserved.
  14. 14. 3. Geographic Risk – Geographic risk is captured primarily at the country level when transactions originate or terminate in countries that have been linked to certain types of money laundering /terrorist financing behavior. As part of risk rating, evaluate AML risk of customers based on associated jurisdictions . * High risk jurisdictions can include jurisdictions on the following lists: – Sanction Listed Countries (e.g., EU, UN, OFAC) – FATF Non-cooperative Countries and Territories – Countries at Risk of Sponsoring Terrorism or Financing Terrorism – Offshore Financial Centers DUE DILIGENCE CONTROLS: RISK RATING METHODOLOGY 14 Risk Indicator Example High Risk Jurisdictions * • Customer’s location – customers located in high-risk jurisdictions pose a higher AML risk • Customers engaging in a significant level of transactions to/from high risk jurisdictions Copyright © 2012 Simon Legal & Compliance. All rights reserved.
  15. 15.  Comprehensive enterprise-wide account monitoring systems enable the bank to detect unusual and potentially suspicious activity that may indicate the need for additional internal money laundering investigations. Alerts may include tax avoidance schemes.  Alerts on transaction patterns or events that exceed statistical thresholds within pre-defined scenarios. The systems typically utilize temporal analysis to evaluate transactions over multiple dimensions of time.  High risk customer surveillance groups may be identified, sourced, and monitored in parallel with the transaction monitoring system.  Alerts generated by the systems are typically clustered with other intelligence data and reviewed by a bank’s Financial Intelligence Unit (“FIU”) or MOT- coordinator. The mission is to bring a focused and proactive approach to the operational aspects of financial crimes deterrence, detection, and reporting. The result can be an enterprise view of risk from across the organization. MONITORING CONTROLS: WHAT CAN FINANCIAL INSTITUTIONS DO? 15 Copyright © 2012 Simon Legal & Compliance. All rights reserved.
  16. 16.  Optimize transaction monitoring program.  Develop a high risk customer surveillance program.  Aspects of tax evasion can potentially be detected by modifying triggers within the Aruban bank’s wire structuring scenario. Most people typically associate structuring with cash deposits; however, this logic is commonly modified to apply to wire transfer activity in high risk customer populations, such as for private banking clients. Intelligence data should flow from across the organization potentially resulting in a STR. MONITORING CONTROLS: WHAT CAN FINANCIAL INSTITUTIONS DO? 16 Copyright © 2012 Simon Legal & Compliance. All rights reserved.
  17. 17. IV. CUSTOMER RISK RATING MODEL
  18. 18. Our customer risk model is based on:  Customers with a predefined low or high risk rating  A risk rating (low, medium or high) for all other customers based on jurisdiction, industry & sector and nature of company (entity type).  Potential adjustment of the risk rating (at least one level up) or rejection of the customer based on material adverse information. CUSTOMER RISK RATING MODEL 18 Copyright © 2012 Simon Legal & Compliance. All rights reserved.
  19. 19. The model is shown in the table below and explained in the next sheets. CUSTOMER RISK RATING MODEL 19 Adjustment for material adverse information Predefined risk rating: Low or High Risk rating based on: - Jurisdiction - Industry and sector - Nature of company (entity type) Copyright © 2012 Simon Legal & Compliance. All rights reserved.
  20. 20. CUSTOMER RISK RATING MODEL: CUSTOMERS WITH A PREDEFINED RISK RATING 20 There are certain types of (prospective) customers who from a customer integrity perspective represent a lower inherent risk or higher inherent risk. Pre-defined and high risk customers are set forth below: The following customer types automatically qualify as low risk:  A supervised financial institution in a low risk jurisdiction.  A publicly traded company in a low risk jurisdiction which is listed on a recognized exchange. This includes all direct and indirect wholly- owned subsidiaries of such a publicly traded company, provided that such a subsidiary is located in a low risk jurisdiction.  A supervised agent or intermediary in a low risk jurisdiction.  Government departments, agencies or local authorities in a low risk jurisdiction. Copyright © 2012 Simon Legal & Compliance. All rights reserved.
  21. 21. CUSTOMER RISK RATING MODEL: CUSTOMERS WITH A PREDEFINED RISK RATING 21 The following customer types automatically qualify as high risk:  A customer that has issued bearer shares. Bearer shares pose a high risk because the ownership of these shares may change without any registration or notification which makes it difficult to identify the ultimate beneficial owner(s). In addition the companies that issue bearer shares are frequently incorporated in high risk jurisdictions. Therefore customers with bearer shares should be classified as high risk. Copyright © 2012 Simon Legal & Compliance. All rights reserved.
  22. 22. For customers that do not qualify as pre-defined low risk as described in previous sheet a risk score is calculated based on AML risk associated with the following 3 main risk areas: CUSTOMER RISK RATING MODEL: ALL OTHER CUSTOMERS CDD Risk Rating 3. Entity Type 1. Country Risk Rating 2. Industries and sectors 22 Copyright © 2012 Simon Legal & Compliance. All rights reserved.
  23. 23.  Each category is rated low (L), medium (M) or high (H) according to how the customers jurisdiction, entity type and industry and sector falls within a pre- defined set of rules.  Within the calculation model every category has the same weight. By simple counting the times that the outcome is low, medium or high, the CDD risk rating will be determined. CUSTOMER RISK RATING MODEL: ALL OTHER CUSTOMERS 23 Copyright © 2012 Simon Legal & Compliance. All rights reserved.
  24. 24. The table below shows all possible combinations of category scores and the corresponding CDD risk rating. Example: Category jurisdiction is rated high, category industry and sector is rated low, category entity is rated medium. So result is 1 high, 1 medium and 1 low. Based on the table above the conclusion is an initial risk rating of medium. CUSTOMER RISK RATING MODEL: ALL OTHER CUSTOMERS 24 Factor risk rankings (Jurisdiction, Industry and Sector and Entity Type): the number of occurrences over all 3 categories Customer risk classification HIGH MEDIUM LOW 3x - - High 3x 1x - High 3x - 1x High 1x 2x - High 1x - 2x Medium 1x 1x 1x Medium - 2x 1x Medium - 1x 2x Low - - 3x Low Copyright © 2012 Simon Legal & Compliance. All rights reserved.
  25. 25. QUESTIONS 25 Copyright © 2012 Simon Legal & Compliance. All rights reserved.
  26. 26. Pierre A. Simon Managing Director, Anti -Money Laundering Consulting Simon Legal & Complianc e Phone: +31 (0)20 - 7 9 9 7955 pierre @si mon l e gal .nl WTC H -Tower Zuidplein 36 1077 XV Amsterda m Pi er r e i s mana g in g di r e ct or at Si mo n L e gal & C o mp lian c e and h as l e d co m pl e x, glo b al AM L p roj e c t s a t va ri e ty o f finan ci al in st it uti on s. Pr e viou sly , Pi e rr e se r ved a s S e n io r Du e D ili g en c e A d vi so r fo r a la r g e Du t ch b an k . Prio r t o tha t, h e wa s a B u sin e ss Ana lyst AM L in th e Glob al D u e Dili g e n c e Mana g e m e nt g ro up o f a la r g e fina nc ial i nstit ut ion where amongst others he helped set up a complet ely n ew CDD departmen t . H e b e ga n hi s ca r e e r i n 1 9 9 7 at th e A ruba n Poli c e F or c e and no w ha s a p rof e ssi onal back g rou nd a s a p ol ic e of fi c e r , busin e ss analy st an d sen io r A ML co mp lian c e co nsul tan t f or o ve r 1 5 y e ar s. H e stu d i ed D ut ch La w at th e V U Un ive r si ty A mst e rda m a nd ha s gai n ed mo st of hi s pro f e ssional e x p e ri en c e wi thin lar g e Eu ro pea n o r gani za tio ns such a s Euro n e xt , Rabo bank , Euro cl e ar a nd Fo r ti s Ba nk’ s G lobal S e cu rit i e s an d Finan c in g Gr ou p and i s th e foun d er of Si mo n L e gal & C o mp lian c e . Pi e rr e find s hi s ad de d va lu e e sp e cial ly in c hall e n g e s e n vol vin g p oli cy d e vel op m e nt & impleme nta tio n s and project managem en t within financial institutions . THANK YOU 26 Copyright © 2012 Simon Legal & Compliance. All rights reserved.

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