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Presentation on AML

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Title: Presentation on AML


1
Presentation on AML
  • 22-Nov-09

2
Agenda
  • Definition of AML
  • Process of Money Laundering
  • Extent of Problem
  • Impact of Problem
  • Key Features of AML System
  • AML Framework
  • Value Proposition

3
(No Transcript)
4
Money Laundering
  • Definition The process whereby the origin of
    funds generated by illegal means is concealed
  • Organized/Unorganized Crime
  • Drug trafficking
  • Corruption
  • Fraud
  • Terrorist Financing
  • 1000 1500 b / y

5
Financial Crime
  • Definition A violation of law committed by a
    person or group of persons in the course of an
    otherwise respected and legitimate occupation or
    business enterprise."  Coleman (1989)
  • Fraud Money Laundering

Money Laundering
Fraud
6
Money Laundering Process
  • Placement - Large volumes of small denominations
  • Layering - Moving funds to obscure paper trail
  • Integration - Reinvestment in legitimate business

7
Financial Impact
  • Money Laundering
  • Multimillion fines
  • Closing the Institution
  • Fraud
  • FBI gt 300 by USA
  • 5 -12 Insurance claims
  • Individual case gt 10 b
  • List of More fines

8
Impact on Reputation
9
Pressure on Financial Institutions
  • FATF Recommendations
  • EU AML Terrorist Financing Legislation
  • Bank Secrecy Act
  • Local AML Legislation (Notice 626)
  • USA Patriot Act
  • Sarbanes Oxley Act
  • Basel II

10
Addressing AML Requirements
  • Know Your Customer
  • Watch List Filtering
  • Risk Scoring
  • Transaction Monitoring
  • Link Analysis
  • Reports
  • Case Management

11
Know Your Customer
  • Due Diligence Check
  • Based on Account
  • Based on Customer Type
  • Define Mandatory Information Templates (To Define
    Compliance Level)
  • Identify Missing Mandatory Information (Measure
    Compliance Level)

12
KYC - Entity Scanning Filtration
  • Entity Scanning Filtration
  • Maintain internal Watchlist
  • Manage Blacklists
  • Storing watch lists/black lists/terrorist lists
    provided by regulatory authorities and also
    add/modify such lists
  • Facility to import/update blacklists and create
    unlimited internal watch lists
  • Entity Scanning Filtration features of KASTLE -
    AML- AML are designed for screening
    customers/counter-party against
    blacklists/watchlists
  • During static data (New Customer, Customer
    update) upload
  • During transaction (Ex- SWIFT Msgs.) upload
  • Name Search Matching
  • Two way list screening

13
KYC - The Name Identity Search Problem
14
Entity Scanning Filtration
White List
OFAC
Alert System
PEP
Watchlist
Customers
Black List
New Customers
AML Cell
Match Score
Blocked
gt X
Other Msgs
Name Extractor
Customer Update
lt X
No
Clean
Reports
Banking System
KASTLE - AML
15
Risk Categorization
  • Nature of Business
  • Product
  • Country / Geography
  • Customer Type
  • List
  • Mode of Operation
  • Source of Funds
  • Customer Occupation
  • Net worth
  • Account Status
  • Credit Rating
  • Account Risk Categorization
  • Low
  • Medium
  • High
  • Extreme

16
Risk Categorization
  • If Customer A is a Retail Merchandiser who is an
    Indonesian National, has a corporate account
    offering wire transfer facilities and is the son
    of a top politician.
  •  Retail Merchandising is classified as extreme
    risk business by the bank, Indonesian is a low
    risk geographic location, Corporate Account is
    classified as extreme risk product by the bank,
    since he is a Watch Listed entity by virtue of
    being a politically exposed person and Watch
    Listed entities are classified as extreme risk
    list by the bank.
  • The account of Customer A is categorized as
    follows
  • The calculated risk of the customer is 3.74 and
    the account of Customer A is categorized in to
    Extreme risk

17
Transaction Monitoring
  • Set the Benchmarks
  • Default Benchmarks
  • Branch group account group
  • Customer type
  • Nature of Business
  • Account risk rating
  • Country code
  • System Generated Benchmarks (Entity Profiling)
  • Specific Benchmarks (Establish Entity Profile)
  • Identify Normal Behavior
  • Set Alert Parameters
  • Alerts
  • Real-time (Patterns)
  • Non Real-time (Scenarios)
  • Subjective

18
Alert Management Facility
  • Allocation of Alerts to different analysts
  • Alerts can be pre-assigned or assigned post alert
    trigger
  • Monitor action taken on alerts
  • Record of any action taken on an alert is
    maintained.
  • An action can constitute any/all of the
    following
  • Alert assignment
  • Marking a false positive
  • Making observations/comments
  • Case investigation

19
Pooling of alerts
  • Provision to pool alerts branch wise/region
    wise/circle wise/bank wise/nature of transaction
    wise etc.
  • Filters allow to view alerts
  • Branch wise
  • Customer wise
  • for a specific alert type, instrument,
    transaction, etc.
  • View available on alerts branch wise/region
    wise/circle wise and for the entire bank

20
Link Analysis
  • The system has Link analysis feature to provide
    linkage of suspicious transaction flows
  • Identify Links
  • Static Data Duplication
  • Transactional
  • Listed Entities
  • Establish Links
  • Transactional List Match
  • Group Accounts
  • Monitor groups

21
Reports
  • CTR as per regulatory format
  • STR as per regulatory format (Reporting to STRO)
  • Other pre-defined Reports
  • User-defined Reports

22
Case Management Schematic
Top Management
Final Decision istaken Case Is Closed
Chief Compliance Officer (CCA)
CCA assigns Alert/Case to Officer
  • Customizable Work Flow
  • Support VOIP
  • Interface with FIU /Central Bank
  • Investigative Reports

Investigator investigates attach evidence
Decision MakersMakes Decisionwith Evidence
ReviewerReviews attach Evidence
23
KASTLE - AML Framework
KASTLE - AML
CONSULTING
Reports
AML FRAME WORK
ENTITYRESOLUTION
CASE MANAGEMENT
TRANSACTION MONITORING
BUSINESS INTELLIGENCE
Fraud Detection
COMPLIANCE
24
Thank You
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