SAS Anti-Money Laundering Solution · Target marketing Segmentation & Profiling Human Resource Mgt Broker Surveillance Compliance Reporting Portal Cross-sell/up-sell Campaign Mgt

Copyright © 2004 SAS Institute Inc. All rights reserved.

SAS® Anti-Money Laundering SolutionSascha Schubert

SAS EMEA

Copyright © 2004, SAS Institute Inc. All rights reserved. 2

How can a Bank become AML compliant?

The Issue• Poorly drafted legislation, open to interpretation• Lack of strong leadership from regulator• AML is ‘all cost, no benefit’

The Temptation• Minimalistic compliance for as long as possible

The Risks• Reputation, reputation, reputation• Increased scrutiny• Personal liability• Financial Risk


Benefits of Technology for AML

Technology is only part of the picture

Financial organizations need to have complete strategy in place to comply with AML regulations• Risk-based approach to AML • Develop and document strategy• Train staff to implement strategy• Use technology to support the implementation of the

strategy


Benefits of Technology for AML

Objective of AML technology:• help financial organizations to comply with local AML

regulations• not to detect money laundering – but to know their

customers better to be able to detect unusual transactions / activity

• Risk-ranking unusual activity to help focus on highest risk

• Minimize false alarms for more efficient investigation• Support investigation of these unusual transactions • Support reporting of these unusual transactions to

regulators


Components of the SAS AML Solution

Discovery


Component ArchitectureData

ManagementAlert Engine Investigation

Transactions

DiscoveryAdministration

Profiles

Data Store

0102030405060708090

1st Qtr 2nd Qtr 3rd Qtr 4th Qtr

Regulatory reports

Feedback

Newscenarios


Data Management

Open Metadata-Driven Architecture

Robust Data Access Engines

Comprehensive Transformation Suite, Data Quality

Framework for executing production scenarios and creating alarms

Framework for scenario management

Logical & Physical Data Models

Customer &Account

Transactions

Product


Data Management – Data ModelsKnowledge

CenterAML CoreOperationalData

Transactional data

Customer Information

Watch Lists

Dimensional Model with Transaction History

and Customer Profiles

Alerts History, Audit Trail

and Metadata


Alert Engine

Administration

Data Management

Transactions

Investigation

Discovery

Profiles

Data Store

0102030405060708090


Regulatory reports

Feedback

Component Architecture

Newscenarios


Alert Engine - ScenariosScenario Library of 20 Business Scenarios

3 categories• Status scenarios

− Independent on transactions, rely on customer information such as address changes

• Transaction scenarios− Monitoring transactions for a subject in date order− no historical information needed

• Behavioral Scenarios− Consider historical behavior of subject over time

SAS hosts consortium with customers to share scenarios


Ranking, Suppression and RoutingRanking• Advanced Analytics

− Bayesian Classifier− Individual Profiling

Suppression• Suppress based on scenario for a specified duration• Suppress based on entity (e.g. account) by scenario for a

specified duration (driven by Investigative UI)

Initial Routing• Route to specific investigators• Route to groups


Data Management

Alert Engine Investigation

Administration

Transactions

Discovery

Profiles

Data Store

0102030405060708090


Regulatory

Reports

Feedback

Component Architecture

Newscenarios


Investigation Component

Web Based Reporting

Security• User and Group Level

Reports based on defined rules

Manage flow of Information

Capture Pertinent Information



Investigation System – Alert Details


Investigation Workflow

Global Suppress?

Do not display

Y

Report & Investigate

FalsePositive?

Y

Local Suppress?

Y

N

Report(SAR)

N

InitialAlert

NAlert

System

AML Knowledge Centre

Log Activity

Local Suppress

list

GlobalSuppress

List


Investigation Component


Workflow Engine – Process Definition


Discovery

Facilitate Basic and in-depth analysis

Ad-hoc query “I just read about a Money Laundering Scheme in WSJ and I want to see if any of our accounts is doing similar activities.”

Reduce False Positives “History has shown us that Accounts with these characteristics are clean, therefore, I don’t want to see them on an alert.”

Data Visualization


Component ArchitectureData

ManagementAlert Engine Investigation

Administration

Transactions

Discovery

Profiles

Data Store

0102030405060708090


Feedback

Newscenarios

Regulatory

Reports


Discovery

Facilitate Basic and in-depth analysis

Ad-hoc query “I just read about a Money Laundering Scheme in WSJ and I want to see if any of our accounts is doing similar activities.”

Reduce False Positives “History has shown us that Accounts with these characteristics are clean, therefore, I don’t want to see them on an alert.”

Data Visualization

Analysis of Textual Data


Administration

Data Management: ETL, metadata, storage

Security and Users: group hierarchy

Alerts: tuning, adding, weighting rules

Workflow: routing of alerts


Scenario Administration

Secure Infrastructure

Fine-tune subsystems by adapting rule parameters

System efficiency

Meet auditing requirements


Administration


SAS Key DifferentiatorsEnd-to-end solution to cover entire Intelligence process (IVC)

Capabilities to build comprehensive AML Warehouse • More than just transaction monitoring –need to link the

characteristics of the single transaction with other data (customer information, history, external information)

Advanced analytics• Uncover hidden relationships between subsequent transactions,

different accounts, different account holders• Monitor the performance of the system in terms of compliance and

accuracy

Information Dissemination• Use web services to make information available where and when

needed

Integration into larger Banking Intelligence Solution


Integrated Data Model

Corporate Performance Management

Market RiskCredit Risk

Operational Risk•Intrusion Detection

“Risk Mgt for Banking”(Basel II)

Anti-Money Laundering

Fraud • Kiting•Credit Card•Loans

Channel Mgt

ATM Forecasting/ Optimization

Branch/Web/ Call CenterMgt

Offer Optimization

Web Analysis

IT Mgt

Product/Channel analysis

Customer ProfitabilityLife time value

Credit Scoring Wealth Mgt

Target marketingSegmentation &

Profiling

Human Resource Mgt

Broker Surveillance

Compliance Reporting Portal

Cross-sell/up-sell

Campaign Mgt

Customer AcquisitionCustomer Retention

Asset/Liability Mgt.

OperationalCustomerRisk

•Credit Scoring

SAS Financial Service Intelligence

Financial Mgt


SAS AML Customers

Financial organizations in:

US

Canada

Europe

Middle East


SAS AML Customers - References

Bank of America, US

Morgan Stanley

Branch Banking & Trust, US

Unity Trust Bank, UK

http://www.unity.uk.com/index.cfm?itemid=642

http://www.bbandt.com/


SAS AML Customers – BB&T

"BB&T's reputation is built on … doing business with unwavering integrity. We take pride in being rated as one of the country's safest…. It is clear SAS supports that sentiment with their rock-solid reputation and financial stability, as well as a commitment to its customers -demonstrated through its high investment in research and development."

“Built on SAS' leading analytic and data management technology, SAS delivers an AML solution that is top of the line. After evaluating other vendor offerings, we chose SAS because of the solution's functionality, compatibility and the ability to customize the technical architecture."

Phil Koonce, Manager of operational risk at BB&T

Copyright © 2004, SAS Institute Inc. All rights reserved. 30Copyright © 2004, SAS Institute Inc. All rights reserved. 30

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SAS Anti-Money Laundering Solution · Target marketing Segmentation & Profiling Human Resource Mgt Broker Surveillance Compliance Reporting Portal Cross-sell/up-sell Campaign Mgt