Hasse Poulsson Business Solution Manager SAS Institute Copyright 2004, SAS Institute Inc. All rights reserved.

Transkript

2 Anti-Money Laundering Solution Fordele ved teknologi til AML-compliance Teknologi er kun en del af løsningen Finansielle virksomheder skal have en komplet strategi på plads til at opfylde AML-reglerne Risiko-baseret tilgang til AML Udvikle og dokumentere strategien Uddanne medarbejdere til at implementere strategien Anvende teknologi til at understøtte implementering af strategien Copyright 2004, SAS Institute Inc. All rights reserved. 2

3 Anti-Money Laundering Solution Fordele ved teknologi til AML-compliance AML-teknologiens mål: Hjælpe finansielle virksomheder med at opfylde lokale AMLregler Øge finansielle virksomheders viden om deres kunder med henblik på at identificere mistænkelige transaktioner/ aktiviteter og bekræfte mistænkelig adfærd Levere et komplet kundebillede Understøtte risiko-baseret tilgang til kundeovervågning og - efterforskning Minimere antallet af falske alarmer og effektivisere efterforskningen Understøtte realtids interaktiv efterforskning af advarsler til hurtigt at identificere mistænkelige aktiviteter Understøtte rapportering af bekræftede mistænkelige aktiviteter til myndighederne Copyright 2004, SAS Institute Inc. All rights reserved. 3

4 Anti-Money Laundering Solution Process of AML Investigation All Activities Alert System High-Risk Activities Suspicious Activities Financial Institution Feedback Reporting Confirmed ML Case Additional Intelligence Regulators Copyright 2004, SAS Institute Inc. All rights reserved. 4

5 Anti-Money Laundering Solution Process Optimization in Financial Institutions All Activities High-Risk Activities Suspicious Activities Alert System Financial Institution Manual Automated Monitoring Transaction Transaction and and Behavior Monitoring Behavior Monitoring Decisioning Decisioning Reporting Analyze Measure Copyright 2004, SAS Institute Inc. All rights reserved. 5

6 Component Architecture Data Management Data Store Alert Engine Investigation Profiles Transactions Backend Automatic Monitoring Scenario Management System Improvement Administration Feedback Discovery Real-Time Investigation Copyright 2004, SAS Institute Inc. All rights reserved st Qtr 2nd Qtr 3rd Qtr 4th Qtr Regulatory reports

7 Data Sources SAS Anti-Money Laundering Solution Data Models Core Model Alert System Investigation System Regulatory Regulators SAR/STR/CTR Raw transaction data Customer information Relationships Entity levels Several months Knowledge Center Audit Trail Reports Stores data of investigative process Hold audit trail of investigation for required period (5 years) Historical data for reporting and improvement Discovery st Qtr 2nd Qtr 3rd Qtr 4th Qtr Copyright 2004, SAS Institute Inc. All rights reserved. 7

8 Component Architecture Data Management Data Store Alert Engine Investigation Profiles Transactions Regulatory reports New scenarios Administration Feedback Discovery 1st Qtr 2nd Qtr 3rd Qtr 4th Qtr Copyright 2004, SAS Institute Inc. All rights reserved. 8

9 Monitoring Approaches RULES Set up rules to filter suspicious transactions Examples: Amount > $20,000 AND country in hotlist = Suitable for KNOWN patterns HYBRID Combination of All existing approaches PROFILING & PEER GROUPING Build statistical profiles of behavior Examples: Mean, standard, deviation, quartiles, distributions = Suitable for UNKNOWN patterns ADVANCED ANALYTICS Knowledge discovery in databases, decision trees and machine learning Examples: Nearest Neigbours Fuzzy logic Link analysis = Suitable for COMPLEX patterns Copyright 2004, SAS Institute Inc. All rights reserved. 9

10 SAS Anti-Money Laundering Solution Monitoring Approach kendte mønstre Scenarier og risikofaktorer til at overvåge kundeadfærd Scenarier og risikofaktorer er mønstre som repræsenterer en situation, som kan være tegn på hvidvask, og når de sammenstilles, kan de begge levere en beskrivelse af adfærden til efterforskerne Scenarier beskriver mindre almindelig og mere mistænkelig - adfærd, og når de sammenstilles, genererer de advarsler Risikofaktorer beskriver mere almindelig, mindre mistænkelig adfærd, og i stedet for at generere advarsler, leverer de, når de sammenstilles, risikoscoren for en enhed som også matcher et scenarie Copyright 2004, SAS Institute Inc. All rights reserved. 10

11 SAS Anti-Money Laundering Solution Monitoring Approach ukendte mønstre Profilering spore historik om adfærd Dynamiske adfærdsprofiler signaturer Varsel om afvigelse fra definerede normer Regelmæssig opdatering Angivelse af normalitets -områder Copyright 2004, SAS Institute Inc. All rights reserved. 11

12 Monitoring Approach avanceret analyse Customers in close proximity to a known Money Launderer Nearest Neighbor Search Exception Report, Scenario, Rule, or Sentinel Risk Factor & Risk Factor Combinations Known Money Launderer or Terrorist Near-Neighbors Copyright 2004, SAS Institute Inc. All rights reserved. 12

13 SAS Anti-Money Launderin g Solution Alert Engine scenarier og risikofaktorer Scenarie og risikofaktor bibliotek er inkluderet Kategorier Transaktionsscenarier Overvågning af transaktioner for et emne i datoorden Historik er ikke nødvendig Adfærdsscenarier Tage historik om emnets adfærd over tid i betragtning Overvåge liste scenarier Checke eksterne og interne lister SAS er vært for et konsortium med kunder for at udveksle scenarier Copyright 2004, SAS Institute Inc. All rights reserved. 13

14 SAS Anti-Money Laundering Solution Alert Engine scenarier og risikofaktorer Scenarier er regulerbare rammer med afgrænsede regler Segmenteringsregler Definere hvilke transaktioner eller kunder som skal overvåges efter specifikt mønster Adfærdsregler Definere grænser for adfærd uden for normen for specifikt segment og specifikt mønster Risikoregler Definere risikoen for et specifik adfærdsmønster for et specifikt segment Copyright 2004, SAS Institute Inc. All rights reserved. 14

15 Risk-based Monitoring Approach Risk-based Customer Segmentation Segment-based Scenario / Risk Factor Selection Segment-based Risk Ranking Integrated Alert Investigation Alert System Medium Risk Alert System Low Risk Alert System High Risk Copyright 2004, SAS Institute Inc. All rights reserved. 15

16 Prioritering, spærring og routing Prioritering Avanceret analyse ved at anvende Bayesian Classifier Spærring Spærring baseret på enhed (konto) for hvert scenarie i en specificeret periode Udarbejde hvide lister på enheds-basis Advarsels-routing Route til specifikke efterforskere Route til grupper Route baseret på advarselsegenskaber Copyright 2004, SAS Institute Inc. All rights reserved. 16

17 Component Architecture Data Management Alert Engine Investigation Data Store Profiles ransactions Regulatory Reports New scenarios Administration Feedback Discovery 1st Qtr 2nd Qtr 3rd Qtr 4th Qtr Copyright 2004, SAS Institute Inc. All rights reserved. 17

19 Component Architecture Data Management Data Store Alert Engine Investigation Profiles Transactions Regulatory Reports New scenarios Administration Feedback Discovery 1st Qtr 2nd Qtr 3rd Qtr 4th Qtr Copyright 2004, SAS Institute Inc. All rights reserved. 19

20 Discovery Component Effektivisere grundlæggende og dybtgående analyse Ad hoc forespørgsel I just read about a Money Laundering Scheme in WSJ and I want to see if any of our accounts is doing similar activities. Analysere systemeffektivitet What is the impact on the investigation workload and number of false positives of different scenario parameter settings? Generere nye rapporter We just received new requirements from our regulators to provide reports on specific transactions on a regular basis Copyright 2004, SAS Institute Inc. All rights reserved. 20

21 Component Architecture Data Management Data Store Alert Engine Investigation Profiles Transactions Regulatory Reports New scenarios Administration Feedback Discovery 1st Qtr 2nd Qtr 3rd Qtr 4th Qtr Copyright 2004, SAS Institute Inc. All rights reserved. 21

22 Scenarie administration Finindstille undersystemer gennem tilpasning til regelparametre Systemeffektivitet Routing konfiguration Opfylde revisionskrav Copyright 2004, SAS Institute Inc. All rights reserved. 22

23 Solution Key Differentiators End-to-end løsning til at understøtte hele AML-processen for at gøre den finansielle virksomhed compliant Muligheder for at bygge omfattende AML-datalager Mere end kun transaktionsovervågning den enkelte transaktions karakteristika skal sammenholdes med andre data (kundeoplysninger, historik, ekstern information) Avanceret adfærdsovervågning og risikoscoring Hybrid tilgang til avanceret overvågning af kundeadfærd Score hver undtagelse i relation til den risiko, som kunden udgør Afdække skjulte forbindelser mellem efterfølgende transaktioner, forskellige konti Solidt beslutningsgrundlag Efterforskningsgrænseflade som er let at bruge og stiller informationer til rådighed på rette tid og sted til at rapportere mistænkelig kundeadfærd Integration til SAS Banking Intelligence Solution Copyright 2004, SAS Institute Inc. All rights reserved. 23

24 SAS Industry Framework Banking Market Risk Fraud Credit Risk Segmentation & Profiling Profitability Analysis Retention & Acquisition Anti-Money Laundering Cross-Sell/ Up-Sell Operational Risk Campaign Mgmt. Regulatory Compliance Cash Mgmt. & ATM Optimization Consolidation & Reporting Workforce Mgmt. & Planning Budgeting & Planning Activity Based Management Scorecarding & KPIs IT Management Copyright 2004, SAS Institute Inc. All rights reserved. 24

26 Data Quality Name: Bob Beckett Address : 392 South Street Address :?????, Retail Banking NY Account #: Cards Investment Name: R. Beckett Address : 392 South Main Address : Black Sayville, Lists NY Policy # : H SH-011 Name: R. E. Beckett Address : S. Main St., Unit 392 Address : Sayville, NY Account #: S AML Platform Name: Rob Beckett Address : 392 S. Main Dr. Address : Sayville, NY Mortgage ID : S12 Can you recognize a customer across lines of business and key business functions? Copyright 2004, SAS Institute Inc. All rights reserved. 26

28 Systemeffektivitet 10 Deposits $10,000 Aggregate Deposits De udvalgte scenarier for en virksomhed skal addressere de identificerede risici i en formel risikovurderingsproces Eferforskningens arbejdsbelastning skal relateres til alvoren af de identificerede risici i risikovurderingen Copyright 2004, SAS Institute Inc. All rights reserved. 28