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3
Topics
• Screening trends & needs
• Increasing screening data accuracy
• Reducing false positives
• Screening international data
• Prioritizing highest potential risks
• Shortening review cycles
• Q&A
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Oracle Watchlist Screening: Selected Customers
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The 2nd Wave of Compliance
2002 - 2008 2009 - 2015
Transaction Modelling (TM)• Detect suspicious behaviour • Pattern recognition• Statistical modelling• Behavioural analysis• ££M costs
Transaction Screening (TS)• Message Parsing• Watch list filtering (basic)• ££M costs
Many failures:• Troubled/lengthy deployments • Missed Sanctions hits • False Positives +++• High acquisition & operational costs
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Leading the 2nd Wave
2002 - 2008 2009 - 2015
Customer Screening (CS)• Sanctions, PEPs, Risk screening• Vast quantities of customer data• Disparate systems, data structures, formats,
languages, alphabets• Breadth + depth of data analysis & search
capabilities
• Intelligent data optimization recognized as critical
• Advanced algorithms required for data variance, anomalies, data quality, transliteration and transcription
• Widespread recognition that greater accuracy = large reduction in false positives
• Compliance cost reduction• S-M-L: all sizes - all sectors
• not just for Tier 1’s
Transaction Modelling (TM)• Detect suspicious behaviour • Pattern recognition• Statistical modelling• Behavioural analysis• ££M costs
Transaction Screening (TS)• Message Parsing• Watch list filtering (basic)• ££M costs
Many failures:• Troubled/lengthy deployments • Missed Sanctions hits • False Positives +++• High acquisition & operational costs
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2nd Wave Requirements:
1. Maximum Operational Effectiveness
• False positives – dramatic reductions
• High accuracy
• Any data / anywhere
• Zero screening limitations (frequency, volumes, watch lists)
• Deploy anywhere
• Multi-lingual, multi-cultural environment
2. Optimum Cost Efficiency
• Risk Scoring, Case Management: reduces review (cycle) time
• Compliance workflow, case routing: speeds case workload
• Advanced language capabilities: reduces costs for international business
• Scales from a laptop to the Data Centre
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New markets...new challenges
POCA
FCPA
UK Bribery Act
Increasing Legislation, Regulation & Guidance
FATF JMLSG
USA PATRIOT Act
EAR
Customers
Partners
Suppliers Employees
Expanding Boundaries of Risk
PortsVessels
Contractors
Universal Risk Screening Requirements
EU 3rd MLD
BSA
Financial Services
Mobile Operators
Gambling
3PL/Trade ExportBroader Markets Facing Legislation
MSBsAuto Finance
Tobacco
Law Firms
OFAC
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Introducing Oracle Watchlist Screening
• What is it?
– A comprehensive risk and compliance screening application
– Chosen by over 160 customers globally
– Agnostic to data being screened
– Screens in batch and real-time
– Comprehensive reviewer and management tools
• How does it benefit you?
– Reduces the cost of meeting compliance obligations
– Reduces the chances of undetected risk sources
– Simplifies screening of international data
– Minimizes vendor dependency
– Makes it easier to demonstrate enhanced due diligence
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Accurate Data = Accurate Screening
1. ‘Overfilling’ of name data
2. Poor spelling of name and address information
3. Multiple names stored in a single field
4. Name information ‘misfielded’ into addresses
5. Date of Birth information in various formats
6. Entities and individuals mixed together
7. Non-standard name constructs
8. Poorly fielded address information
9. Non-standard country information
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Customer Data Preparation
Understand StandardiseStructure Re-structure EnrichDownload
ISOCountry
AliasTagging
Name Analytics
OccupationAnalytics
Dedupe
CountryFrom City
GenderAnalytics
YOB Inference
CountryInference
Phrase Profiling
EntityHints
Look ups
Spellings
MisusedFields
Split Records
LinguisticEquivalency
Phone No.Analytics
EmailAnalytics
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Simplifying international data screening
• New geographies – new risks
– PEPs and their associates
– Embargoed Countries
• Multiple writing systems in use
• Oracle Watchlist Screening
– Optional Language & Country Packs
– 45 languages & 57 countries
– Cyrillic
– Greek
– Chinese
– Arabic
– Hangul (Korean)
– Kanji, Hiragana and Katakana
(Japanese)
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Transliteration Example: Greek
• Mostly character level but with some complex rules
• Uses the standard EDQ Transliterator processor with the Greek
to Latin option, and a few simple additional rules (removing
‘Diacritics’ etc.):
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Name Variant Recognition Example: Russian
• Dictionaries are provided to recognize and
match different transliterations of the same
Russian name (that might exist on lists) >>>
• …and also Nicknames >
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Transcription Example: Arabic
• For Arabic, transliteration does not work
– e.g. محمد is transliterated by most methods to ‘mhmd’ but really represents ‘Muhammad’
• Direct transcription is required. This uses a dictionary which recognises more than 200,000 names, and over 5m transliterated variants of those names
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Prioritizing highest potential risks
• Risk Scores provide measures of relative risk of doing business with
individuals or entities
• Ensures priority is given to reviewing high risk individuals/entities
• Automates the closure of low confidence/low risk matches avoiding
unnecessary review work
• Ensures effective use of resources by prioritising work activity
• Reduces the burden maintaining PEPs whilst continuing to demonstrate
enhanced due diligence
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Externally calculated Risk Scores may be used – for example
Safe Banking Systems Risk Score
Original
Watchlist
record
SAFE EI risk
score
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Filters provide links
to investigators
work queue
Cases ranked in priority
order presenting highest
risk first
Shortcuts to
workflow MI
reporting
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Match rules tells us why this case has
been flagged as a potential match
Customer
Data
Watchlist
Data
Audit log and comment
capability provide a full
investigation history
Hyperlinks to Watchlist profile,
web search & other external
sources
Click to confirm match decision
and add comments
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Realtime screening of
individuals and entities
Match score and risk
score highlight degree of
risk
Link to Case Management for
fully audited and tracked
investigations