making the most of sanctions and other watch lists · • different variations of the same...
TRANSCRIPT
Making the Most of
Sanctions and Other Watch Lists
Agenda and Course Material
1. What intelligence is available?
• Different kinds of lists
• How they can be used
3. How to search it
• Sources of variation in names
• Linguistic matching
• Defining requirements
2. How to manage it
• Available formats
• UN Intelligence Data Project
What Kind of Watch Lists are
Available?
Types of Watch List
Sanctions Lists Law Enforcement
Other Watch
Lists
Public
Intelligence
Internal
Intelligence
1. Sanctions Lists • Many different issuers
– UN > Supranational > National
• Targeted Sanctions
– Terrorists
– Corrupt / Violent Regimes
– War Criminals
– Organised Crime
• Country-based Programs
– Cities, Towns
– Ports, Ships
– Controlled entities
Consequences of breach
• Can be severe
– Financial penalties
– Loss of licences
– Ongoing compliance costs
• Deliberate vs Unintentional Breach
– Payment stripping
• Not Just FS firms
– Any material support
– Reputational Damage
Ac Closed IL Listing
• Claim by victims of pre-2003 attacks
– Should have been aware of Israeli Listing
– KYC Requirements
– Key business partners also listed
Founded
1994 1998
OFAC
2007
UK Charities Commission Investigations
2009 1996 2003
Charges Filed
2006
Extra-territorial impact
2. Law Enforcement Lists
• International Criminal Tribunals
– International Criminal Court
– UN Tribunals (ICTY, ICTR, SCSL)
• Interpol
– Red Notices: issued at request of national bodies
• National Most Wanted Lists
– National Police Forces
– Border Agencies
– National Crime Agencies (DEA, ATF, etc)
• Lists Issued by Regional Forces
Interpol Red Notices
Stephen Mark Lecorgne (UK: 18/12/79)
Jiri Vymetal
(CZ: 26/4/48)
Ione Lozano Miranda (ES: 28/10/86)
Jean Claude Mas Florent (FR: 24/5/39)
Chandima Anil Withanaarachchi(LK: 18/2/66)
Boris Berezovsky
(RU: 23/1/46)
Mark Paul Walker (UK: 4/9/66)
Christof Schneider (DE:11/2/73)
3. Other Official Watch Lists
• Regulatory Warnings
– Unauthorised Firms
– Known scams
• Enforcement Actions
– Penalties issued
– Bankruptcy proceedings
• Ethical Watch Lists
– Human Rights
– Environmental
4. Public Intelligence Lists
• PEPs
– Politically Exposed Parties
– Relatives and Close Associates
• State-owned entities
– FCPA / UKBA Compliance
– Sanctions Compliance
• Specific Interest Groups
– Victims lists
– Rich Lists
– Sporting Organisations, etc
5. Internal Intelligence Lists
• Black lists
– Previous fraud attempts
– Convicted criminals
• Watch lists
– Allegations in media
– Suspicious activity
• Case specific intelligence
– Local players
– Friends and family of suspect
Selecting Relevant Lists
10%
23%
55%
12%
List Maintenance
Technology
Analysis
Management
Cost of Intelligence Screening
• Average cost at a large FI - approx $14.5m p.a.
– Of which $8m is hit handling
Selection Strategy • Nature of process / investigation
– Reactive: narrower focus
– Proactive: broader requirements
– Volume and resources
• Third Party Requirements
– Regulators / industry bodies / key business partners
• Quality of Lists
– Political motivations / detail provided / updates
• Response to True Hits
– Escalation / exception procedures
– Reporting requirements
– Data protection / secrecy issues
Exercise 1
Exercise 1
US OFAC SDN List Terrorists, organised crime, sanctioned regimes
Magnitsky List US list of RU officials involved in human rights abuses
Russian FFMS sanctions list Extremist activities and money laundering
Interpol Red Notices International Most Wanted Registry
HRW Forced Labour Parties allegedly involved in child or slave labour
Constantly Review • Current Lists
– Frequent updates – may need to test
• New Lists
– Industry News
– Current Events
Qadhafi, Al-Gaddafi, Al-Qadhafi, Al-Qadhafi, Elkaddafi,
El-Qaddafi, Gaddafi, Gadhafi, Ghadaffi, Ghathafi, Qaddafi
17 February 2011 – Libyan “Day of Rage”
25
Qadhafi Qadhafi Kadhafi Qadhafi
24 28 27 26 17
Managing An Intelligence
Database
10%
23%
55%
12%
List Maintenance
Technology
Analysis
Management
Cost of Intelligence Screening
• Internal list management estimated at $1.5m p.a
– 10% of total cost in large financial institution
PDF Format Lists
XML Format Lists
Press Releases
Searchable Databases
Sourcing Intelligence Lists • Significant effort
– Poor formats of public information
– Frequent updates
– Error prone
– Consolidation
• Many choose to outsource
New Format for Intelligence
Watch Lists
UN Intelligence Data Project
• Multi-Party Cooperation
– UN lead, with EU / US / UK
– Wolfsberg Group, Swift
– With input from data vendors an search experts
• Dual Output
– Design of intelligence data model
– Design of XML format for list publication
• Data model already in use
– Proposed ISO standard
Aims of New Model
• Remove Ambiguity
– Relational nature of identity data
– Ensure no information loss between input and
output
• Facilitate Searching
– Accommodate international naming conventions
– Provide all information useful to modern
screening systems
• Promote Flexibility
– Minimise need for future revisions
Searching Identity Data
The Major Challenge
Good Matches Poor Matches
Recall
Relative proportion of
false negative results
Good Matches Poor Matches
Precision
Relative proportion of
false positive results
Hits Returned Not returned
Data being Searched
Recall / Precision Trade-Off
Exercise 2
New List Entries
1) Aleksandr Nikolayevich Yeltsin
– (Алекса́ндр Никола́евич Е́льцин)
– Russian, DOB: 1975
2) Muhammad ibn Abdul Azziz ibn Abdullah Faysal
– بن عبد هللا فیصل) (محمد بن عبد العزيز
– Yemeni, DOB 1964 / 1965 / 1966
3) Lee Young-sook (리영숙)
– N.Korea, DOB 1988
4) Maria del Carmen Rodriguez Lopez
– Spain, DOB 1973
Sources of Variation
Russian / Cyrillic
• Ельцин > Yeltsin (EN), Jelzin (DE), Ieltsine (FR)…
• Ельцин > Yelcin (ISO)…
Transcription Variants
• Different variations of the same non-Latin-script name
• Transcription standards have two parts – Script being transcribed
– Languages involved
• Many standards > very different variants – ISO standard may be very different from those used in practice
Japanese Transcription
• じゅんいち > Jun’ichi (Real Life), Zyun'iti (ISO)
Chinese / Kanji
• 張 > Zhang (Pinyin), Chang (WG), Cheong (HK) , Teo (SE Asia)
Arabic Transcription
• …Abd al Rahman < عبدالرحمن
• Abdul Rahman, Abdel Rachman…
• Abderrahmane, Abdurakhman, Abdorrahman…
Phonetic Similarities
• Differently written names which sound the same – depend on language / accent
• Discriminate between languages to avoid over matching
English Pronunciation
• White (EN) = Wight (EN) <> Wigit (EN)
• Stewart (EN) = Stuart (EN) <> Steart (EN)
French Pronunciation
• Baudaint (FR) = Bodins (FR) <> Bodine (FR)
English / French Pronunciation
• Roger = Rodger (EN)
• Roger = Roget (FR)
Multiple Name parts
• Abu Omar Muhammad al-Rashid ibn Faisal ibn Abdulazeez al-Tikriti
Naming Conventions
• Name parts can appear in different data fields
– Multiple name parts
– Standard 3 fields don’t fit all name types
– Transcription variants may end up split
• Synonyms
– Diminutives, organisation name parts, translations
Naming Conventions
• Donald Tsang Yam-kuen
Synonyms
• Robert = Robert and Rob and Robbie and Bob and Bobby…
• Ltd = Ltd and Limited…
• Bank = Bank and Banque and Banco…
• Milan = Mailand and Milano…
Typographic Errors
• Non-linguistic spelling variations – Character replacement
– Character omission
– Character addition
– Character transposition
Typos
• Transposition: Richards / Rihcards
• Replacement: Calderone / Calverone
• But: Wang <> Wong, Brown <> Crown
Matching Methods
String Comparison Algorithms
• Many different mathematical algorithms – Damerau-Levenshtein
– N-Grams
– Jaro-Winkler
– …
• Don’t deal with linguistic variation sources – Useful for typo handling
• Can try to refine – String length
– Graphical similarities / OCR errors
– Keyboard position
– Motor function
Generic Phonetic Algorithms
• Known for poor precision
– Poor recall often unrecognised
• Commonly used
– Soundex: very simple
– Metaphone: now largely superceded
– Double Metaphone: allows more than one alternative
• Major limitations
– Focus on US pronunciation / population
– Try to deal with all languages at the same time
– Don’t deal with transcription variants
Linguistic Search Methods • Based on research into:
– transcription
– phonetics
– cultural conventions
• Dictionary Approaches
– Will never be comprehensive
– Best for handling synonyms and translations
• Linguistic Rule Sets
– Use similarity keys like phonetic algorithms
– Cover transcription as well as phonetics
– Specific to each language
– Easier to adjust and configure
Implementing Your Search
• Market for search technology
– Complex area – many sales rep’s don’t understand
– Market popularity not a good indicator of quality
• Create your own search standard
– Look at each source of variation
– Determine what you want to match
– Create a set of principles
– May be different for different processes
• Evaluate commercial software
– Test thoroughly
