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D O W J O N E S & A C A M S

G L O B A L A N T I - M O N E Y L A U N D E R I N G

S U R V E Y R E S U L T S 2 0 1 6

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ContentsContents & Infographic

Executive Summary

Survey Highlights

AML Challenges & Workloads

AML Data Providers

Client Screening

Beneficial Ownership & Sanctions Lists

De-Risking

Human Trafficking & Terrorism

Respondent Profiles

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3

4

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9

12

14

15

16

C L I E N T S C R E E N I N G [ P A G E 9 ]

P E P S C R E E N I N G [ P A G E 1 0 ]

~80%screen for domestic PEPs.

Among them, more than 90% also screen for local-level PEPs

83% report this as part of the KYC process and 70% use this as part of due

diligence – stable from previous years

V E R I F Y I N G B E N E F I C I A L O W N E R S H I P [ P A G E 1 2 ]

D E - R I S K I N G [ P A G E 1 4 ]

40% report their companies have

exited a full business line or segment in the

past 12 months due to regulatory risk

One-third of respondents are

planning and/or investigating

exiting a business line/segment in

the next 12 months

H U M A N T R A F F I C K I N G [ P A G E 1 5 ]

63%of respondents have modified AML training to incorporate smuggling red flags and typologies

58%of respondents have modified AML transaction monitoring

69%of respondents do one or both of the above

47% report that too many false-positive alerts hurt confidence in client-screening data accuracy

42% note that comprehensiveness of the data is important – a 10% increase from 2015

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Dow Jones Risk and Compliance, in conjunction with the Association of Certified Anti-Money Laundering Specialists (ACAMS), surveyed 812 respondents around the world to (1) assess the current regulatory environment, (2) deepen understanding of client-screening processes, content and systems and (3) explore emerging issues.

In 2016, the trend continues as Anti-Money Laundering (AML) professionals cite increased regulatory expectations and enforcement of current rules as their greatest challenge. This is followed by concerns regarding a shortage of trained staff. These challenges translate to increased personal workloads and comparable portions predict increases in department workloads in the coming year.

The regulations most responsible for increased workloads are FinCEN’s Proposed Beneficial Owner Rules, followed by FATCA, other tax evasion legislations and the Fourth EU Anti-Money Laundering Directive.

We invite you to delve into the Annual Survey to find out the latest views and practices on anti-money laundering.

We hope your compliance program benefits from the insights and opinions within this survey in 2016 and beyond. If you’d like to learn more, get in touch with our team at AMLsurvey@dowjones.com

T H E D O W J O N E S R I S K A N D C O M P L I A N C E T E A M

Executive Summary

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Survey Highlights

C L I E N T- S C R E E N I N G T E C H N O L O G Y90% of respondents work in companies with client-screening technology solutions in place, with implementation of Governance, Risk and Compliance (GRC) platforms steady at 45%. Among respondents from companies with client-screening technology solutions in place, cost issues and excessive false alerts – positive and/or negative – are the reasons that mostly prompt companies to review their solutions. Cost issues are more important in 2016 than in 2015.

B E N E F I C I A L O W N E R S H I P V E R I F I C AT I O N A N D S A N C T I O N S S C R E E N I N GAlmost one-half of firms limit their research into beneficial ownership to those with 25% or greater ownership, while slightly more than one-quarter do so for all ownership stakes of 10% or larger. The average number of sanctions or official lists used in client screening, as well as in payment filtering, saw a significant increase year-over-year. Respondents value having more complete and accurate list information over receiving list updates quicker, although nearly 90% of those surveyed expect those list updates to be available within 24 hours of their publication by regulators.

D E - R I S K I N G40% of respondents report their companies have exited a full business line or segment in the past 12 months due to regulatory risk. One-third of respondents are planning and/or investigating exiting a business line/segment in the next 12 months.

H U M A N T R A F F I C K I N G Nearly 70% of respondents report their organizations have modified AML training and/or transaction monitoring to incorporate human trafficking and smuggling red flags and typologies, while about the same proportion have taken similar steps with addressing ISIS terrorist financing and recruitment risks.

A M L C H A L L E N G E S A N D W O R K L O A D SIncreased regulatory expectations continue to represent the greatest AML compliance challenge, as cited by 60% of respondents, followed by concerns regarding shortages of trained staff. Formal regulatory criticism, future shortage of trained staff and outdated technology are mentioned more often in 2016 compared with 2015.

R E G U L AT I O N S I M P A C T I N G O R G A N I Z AT I O N W O R K L O A D

FinCEN’s Proposed Beneficial Owner Rules (new in 2016 survey) is cited by nearly 75% of respondents as contributing to increased workloads. FATCA, other tax evasion legislation and the Fourth EU Anti-Money Laundering Directive are the other regulations mentioned by more than half of the respondents as adding to workloads. FATCA, Dodd-Frank and Ukraine-related sanctions have less workload impact in 2016 compared to 2015.

D ATA A C C U R A C Y R E M A I N S M O S T I M P O R TA N TDecision makers continue to cite data accuracy as the single most important factor in choosing AML data providers. Well-structured data, depth of content, customer service, conforming to international standards and company reputation are also very important for 60% or more of decision makers.

Excessive false-positive alerts remain the key factor for hurting confidence in client-screening data providers. Concerns about comprehensiveness and lack of data coverage definitions increased in importance from 2015 to 2016.

P E P S C R E E N I N GAbout 80% of respondents screen for domestic PEPs; among them, more than 90% also screen for local-level PEPs. Local PEPs are usually included in client screenings in all countries, not only those with regulatory requirements.

2016 total results are compared to 2013 and 2015 to measure trends; statistically significant differences between 2015 and 2016 are noted with arrows.

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A M L C O M P L I A N C E C H A L L E N G E S F A C E D B Y O R G A N I Z AT I O N S60% of respondents cite increased regulatory expectations as the greater AML compliance challenge, followed by concerns regarding having enough properly trained staff. Formal regulatory criticism increases by 4% from 2015.

AML Challenges & Workloads

2013 2015 2016 M A I N C H A L L E N G E

Increased regulatory expectations & enforcement of current regulations

53% 62% 60% 28%

Having enough properly trained AML staff 36% 49% 50% 19%

Insufficient/outdated technology 31% 38% 41% 15%

Too many false positive screening results

31% 32% 36% 7%

Budget constraints & increased scrutiny of third-party reviews

27% 5%

Additional regulations 25% 26% 22% 3%

Understanding regulations outside home country

22% 23% 25% 4%

Sanctions compliance 24% 3%

Formal regulatory criticism 12% 15% 19% ↑ 5%

Fear of personal civil & criminal liability 15% 2%

Lack of senior management/BoD AML engagement

13% 17% 14% 5%

Understanding regulations in home country

10% 9% 9% 1%

A M L C O M P L I A N C E C H A L L E N G E S I N N E X T 1 2 M O N T H SIncreased regulatory expectations and enforcement of current rules continue to be the key future challenges for AML professionals. In addition, concerns about future shortages of trained staff and outdated technology are mentioned more often in 2016 than in 2015.

2013 2015 2016

Increased regulatory expectations & enforcement of current regulations

50% 58% 57%

Having enough properly trained AML staff 30% 40% 45% ↑

Additional regulations 37% 37% 40%

Insufficient/outdated technology 25% 31% 36% ↑

Budget constraints & increased scrutiny of third-party reviews

26%

Too many false positive screening results 21% 22% 25%

Sanctions compliance 20%

Understanding regulations outside home country

18% 16% 18%

Formal regulatory criticism 10% 13% 16%

Fear of personal civil & criminal liability 11%

Lack of senior management/BoD engagement

9% 12% 10%

Understanding regulations in home country

9% 8% 7%

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I M P A C T O F R E G U L AT I O N S O N O R G A N I Z AT I O N W O R K L O A DNearly 75% of the respondents cite FinCEN’s Proposed Beneficial Owner Rules as contributing to increased workloads. FATCA, other tax evasion legislation and the Fourth EU Anti-Money Laundering Directive are the other regulations mentioned by more than half of the respondents as adding to workloads.

R E G U L AT I O N W I T H M O S T I M P A C T O N O R G A N I Z AT I O N W O R K L O A DFinCEN’s Proposed Beneficial Owner Rules (new in 2016 survey) is cited by 20% of respondents as the regulation most responsible for increased workloads. The relative impact of FATCA, Dodd-Frank and Ukraine-related regulations decreases from 2015 to 2016. For 35% of respondents, none of these specific regulations represent a major impact on workloads.

Major increase in workload Minor increase in workload

35% 40% FinCEN ProposedBeneficial Owner Rules

26% 39% FATCA

14% 42% Other tax evasion legislation

15% 39% Fourth EU Anti-MoneyLaundering Directive

19% 34% Dodd-Frank

12% 34% Ukraine-related sanctions

11% 32% FinCEN Proposed Rulemakingto Investment Advisors

9% 33% FCPA

8% 30% UK Bribery Act

15% 8% Local regulation

16% Brazil Clean Companies Act

2013 2015 2016

FinCEN Proposed Beneficial Owner Rules 20%

FATCA 17% 17% 11%

Local regulation 7% 8% 9%

Dodd-Frank 22% 16% 8% ↓

Fourth EU Anti-Money Laundering Directive 2% 5% 5%

Ukraine-related sactions 6% 3% ↓

None will cause major increase 36% 39% 35%

2013 2015 2016

N/A N/A 74%

69% 72% 65% ↓

54% 52% 56%

42% 52% 54%

60% 59% 53% ↓

N/A 51% 46% ↓

N/A N/A 43%

45% 45% 42%

39% 38% 37%

20% 22% 23%

N/A 20% 19%

Major/Minor increase

in workload

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C O M P A N Y R I S K P O L I C I E S & O P E R AT I O N A L E F F E C T I V E N E S SAlthough the proportion decreases from 2015 to 2016, more than 80% of respondents continue to believe their companies’ risk policies and/or operations reflect a convergence of global compliance disciplines. As in previous years, about 80% report increased regulatory expectations for operational effectiveness in the past 12 months.

Completely agree

Somewhat agree

Neutral

Somewhat disagree

Increased

Stayed the same

Decreased

P O L I C I E S / O P E R AT I O N S R E F L E C T C O N V E R G E N C E O F C O M P L I A N C E D I S C I P L I N E S

C H A N G E I N R E G U L AT O R Y E X P E C TAT I O N S F O R O P E R AT I O N A L EFFEC TIVENES S IN PAS T 12 MONTHS

20% 20% 18%

79% 79% 81%

0%

20%

40%

60%

80%

100%

2013 2015 2016

5% 4% 7% 8% 6% 9%

40% 41% 40%

45% 47% 42%

0%

20%

40%

60%

80%

100%

2013 2015 2016

40%

C L I E N T- O N B O A R D I N G C H A N G E S D U E T O F AT C A R E Q U I R E M E N T SAs in 2015, more than 70% of respondents report their organizations have already made or are considering changes to client-onboarding processes due to FATCA requirements. Enhanced identity verification and standardized onboarding processes across BU’s remain the most mentioned changes. The proportion adding negative news checks increases from 2015 to 2016.

73% considering and/or have made changes

2013 2015 2016

Enhanced identify verification 35% 39% 39%

Standardizing onboarding processes across BU’s

27% 38% 39%

More stringent standards for accepting customers

23% 32% 30%

Enhanced watch list scans 22% 24% 27%

Adding PEP checks 17% 21% 25%

Increased search of public records 18% 22% 22%

Establishing enterprise-wide due diligence unit

14% 17% 20%

Adding negative news checks 12% 15% 20% ↑

Commissioning due diligence research 10% 12% 11%

None defined yet 41% 28% 27%

Completely/somewhat agree:85% 88% 82% ↓

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R E A S O N S F O R I N C R E A S E I N P E R S O N A L W O R K L O A D Rising regulatory expectations and increased areas of responsibility remain the strongest drivers of greater personal workloads. Formal examination criticism by regulators and merging with another organization have become more widely reported reasons for increased workloads in 2016.

A M O N G T H O S E R E P O R T I N G I N C R E A S E D P E R S O N A L W O R K L O A D S :

2013 2015 2016 M A I N R E A S O N

Rising regulatory expectations 61% 67% 68% 21%

Increased areas of responsibility 58% 55% 55% 21%

Increased AML focus by senior management

38% 44% 45% 12%

New or expanded government regulations

39% 37% 40% 8%

Growth of company 38% 37% 39% 9%

Formal examination criticism by regulators

15% 21% 30% ↑ 8%

Out-dated technology/processes 20% 27% 26% 5%

Expanding into new markets 22% 21% 24% 4%

Received regulatory fine or penalty 5% 9% 12% 4%

Merging with another organization 11% 6% 10% ↑ 2%

Layoffs in the organization 8% 5% 7% 1%

C H A N G E S I N P E R S O N A L & D E P A R T M E N T W O R K L O A D As in previous years, over three-quarters of AML professionals report increased personal workloads and comparable proportions predict further increases in department workloads in the coming year. Most others expect their workloads to remain at current levels.

C H A N G E I N P E R S O N A L W O R K L O A D I N P A S T 1 2 M O N T H S

E X P E C T E D C H A N G E I N D E P A R T M E N T W O R K L O A D I N N E X T 1 2 M O N T H S

Increased

Stayed the same

Decreased

Increased

Stayed the same

Decreased

21% 21% 21%

77% 77% 77%

0%

20%

40%

60%

80%

100%

2013 2015 2016

19% 20% 17%

79% 78% 81%

0%

20%

40%

60%

80%

100%

2013 2015 2016

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U S I N G A N D C O N S O L I D AT I N G M U LT I P L E A M L D ATA P R O V I D E R SComprehensiveness remains the most mentioned reason for using multiple data providers, followed by coverage of specialized risk categories. Nearly 50% of 2016 respondents in companies using multiple providers report their companies are considering consolidating to a single provider, up slightly (not significantly) from 2015.

AML Data Providers

K E Y F A C T O R S I N C H O O S I N G A M L D ATA P R O V I D E RDecision makers continue to cite data accuracy as the single most important factor in choosing AML data providers. Well-structured data, depth of content, customer service, conforming to international standards and company reputation are also very important for 60% or more of decision makers.

2013 2015 2016

Data accuracy 88% 89% 89%

Well-structured data 75% 74% 75%

Depth of content 65% 64% 65%

Customer Service/support 64% 63% 63%

Conforms to international standards 56% 57% 63% ↑

Company reputation 60%

Breadth of content 59% 56% 57%

SME/staff knowledge 53% 51% 51%

Price 50% 47% 51%

Data quality verified by third party 49% 48% 49%

Speed of implementation 53% 51% 48%

Technology independent 43% 42% 43%

Recommended by regulators/FIU’s 41% 42% 43%

Suite of products 43% 42% 42%

Used by similar organizations 29% 29% 32%

Local presence 22% 23% 24%

Existing vendor relationship 23% 21% 19%

2013 2015 2016

Comprehensiveness 51% 55% 57%

Specialized risk categories 36% 40% 42%

Result of legacy systems/contracts 25% 27% 31%

Decentralized AML structure regional requirements

16% 23% 19%

Risk of data provider outage 12% 13% 16%

Result of company acquisitions 10% 12% 10%

42% 44% 49%

0% 2013 2015 2016

20%

40%

60%

C O N S I D E R I N G C O N S O L I D AT I N G D ATA P R O V I D E R S[ A M O N G D E C I S I O N M A K E R S U S I N G M U LT I P L E D ATA P R O V I D E R S ]

R E A S O N S F O R U S I N G M U LT I P L E D ATA P R O V I D E R S[ A M O N G T H O S E U S I N G M U LT I P L E D ATA P R O V I D E R S ]

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Client Screening

W H Y N O T F U L LY C O N F I D E N T I N C L I E N T- S C R E E N I N G D ATA A C C U R A C Y Excessive false-positive alerts remain the key factor hurting confidence in client-screening data providers. Concerns about comprehensiveness and lack of data coverage definitions increases in importance from 2015 to 2016.

C O N F I D E N C E I N C L I E N T- S C R E E N I N G P R O V I D E R D ATA A C C U R A C Y About two-thirds of respondents who mainly focus on client screening remain extremely or very confident in the data accuracy of their primary data provider. Confidence levels have been steady in recent years.

2013 2015 2016

Too many false-positive alerts 37% 44% 47%

Comprehensiveness of the data 34% 32% 42% ↑

Name variations/transliterations 32% 41% 38%

Gaps in coverage/in certain regions 25% 27% 27%

Data structure 17% 24% 24%

Lack of data coverage definition 16% 13% 22% ↑

Too many false-negative alerts 19% 23% 22%

Integration 12% 18% 20%

Insufficient breadth of coverage 23% 24% 19%

Timeliness 14% 17% 14%

Not enough crime types covered 9% 13% 12%

A M O N G T H O S E F A M I L I A R W I T H C L I E N T S C R E E N I N G A N D N O T “ E X T R E M E LY ” O R “ V E R Y ” C O N F I D E N T I N D ATA A C C U R A C Y

A M O N G T H O S E W I T H C L I E N T S C R E E N I N G A S A M A I N F U N C T I O N

Extremely confident

Very confident

Somewhat confident

Not confident

Extremely/very confident

2013: 67%2015: 67%2016: 65%

2% 2% 2%

31% 33% 32%

51% 52% 55%

16% 13% 10%

0%

20%

40%

60%

80%

100%

2013 2015 2016

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T E S T I N G C L I E N T- S C R E E N I N G D ATA Q U A L I T YAbout 90% of respondents report that their companies test the quality of data from their client-screening data providers, including almost half who conduct quality checks monthly or more often.

S C R E E N I N G F O R D O M E S T I C P E P SAbout 80% of respondents work in organizations that screen for domestic PEPs in the client-screening process.

S C R E E N I N G F O R L O C A L - L E V E L P E P S More than 90% of respondents in organizations that screen for domestic PEPs report that their companies also screen for local-level PEPs. Local PEPs are usually included in client screening in all countries, not only those with regulatory requirements.

R E A S O N S F O R N O T R E V I E W I N G C L I E N T- S C R E E N I N G D ATA Q U A L I T YRespondents in companies that don’t review client-screening data quality mainly cite lack of resources, trust in their vendors and not knowing how to test data as the reasons – or claim it is simply not their responsibility.

A M O N G T H O S E W I T H C L I E N T S C R E E N I N G A S A M A I N F U N C T I O N

A M O N G O R G A N I Z AT I O N S S C R E E N I N G F O R D O M E S T I C P E P S

2015 2016

No resources 17% 29%

Trust my vendor 18% 27%

Don’t know how 19% 24%

Not my responsibility 33% 22%

No time 11% 10%

Budget constraints 7% 7%

Not important 0% 7%

A M O N G T H O S E F A M I L I A R W I T H C L I E N T S C R E E N I N G W H O H AV E N E V E R S C R E E N E D F O R D ATA Q U A L I T Y

91% run quality checks

2015 2016

Daily 19% 22%

Weekly 11% 12%

Monthly 16% 14%

Quarterly 12% 12%

Annually 14% 14%

Every few years 2% 1%

Only when issue suspected 16% 17%

Have never run quality checks 11% 9%

2013 2015 2016

80% 76% 82%

A M O N G T H O S E F A M I L I A R W I T H C L I E N T S C R E E N I N G

Test monthly or more often

2015: 26%2016: 48%

Notes: Small base sizes (n<75); no statistical testing performed

All countries

Only countries with regulatory requirements

Other

S C R E E N F O R L O C A L- L E V E L P E P S W H E R E L O C A L P E P S I N C L U D E D I N C L I E N T S C R E E N I N G

89% 89% 92%

0%

20%

40%

60%

80%

100%

4% 3% 4%

19% 19% 21%

77% 78% 75%

0%

20%

40%

60%

80%

100%

2013 2015 2016

2013 2015 2016

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S E C O N D A R Y I D E N T I F I E R S U S E D I N C L I E N T S C R E E N I N G As in previous years, more than 90% of respondents report their organizations use secondary identifiers in the client-screening process. Date of birth, personal identification data, country of birth and entity type continue to be the most widely used secondary identifiers. The proportion using name in original script increases in 2016 compared to 2015.

AV E R A G E T I M E T O C L E A R G E N E R AT E D A L E R T As in previous years, nearly half of the respondents claim their companies typically clear a generated alert within five minutes or less. The average across all respondents increases to 19 minutes, likely due to a change in available survey responses.

2013 2015 2016

Date of birth 77% 78% 81%

Personal identification data (passport, ID card)

58% 62% 62%

Country of birth 52% 53% 52%

Entity type 47% 49% 52%

Known location 43% 43% 44%

City/state province of birth 46% 47% 44%

Gender 38% 40% 44%

Name in original script 29% 28% 33% ↑

Corporate identification data 23% 26%

None 6% 7% 4%

A M O N G T H O S E F A M I L I A R W I T H C L I E N T S C R E E N I N G% O F A L E R T S T H AT A R E F A L S E P O S I T I V E S

Other

Longer than 1 hour*

31-60 minutes

16-30 minutes

6-15 minutes

3-5 minutes

<2 minutes

*New response option in 201621% 20% 21%

26% 27% 24%

22% 23% 23%

12% 13% 12%

13% 12% 8% 10%

6% 5% 3%

0%

20%

40%

60%

80%

100%

2013 2015 2016

Average 13 min. 13 min. 19 min.

Cleared in 5 minutes or less:

2013: 47%2014: 47%2016: 45%

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R E A S O N S T O R E V I E W / C H A N G E C L I E N T- S C R E E N I N G T E C H N O L O G YAmong respondents from companies with client-screening technology solutions in place, cost issues and excessive false alerts – positive and/or negative – are the reasons most likely to prompt companies to review their solutions. Cost issues are more important in 2016 than in 2015.

2013 2015 2016

Cost issues 38% 40% 46% ↑

Too many false-positive alerts 48% 47% 45%

Too many false-negative alerts 40% 40% 43%

Poor customer service/roadmap 31% 33% 36%

Consolidation of software across risk areas

32% 38% 35%

Enterprise technology consolidation 33% 34% 35%

Inability to handle non-Latin script 10% 12% 11%

2013 2015 2016

Part of KYC process 84% 82% 83%

Due diligence 66% 69% 70%

Country company registry 30% 29% 31%

Outsourced due diligence 16% 18% 21%

A M O N G T H O S E F A M I L I A R W I T H C L I E N T S C R E E N I N G A N D H AV E S O L U T I O N I N P L A C E

Beneficial Ownership & Sanctions Lists

H O W C O M P A N I E S V E R I F Y B E N E F I C I A L O W N E R S H I P Beneficial ownership continues to be verified mainly as part of the KYC process or through internal due diligence.

B E N E F I C I A L O W N E R S H I P V E R I F I C AT I O N R E Q U I R E D Nearly half of respondents report their companies adhere to the standard of 25% beneficial ownership verification, and another one-fourth require 10% verification. Nearly one-tenth claim their companies require 100% verification.

Other

100%

26%–99%

25%

11%–24%

10%

1%–9%

5% 3% 3%

26% 29% 26%

3% 4% 4%

42% 42% 47%

6% 5% 6% 12% 9% 8% 6% 7% 6%

0%

20%

40%

60%

80%

100%

201620152013

Average 32% 29% 28%

“Other” mentions (2016): – Risk-based– Varies by entity/account type– No formal requirements

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U S A G E O F S A N C T I O N S / O F F I C I A L L I S T SThe average number of sanctions/official lists for client screening increases in 2016 compared to 2015, due mainly to a decrease in respondents reporting their companies use five or fewer lists. Payment filtering list usage also increases, with more respondents estimating their companies use 10 or more lists.

I N T E R N A L U P D AT E S T O S A N C T I O N S / O F F I C I A L L I S T SNearly 90% of respondents expect internal lists to be updated within 24 hours of changes to sanctions/official lists, including one-third that expect updates within four hours. Almost 40% of respondents report their companies are basing their expectations on regulator guidance in 2016, comparable to 2015 levels.

P R E F E R E N C E F O R S P E E D V S . A C C U R A C Y I N L I S T U P D AT E SMore than half of respondents prefer accurate/complete list information over quicker updates. Another 30% claim that preference for quicker updates would depend on the effort required to correct any erroneous list information.

C H O O S I N G L I S T S F O R C L I E N T S C R E E N I N G A N D P AY M E N T S F I LT E R I N GThe proportion of respondents working in AML departments that make risk-based decisions (by AML officers or staff) in choosing which sanctions/official lists to use in client screening and/or payments filtering decreases in 2016 compared to 2015. The impacts of guidance from local AML regulations, system capabilities, origin of list and risk of penalty increases.

2013 2015 2016

Risk-based decision by AML Officer/Staff 62% 62% 57% ↓

Guided by local AML regulation 47% 47% 54% ↑

Understanding of best practices 37% 39% 41%

System capabilities 27% 26% 32% ↑

Centralized decision 28% 28% 30%

Origin of list 23% 23% 28% ↑

Risk of penalty 12% 13% 17% ↑

Currency of payment 9% 9% 12%

2016

More accurate and complete list information 53%

Depends on the impact of additional research efforts to correct and enhance list information on the availability of the list

30%

Quicker updates of lists 16%

A M O N G T H O S E R E S P O N S I B L E F O R C L I E N T S C R E E N I N G A N D / O R P AY M E N T S F I LT E R I N G

W H AT I S VA L U E D M O S T R E G A R D I N G S A N C T I O N S / O F F I C I A L L I S T S

A M O N G T H O S E R E S P O N S I B L E F O R C L I E N T S C R E E N I N G A N D / O R P AY M E N T S F I LT E R I N G# O F L I S T S U S E D I N C L I E N T S C R E E N I N G

A C C E P TA B L E D E L AY I N G E T T I N G I N T E R N A L L I S T S U P D AT E D

I N T E R N A L E X P E C TAT I O N S R E G A R D I N G S P E E D O F L I S T U P D AT E S A R E B A S E D O N R E G U L AT O R G U I D A N C E

# O F L I S T S U S E D I N PAY M E N T S F I LT E R I N G

40 or more

30 to 39

20 to 29

10 to 19

6 to 9

1 to 5

> 10

8 to 10

6 to 7

4 to 5

2 to 3

1

> 24 hours

5–24 hours

2–4 hours

1 hour or less

Note: Small base size in 2016 (n<75)

10% 10% 9%

21% 24% 10%

23% 25%

24%

16% 8%

9%

8% 5%

9%

22% 28% 40%

0%

20%

40%

60%

80%

100%

43% 44% 38%

18% 16% 16%

15% 15% 17%

6% 6% 7% 3% 2% 2%

16% 17% 19%

0%

20%

40%

60%

80%

100%

14.4 14.6 15.9 Average lists

Average lists 6.1 6.2 7.6

2013 2015 2016 2013 2015 2016

↑ ↑

↑

10% 10% 9%

21% 24% 10%

23% 25%

24%

16% 8%

9%

8% 5%

9%

22% 28% 40%

0%

20%

40%

60%

80%

100%

43% 44% 38%

18% 16% 16%

15% 15% 17%

6% 6% 7% 3% 2% 2%

16% 17% 19%

0%

20%

40%

60%

80%

100%

14.4 14.6 15.9 Average lists

Average lists 6.1 6.2 7.6

2013 2015 2016 2013 2015 2016

↑ ↑

↑

47% 40% 39%

0%

20%

40%

60%

18% 16% 14%

15% 17% 18%

55%

2013 2015 2016 2013 2015 2016

52% 55%

12% 15% 13%

0%

20%

40%

60%

80%

100%

47% 40% 39%

0%

20%

40%

60%

18% 16% 14%

15% 17% 18%

55%

2013 2015 2016 2013 2015 2016

52% 55%

12% 15% 13%

0%

20%

40%

60%

80%

100%

14

A D D I T I O N A L I N F O R M AT I O N U S E D I N S A N C T I O N S / O F F I C I A L L I S T S The proportion of respondents reporting their companies include information other than the entities named on sanctions/official lists in their screening processes increases in 2016 compared to 2015. Additional names of people/companies/organizations, entities controlled or owned by other sanctioned entities and entities linked to sanctioned jurisdictions are the most frequently used types of supplemental information.

E X I T I N G B U S I N E S S L I N E S A N D C U S T O M E R S E G M E N T SIn 2016, 40% of respondents report their companies have exited a full business line or segment of business in the past 12 months due to perceived regulatory risk and/or the organization’s inability to manage the risk, an increase from 2015. About one-third of respondents claim their companies are planning to exit and/or are investigating the possibility of exiting a business line or segment in the next 12 months due to regulatory risk.

De-Risking

2013 2015 2016

Additional names of people, companies, organizations

80% 77% 78%

Entities controlled/owned by other sanctioned entities

66% 66%

Entities linked to sanctioned jurisdictions 69% 68% 64%

Vessels 39% 44% 43%

Cities and ports 34% 33% 38%

BIC Codes 31% 24% 27%

Debt and equity securities 13% 15%

Chinese Commercial/Telegraph Codes 14% 10% 14%

2015 2016

Due only to regulatory risk 30% 33%

Due to inability to manage the risk 21% 25%

2015 2016

Planning to exit 10% 12%

Investigating possibility of exiting 24% 23%

Not planning or investigating exit 70% 67%

T Y P E S O F A D D I T I O N A L I N F O R M AT I O N I N C L U D E D

I N C L U D E A D D I T I O N A L I N F O R M AT I O N T O C O M P LY W I T H S A N C T I O N P R O G R A M S

H AV E E X I T E D B U S I N E S S L I N E / S E G M E N T O R C U S T O M E R S E G M E N T I N P A S T 1 2 M O N T H S

P O S S I B I L I T Y O F E X I T I N G B U S I N E S S L I N E / S E G M E N T I N N E X T 1 2 M O N T H S D U E T O R E G U L AT O R Y R I S K

Net: Have exited for either reason

2015: 35%2016: 40% ↑

Net: Planning and/ or investigating possibility of exiting

2015: 30%2016: 33%

70% 71% 76%↑

0%

20%

40%

60%

80%

2013 2015 2016

15

F A C T O R S T H AT C O U L D M A K E F I R M R E - E VA L U AT E E X I T D E C I S I O NMore than half of respondents whose companies are considering exiting business segments claim that better guidance from regulators could keep them from leaving. However, more than 20% believe nothing can influence the decision to exit.

H U M A N T R A F F I C K I N G I N F O R M AT I O N A N D A C T I O N SNearly 70% of respondents report their organizations have modified AML training and/or transaction monitoring to incorporate human trafficking and smuggling red flags and typologies (organizations typically have done both or neither). Nearly all respondents work in organizations that use information, usually multiple sources, to identify human trafficking and smuggling activities.

T E R R O R I S M - R E L AT E D A C T I O N S70% of respondents report their organizations have modified AML training and/or transaction monitoring to include red flags and typologies indicative of ISIS terrorist financing and recruitment (organizations typically have done both or neither).

Human Trafficking & Terrorism

T Y P E S O F B U S I N E S S S E G M E N T S A N D R E A S O N S F O R E X I T I N G More than half of the respondents whose companies are considering exiting business segments mention leaving industries designated as high-risk by government agencies. At least 40% also cite leaving specific product lines or geographic areas. The main reasons for leaving involve the organization is no longer willing to assume the segment risk and the cost of compliance making the segment unprofitable.

T Y P E S O F S E G M E N T S C O N S I D E R I N G E X I T I N G

2016

Industries that have been designated high-risk by government agencies

51%

Specific products/product lines 45%

Specific geographic area(s) 40%

Non-governmental organizations (NGOs) or charities

14%

Other 8%

2016

More precise guidance from regulators or increased compliance comfort for segments in question

53%

A mechanism to “pre-clear” compliance activities with regulator for riskier business segments

32%

A “hold harmless” letter or some type of “safe harbor” from regulators or other government agency

30%

Other 3%

Nothing could influence the decision 21%

R E A S O N S C O N S I D E R I N G E X I T I N G S E G M E N T

2016

Segment no longer within organization’s risk appetite

56%

Cost of compliance makes segment unprofitable

51%

Segment draws excessive regulatory oversight

40%

No confidence regulators will approve risk management approach

20%

Segment is generally unprofitable 18%

Other 1%

A M O N G T H O S E P L A N N I N G A N D / O R I N V E S T I G AT I N G P O S S I B I L I T Y O F E X I T I N G

A M O N G T H O S E P L A N N I N G A N D / O R I N V E S T I G AT I N G P O S S I B I L I T Y O F E X I T I N G

2016

Have modified AML training 63%

Have modified AML transaction monitoring

58%

Neither of these 31%

2016

Have modified AML training 65%

Have modified AML transaction monitoring

64%

Neither of these 30%

2016

FinCEN or other advisories 73%

Government agencies 68%

Adverse media 65%

FATF reports 64%

Other 6%

None 5%

A M O N G T H O S E P L A N N I N G A N D / O R I N V E S T I G AT I N G P O S S I B I L I T Y O F E X I T I N G

A C T I O N S TA K E N T O I N C L U D E A M L T Y P O L O G I E S A N D R E D F L A G S I N D I C AT I V E O F I S I S T E R R O R I S T F I N A N C I N G A N D R E C R U I T M E N T

I N F O R M AT I O N U S E D T O I D E N T I F Y H U M A N T R A F F I C K I N G A N D S M U G G L I N G A C T I V I T I E S

16

Respondent Profiles

C O M P A N Y G E O G R A P H Y A N D S I Z E As in recent years, about 70% of respondents are from companies in the Americas, including a majority from the US. Respondents are split between small, medium and large companies.

A M L D E P A R T M E N T S T R U C T U R E A N D S TA F F I N G As in previous years, most respondents report their AML departments are centralized. The proportion having a combination of structures decreases in 2016 compared to 2015. More than 60% report their organizations have increased AML staff levels in the past year, continuing the increase in staffing growth rates in recent years.

T Y P E O F O R G A N I Z AT I O N Retail and commercial banking remain the largest industries represented among respondents, followed by private banking/wealth management and investment banking.

2013 2015 2016

Retail banking 37% 36% 38%

Commercial banking 31% 32% 35%

Private bank or wealth management 16% 17% 16%

Investment banking 13% 16% 15%

Brokerage 9% 9% 9%

Money service business 9% 8% 9%

Consulting company 7% 8% 7%

Insurance 7% 6% 5%

Mentions less than 5% omitted

R E G I O N

A M L D E P A R T M E N T S T R U C T U R E

C H A N G E I N A M L S TA F F I N G I N P A S T Y E A R

C O M P A N Y S I Z E

APAC

EMEA

AmericasIncreased

Remained the same

Decreased

Combination

Regional

Decentralized

Centralized

10,000+ employees

Medium (501-10,000 employees)

Small (1-500 employees)

73% 73% 69%

15% 15% 16%

12% 12% 15%

0%

20%

40%

60%

80%

100%

U.S. 57% 58% 56%

31% 31% 29%

34% 30% 30%

35% 39% 40%

0%

20%

40%

60%

80%

100%

2013 2015 2016 2013 2015 2016

73% 73% 69%

15% 15% 16%

12% 12% 15%

0%

20%

40%

60%

80%

100%

U.S. 57% 58% 56%

31% 31% 29%

34% 30% 30%

35% 39% 40%

0%

20%

40%

60%

80%

100%

2013 2015 2016 2013 2015 2016

9% 7% 5%

39% 33% 32%

52% 60% 63%

0%

20%

40%

60%

80%

100%

59% 57% 60%

6% 7% 8% 5% 4% 5%

30% 32% 27% ↓

0%

20%

40%

60%

80%

100%

2013 2015 2016 2013 2015 2016

9% 7% 5%

39% 33% 32%

52% 60% 63%

0%

20%

40%

60%

80%

100%

59% 57% 60%

6% 7% 8% 5% 4% 5%

30% 32% 27% ↓

0%

20%

40%

60%

80%

100%

2013 2015 2016 2013 2015 2016

17

A M L J O B F U N C T I O N S In 2016, 80% of respondents have AML-related job functions, a level comparable to previous years. Many also identify working in KYC, regulatory/policy compliance and compliance operations.

J O B T I T L E S More than 70% of respondents have job titles specifying AML, BSA and/or Compliance responsibilities. The proportion of respondents who are AML Compliance Managers increases in 2016 compared to 2015.

2013 2015 2016

Anti-Money Laundering (AML) 78% 79% 80%

Know Your Customer (KYC) 49% 50% 50%

Regulatory & policy compliance 49% 52% 48%

Compliance operations 45% 45% 44%

Sanctions 28% 33% 34%

Fraud 28% 26% 28%

Client screening 26% 26% 26%

Governance 17% 20% 19%

Other 10% 11% 11%

Accounting risk and control 9% 8% 10%

Payments filtering 10% 9% 9%

Technology risk and security 7% 6% 8%

2013 2015 2016

AML/BSA/Compliance Officer 20% 19% 20%

AML/BSA/Compliance Chief Officer 15% 13% 12%

AML Compliance Manager 8% 7% 10% ↑

AML/Compliance Consultant/Specialist/Investigator

9% 9% 10%

AML/BSA/Compliance Analyst 11% 11% 10%

CEO/President/Director/AVP/VP/SVP/Officer 9% 9% 8%

AML Auditor/Audit Manager 5% 9% 8%

Risk Analyst/Manager/Officer 6% 5% 5%

Other 17% 18% 16%

18

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