Trends in Canadian Suspicious Transaction Reporting (STR)

FINTRAC Typologies and Trends Reports - April 2011

Table of Contents


Trends in Canadian Suspicious Transaction Reporting (STR) - April 2011
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Message from the Director

I am pleased to present another report in FINTRAC's continuing series of strategic financial intelligence reports. Trends in Canadian Suspicious Transaction Reporting represents an ambitious undertaking—the first time we have made an in-depth analysis of 300 000 suspicious transaction reports (STRs) we have received over the last ten years from across the country.

This study identifies trends in the reporting of suspicious transactions, particularly the grounds for which the suspicions were reported. We hope our results will provide tangible feedback to help reporting entities strengthen their efforts to comply with reporting obligations under the Proceeds of Crime (Money Laundering) and Terrorist Financing Act (PCMLTFA). This report presents a broad overview of trends identified to date and we plan to do more intensive analysis in the coming months to see if we can discover more trends.

Our analysis has revealed that the reporting entities are good overall at submitting STRs concerning structuring activities and the placement stage of money laundering, but they are not doing nearly so well when the laundering concerns the layering and integration stages. The layering stage involves converting the proceeds of crime into another form and creating complex layers of financial transactions to disguise the audit trail, and the source and ownership of funds. The integration stage involves placing the laundered proceeds back in the economy to create the perception of legitimacy.

STRs provide valuable information allowing FINTRAC to assist partners in their investigations of money laundering (ML), terrorist financing (TF), and other threats to the security of Canada. They also feed into strategic intelligence which informs various stakeholders about current and emerging ML/TF trends and patterns, as well as supports high-level policy decisions.

Since new compliance obligations came into force in 2008, reporting entities are required to expend more effort in identifying their highest ML and TF risks. We hope to see an increase in the level of variety and sophistication in STR reporting in the future. The purpose of this report is to provide strategic financial intelligence feedback to help reporting entities conform to these new obligations.

The Centre believes that Canadian reporting entities can make a real difference in the fight against money laundering and terrorist financing through the identification and reporting of suspicious transactions. FINTRAC looks forward to continued collaboration with all financial entities in order to detect, deter and prevent money laundering and terrorist financing activities. Not only does money laundering and terrorist financing threaten the integrity of Canada's financial system, but these activities are fundamentally at odds with Canadian values and interests, and pose serious risks to the safety, security, and prosperity of all Canadians.

Jeanne M. Flemming
Director

1. Introduction

This is one of a series of FINTRAC publications which are intended to provide strategic financial intelligence and feedback to reporting entities. This particular document is focused on suspicious transaction reports (STRs)Footnote 1 submitted to FINTRAC, from November 8, 2001 (time when the legal obligation for STR reporting came into force) to August 31, 2010.

For the purposes of this report, different techniques were used to analyze STRs submitted to FINTRAC. In addition to illustrating the overall STR volume by sector, by region, and per capita, the text mining technique was used to analyze Part G of STRs in an effort to identify trends in the reasons for suspicion provided by reporting entities. Developing a standardized vocabulary for the text mining tool, in both official languages, proved to be a challenge and therefore, for this report, only English STRs could be analyzed. However, the development of the French text mining vocabulary was initiated by manually reviewing a sample of French STRs, the results of which are also included in this report. In the next few months, the automated analysis of French STRs will be conducted in a similar fashion than for the English STRs, and a second report including those results will be published in late spring or early summer of 2011.

A broad overview of various STR trends is provided in this report, which highlights the important role that STRs play in developing financial intelligence. Many interesting trends were observed in the vast amount of STR data analyzed for this project, but to keep the report within a reasonable length, only a small percentage of our findings are presented. It is anticipated that this will be the first in a series of FINTRAC analytical publications focusing on STRs, with future iterations providing a more in-depth focus on selected topics related to money laundering and terrorist financing suspicious transaction reporting.

This report is divided into several sections. The first part highlights the role of an STR in developing various FINTRAC products such as strategic intelligence assessments and case disclosures to law enforcement and security agencies. The second part provides an overview of STR reporting volumes by sector, region, and per capita. Part 3 is an analysis of various trends in the Part G narrative of STRs. This part explores relationships between STR reporting and various factors such as region, population, and the most common reasons for suspicion. Part 4 concludes the report and Annex 1 describes various characteristics of STRs that are valuable to FINTRAC intelligence analysts. Finally, Annex 2 presents examples of FINTRAC cases where STRs played a key role.

(A) STRs: A Key Source of Financial Intelligence

The world of terrorist financing and money laundering is constantly evolving, and we must aim to keep abreast of new developments. STRs can be viewed as an important part of an early warning financial intelligence system, which assists FINTRAC in uncovering situations when funds are being used for illegitimate goals. The information contained within STRs provides valuable insight for a wide spectrum of issues ranging from tactical intelligence for furthering criminal investigations to strategic intelligence for supporting high level policy decisions.

FINTRAC regularly produces a variety of strategic financial intelligence products on emerging trends and patterns in the way funds may be moved by criminal organizations and terrorist financiers, for a variety of different users. FINTRAC develops such products, not only for our case disclosure recipients in law enforcement or security agencies, but also for the broader security and intelligence community. Examples of such products include Backgrounders on prepaid cards and virtual worlds, as well as Financial Intelligence Assessments, which involve extensive reviews of cases and reports associated with countries of concern and terrorist groups. FINTRAC also analyzes the information provided in STRs and other report data to advise the Department of Finance on emerging threats to assist it in making well-informed policy decisions concerning the protection of the integrity of the Canadian financial system and maintaining an appropriate anti-money laundering and counter-terrorist financing regime. Finally, FINTRAC continues to produce and disseminate a wide range of strategic analysis publications for reporting entities and other stakeholders such as this document, sector-specific Money Laundering and Terrorist Financing Typologies and Trends Reports, and the Money Laundering and Terrorist Financing Watch.

Valuable information is provided in all fields of STRs, but even more so in the Part G narrative which allows reporting entities to provide additional details about the reasons for their suspicions and to describe the unusual behaviour of their clients. STRs also play an important role in the reporting of transactions conducted under the CA$10,000 reporting threshold. STRs can often assist FINTRAC's analysis of other reports received from reporting entities such as large cash transaction reports (LCTRs) and electronic funds transfer reports (EFTRs), thus contributing to the detection and, ultimately, to the possible investigation of money laundering and terrorist financing activity.

FINTRAC's store of STR and other report data is complemented by information provided voluntarily by law enforcement and security agencies, foreign financial intelligence units (FIUs), databases of classified intelligence and from public sources of information. Together they are powerful sources of information, enabling us to assist police, intelligence agencies, and others in the detection and deterrence of money laundering and terrorist activity financing.

(B) How Reports Are Used in FINTRAC Cases

Case disclosures to law enforcement and security agencies are another intelligence product of FINTRAC's analysis of the information received from reporting entities. Reports are analyzed, along with other information available, to uncover connections among parties and to identify financial activity associated with patterns of suspected money laundering and/or terrorist financing. From 2006 to 2009, 72% of FINTRAC case disclosures, on average, included at least one STR. There have been numerous instances where STRs assisted FINTRAC to identify new connections between organized crime groups and various other individuals or entities for the first time. Once FINTRAC determines there are reasonable grounds to suspect that the information would be relevant to the investigation or prosecution of a money laundering offence, terrorist financing offence or threat to the security of Canada, FINTRAC must disclose "designated information" to the appropriate police force or security agency. Annex 2 includes three cases that demonstrate how STRs can be key to developing a case. Sanitized examples of STRs used in these cases are also provided.

(C) Report Methodology

In developing this STR Report, FINTRAC used multiple analytical techniques. The first step was to identify all STRs ever submitted to FINTRAC, in English and French, for which statistics are provided in Table 1. Our analysis of STR data has revealed that approximately 88% of the total STRs submitted to FINTRAC between November 2001 and August 2010 is from the following business sectors: banks and trust/loans, credit unions/caisses populaires, and money services businesses (MSBs).

Table 1: Percentage of STRs submitted to FINTRAC by sector Footnote 2
Sector Number of STRs submitted (percentage)
Banks and trust/loans 33%
MSBs 29%
Credit unions / caisses populaires 26%
Other sectors 12%
Total 100%

Text mining

A brief overview of the text mining technique is provided below.

Contained within each FINTRAC suspicious transaction report is a narrative comment field (Part G) in which reporting entities are free to describe suspicions associated with financial transactions. One of the goals of our analysis was to extract general themes from this text and identify trends in suspicious behaviour related to money laundering and/or terrorist financing.

There were several steps involved in order to mine the text in Part G of over 240,000 English STRs. First, a standardized vocabulary was created by defining words (or concepts) and collapsing them into synonym groupings. Once established, vocabulary elements were identified within narratives across all STRs. These elements were then extracted based on contextual patterns. For example, observe the following three sentence segments with the concepts in red:

The text "US$ 1,000" and "$20 dollar bills" are synonymous with the term cash – which is the term extracted.

Once processed, each narrative is represented by a series of standardized concepts which can be found in the same STR and analyzed to identify possible trends. For example, the concept cash can be found in the same STR than a financial action concept such as deposit which, when analyzed may reveal some interesting trends. For the purposes of simplifying the presentation of our results in this report, concepts such as "cash deposit" are referred to as single suspicion concepts while when two of them are found in the same STR, we refer to them as paired suspicion concepts. It should be noted that single concepts, on their own, cannot be easily linked to ML or TF techniques and methods. However, when two or more concepts are found in the same STR, the reason(s) for suspicion become more apparent and concepts can be more easily linked to ML or TF activity.

The core of the text mining process is to develop accurate single concepts which become the building blocks in establishing concept groups used to summarize STR narratives. As the text mining dictionary and methodology matures, these groupings will become more complex and provide a higher level of summarization accuracy. Given the infancy of FINTRAC's text mining program, we have elected to limit the concept groups to pairings to ensure maximum accuracy for this document. These single concepts and their pairings offer a broad overview of the STR narratives. Future reports will, however, present results of more complex groupings and therefore should provide a more complete picture of the trends associated with all STR narratives.

Table 2 shows the total number of English STRs received between January 1, 2003 and December 31, 2009 from each sector and which were analyzed using the text mining technique. It illustrates how many of those STRs contained at least one suspicion concept.

As indicated in this table, the percentage of STRs for which our text miner identified at least one suspicion concept varied between 50% and 94%. The lower percentages for some sectors may indicate either a need to further refine the text mining vocabulary, or the possibility that the Part G narratives, in some STRs, are not of adequate quality. It should be noted that trends presented in this report are dependent on the text mining vocabulary developed to date. Other suspicion concepts may be contained in the STRs that have not yet been identified and therefore not yet included in the vocabulary.

Of the total sample of STRs in both languages, approximately 94,700 were submitted by reporting entities from Quebec. About 79% (75,000) of these STRs were submitted in French and the remainder in English. Due to the complexity of the text mining methodology and some limitations with the tool, the automated text mining of the French STR Part G narratives was not possible for this report. These issues are currently being addressed and the first step towards developing the French vocabulary necessary for text mining analysis was taken by manually reviewing a stratified sample of over 400 French STRs submitted by reporting entities in Quebec. In a future FINTRAC report on STR trends, we will be in a position to use the text mining technique to review all STRs written in French and submitted from reporting entities across Canada.

Table 2: Percentage of English STRs containing at least one suspicion concept
Sector Total number of English STRs Total number of English STRs containing at least one suspicion concept Percentage of STRs containing at least one suspicion concept
Banks and trust/loans 108,452 102,260 94.29%
MSBs 94,987 87,082 91.68%
Credit unions/caisses populaires 26,150 20,937 80.07%
Casinos 15,697 12,462 79.39%
Securities dealers 895 707 78.99%
Real estate 56 34 60.71%
Life insurance 1,347 678 50.33%
Other sectorsFootnote 3 105 74 70.48%

2. Suspicious Transaction Reporting Volume Overview

(A) Reporting Volumes by Sector

Reporting entities (RE) with obligations under the PCMLTFA include the following:

This section of the report provides an overview of STR (English and French) reporting volumeFootnote 4 broken down by various business sectors, and how it has changed over time.

Figure 1: Number of STRs submitted to FINTRAC by sector between 2007 and 2009

Number of STRs submitted to FINTRAC by sector between 2007 and 2009

View the text equivalent for Figure 1

This chart illustrates the number of STRs submitted to submitted to FINTRAC by sector between 2007 and 2009.


Figure 1 shows an overall steady increase in STR reporting since 2007 in most sectors. However, a significant spike in STR reporting from banks was observed in 2008 but volumes dropped in 2009 to a lower level than in 2007. It is suspected that this may be attributable to a few large reporting entities modifying their policies and procedures for submitting STRs, which resulted in significant fluctuations in their reporting levels.

The following chart shows the total number of reporting entities that submitted at least one STR to FINTRAC in a given year. It should be noted that there has always been less than 1,000 different REs submitting an STR to FINTRAC in any calendar year.

Figure 2: Total number of reporting entities submitting at least one STR per year

Total number of reporting entities submitting at least one STR per year

View the text equivalent for Figure 2

This chart illustrates the number of reporting entities submitting at least one STR per year between 2001 and 2010.


Since November 2001, when the legislative obligation to report STRs came into effect, 2,201 different reporting entities have submitted an STR to FINTRAC. It is also interesting to note that approximately 1,000 of these reporting entities have historically sent more than five STRs to FINTRAC.

It is acknowledged that the type of business model, client base, and transactions facilitated by some reporting entities may not trigger the legislative obligation to file an STR. Given that FINTRAC has recently marked ten years since its creation and that, in November 2011, STR reporting obligations will reach the same anniversary, it is hoped that various REs will show an increased awareness of their obligations.

Since June 23, 2008, reporting entities have had the obligation to identify and assess their risk of ML and TF, and to conduct ongoing monitoring and mitigation of their highest risks. One of the intended objectives of the new risk-based approach (RBA) obligation is to increase the overall quantity and quality of the STRs submitted to FINTRAC. At this juncture, an analysis of the STR reporting data since June 2008 indicates mixed results. Many of the business sectors that were already reporting to FINTRAC showed increases in the volume of STR reporting in the months immediately prior to and post June 2008. Nonetheless, this trend was not observed in all sectors. One may hypothesize that those who were already reporting are doing more, while other reporting sectors with low reporting volumes have continued with this trend. However, it should be noted that high volumes of STR reporting does not necessarily correlate to high quality STRs.

Top 25 reporting entities submitting most STRs

It is interesting to note that there is a mix of different sectors represented in the Top 25 reporting entities submitting the most STRs. The types of sectors represented among these include the following:

The Top 25 reporting entities account for over 60% of the 300,000 and more STRs submitted to FINTRAC between November 2001 and August 2010. A list in descending order of the Top 25 reporting entities by sector is provided in Table 3.

Table 3: Top 25 reporting entities submitting STRs to FINTRAC
Position Business Sector Total number of STRs
1 Money services businesses 58,761
2 Banks and trust/loan 43,994
3 Banks and trust/loan 24,396
4 Banks and trust/loan 11,258
5 Casinos 8,467
6 Banks and trust/loan 6,586
7 Banks and trust/loan 4,620
8 Money services businesses 4,559
9 Banks and trust/loan 3,857
10 Money services businesses 3,724
11 Money services businesses 3,269
12 Money services businesses 2,815
13 Banks and trust/loan 2,674
14 Money services businesses 2,570
15 Banks and trust/loan 2,415
16 Money services businesses 2,336
17 Casinos 2,094
18 Credit unions/caisses populaires 2,060
19 Money services businesses 2,045
20 Money services businesses 2,019
21 Credit unions/caisses populaires 1,963
22 Banks and trust/loan 1,834
23 Credit unions/caisses populaires 1,802
24 Banks and trust/loan 1,781
25 Money services businesses 1,699
TOTAL   203,598

(B) STR Reporting Volumes by Region and Per Capita

Previous FINTRAC publications such as our annual reports have presented the volumes of all report types sent to FINTRAC: large cash transaction reports (LCTRs), electronic funds transfer reports (EFTRs), suspicion transaction reports (STRs), and cross-border currency reports (CBCRs).

The volume of EFTRs and LCTRs often overshadow the volume of STRs. Despite the fact that they are an extremely useful form of financial intelligence, STRs only comprise an average of approximately 0.25% of all the reports sent to FINTRAC on an annual basis. When EFTR and LCTR reporting volumes are set aside to focus only on STR reporting, some interesting trends become apparent. In Figure 3 below, the total volume of STRs (between November 8, 2001 and August 31, 2010), broken down by province and sector, is illustrated.

In Figure 3, there are many different interesting trends. Overall it appears that the banks and trust/loans, MSBs and credit unions/caisses populaires account for the highest percentages of STRs provided to FINTRAC by each province. When one compares the two largest STR reporting provinces, we see that the percentage of STRs reported by the banks and trust/loan sector in Quebec is much smaller than in Ontario. This is mainly due to the fact that caisses populaires report the large majority of STRs in Quebec. In terms of the percentage of STRs for the casino sector reported at a provincial level, Ontario has the highest, while Quebec has one of the lowest.

Figure 3: Total number of STRs by province and by sector

Total number of STRs by province and by sector

View the text equivalent for Figure 3

This map of Canada illustrates the total number of STRs submitted by province and by sector from November 2001 to August 2010.

Overall the map shows that the banks and trust/loans, MSBs and credit unions/caisses populaires account for the highest percentages of STRs provided to FINTRAC by each province.

STR reporting by region

The map in Figure 4 divides the country into 288 different regionsFootnote 6 and illustrates the regional differences in the volume of STRs reported by all sectors between November 8, 2001 and August 31, 2010. As one would expect, the major Canadian regional municipalities generally exhibit larger STR volumes.

Figure 4: Number of STRs provided by all sectors by regional municipality

Number of STRs provided by all sectors by regional municipality

View the text equivalent for Figure 4

This map of Canada highlights the regional differences in the total volume of STRs reported by sector. The map illustrates that most major Canadian regional municipalities exhibit larger STR volumes ranging from 10 001 –; 100 000 STRs. While most other regional municipalities across the country range from 0 –; 100 STRs.

STR reporting per capita (per 100,000 people)

When representing the regional STR volumes per capita for the same period as in Figure 4, some interesting trends emerge which are illustrated in Figure 5 and discussed in greater detail in the following pages.

In our analysis of the number of STRs per capita, it was noted that Canada's three largest cities/regional municipalities did appear in the list of the Top 50 reporting entities in Canada submitting most STRs. Interestingly, Toronto is 14th, Vancouver is 21st and Montreal is 25th. Six out of ten Canadian provinces have at least one region that is identified amongst the Top 50 reporting entities.

There are a variety of factors that may contribute to the STR reporting trends illustrated in Figure 5, which may include social, cultural, economic, and criminal characteristics specific to some regions. In some situations, the high levels of STR reporting per capita in rural areas maybe partly attributable to employees of reporting entities in rural municipalities having a more personal knowledge of their clients and communities than those in major centres. It may also be due to an increased sense of obligation for those living in smaller municipalities to make a direct contribution towards protecting their communities from suspected criminal activity. Higher STR reporting may also be explained by reporting entities in some of these regions having more robust AML/CFT programs.

There may have been instances in which some entities were believed to be over-reporting STRs. For example, several reporting entities from one part of the country have agreements for their clients to use each other's ATMs. However, it appeared that these reporting entities were submitting a significant volume of STRs on a routine basis whenever any client who was not a local member of their financial entity was using their ATM.

Figure 5: Number of STRs per 100,000 people within each regional municipality

Number of STRs per 100,000 people within each regional municipality

View the text equivalent for Figure 5

This map of Canada illustrates the number of STRs per capita. One key finding illustrated in the map is that six out of ten Canadian provinces have at least one regional municipality that is amongst the highest levels of per capita reporting.

Notable regional STR reporting trends per capita

One notable finding is that there are high levels of STR reporting in regions of British Columbia's interior near Nelson and Fort St. John that have been identified in the media as being home to organized criminal activity.Footnote 7 In addition, other open source reporting has indicated that the B.C. marijuana trade has been generating annual revenues of approximately $4 billion for at least the past seven years.Footnote 8 A more detailed map of STR reporting in B.C. can be found in Figure 6.

Figure 6: Number of STRs per 100,000 people within each regional municipality in Southern British Columbia (November 2001 to August 2010)

Number of STRs per 100,000 people within each regional municipality in Southern British Columbia (November 2001 to August 2010)

View the text equivalent for Figure 6

This map illustrates British Columbia and highlights that there are high levels of per capita STR reporting in the regions near Nelson and Fort St. John. The number of STRs reported in these areas range from 2001 to 6250 STRs.


Other areas of significant STR reporting, as illustrated in Figure 7, can be found in the regions that include Fort McMurray (Northern Alberta), Yellowknife (Northwest Territories), and various areas of Saskatchewan. These regions of the country have enjoyed very high levels of economic growth over the past decade, which is largely attributable to booms in the oil and mining industries. It is known that organized crime often flows to areas with more money and wealth. Multiple reporting entities from these areas have also been identifying and reporting increased suspicious activity. Unclassified reporting has revealed that there has been increased drug trafficking and other organized criminal activity in these regions. For example, it has been previously reported by the Criminal Intelligence Service of Canada that organized crime has targeted diamond mines in the Northwest Territories.Footnote 9 In April 2010, it was publicly announced that a new Alberta Law Enforcement Response Team was established in Fort McMurray to combat the increased organized criminal activity in this area.Footnote 10 In 2008, it was also reported that a major drug investigation resulted in the coordinated execution of search warrants and arrests from 17 different communities across Saskatchewan.Footnote 11

Figure 7: Number of STRs per 100,000 people within each regional municipality in Alberta and Saskatchewan (November 2001 to August 2010)

Number of STRs per 100,000 people within each regional municipality in Alberta and Saskatchewan (November 2001 to August 2010)

View the text equivalent for Figure 7

This map illustrates the regions of Fort McMurray, Northern Alberta, Yellowknife Northwest Territories and various areas of Saskatchewan. The map highlights that multiple regional municipalities from these areas have an increased number STRs per capita ranging from 1001 to 6250.


Figure 8: Number of STRs per 100,000 people within each regional municipality in Southern Ontario and Western Quebec (November 2001 to August 2010)

Number of STRs per 100,000 people within each regional municipality in Southern Ontario and Western Quebec (November 2001 to August 2010)

View the text equivalent for Figure 8

This map illustrates Southern Ontario and Southern Quebec. It highlights Toronto and Montreal as the largest urban centres with higher STR reporting per capita compared to other regions and municipalities. The regional municipalities including Niagara Falls and Akwasasne are also identified as having higher STR reporting levels per capita.


It is well known that a very large percentage of Canada's population resides in the Windsor to Montreal corridor. It is not surprising to see several pockets of higher STR reporting per capita around the largest urban centres such as Toronto and Montreal which have been recognized in open source reporting to have significant levels of various organized criminal activity.Footnote 12 One notable reporting hot spot includes the South Western corner of Quebec near Akwasasne. Various open source reporting has identified that this region has been exploited for various organized criminal activities such as contraband smuggling.Footnote 13 Higher STR reporting is also apparent in the regions around Windsor and St. Catharines/Niagara which include some of Canada's busiest land border crossings and casinos.

3. STR Relationships and Trends In Part G Narrative

The previous part of this report focused on overall STR reporting volume statistics by sector, region and per capita. This section explores the content of the STR Part G where reporting entities explain or describe the reasons why they suspect that financial transactions or client behaviours may be associated with money laundering or terrorist financing.

The tables and charts in this section illustrate various trends and statistics concerning the most common reasons for suspicion provided in the Part G narrative section of English STRs reviewed for this report.

Table 4 presents the number of STRs received between 2007 and 2009, from the sectors providing the most reports, and for which we could identify at least one suspicion concept in the Part G narrative section using our text mining technique.

Table 4: Number of STRs by sector containing at least one suspicion concept
Sector Number of STRs containing at least one suspicion concept
2007 2008 2009
Banks and trust/loans 18,077 28,748 15,054
MSBs 12,725 15,650 18,407
Credit unions/caisses populaires 2,039 2,787 3,821
Casinos 740 4,206 3,905
Life insurance 180 175 105
Securities dealers 78 127 133
Real estate 5 9 5
TOTAL 33,844 51,702 41,430

(A) Most Common Single Suspicion Concepts

The charts (Figures 9 and 10) on the next two pages identify the Top 5 most common single suspicion concepts for banks and trust/loans, credit unions/caisses populaires, MSBs and casinos, for the period of 2007 to 2009. The percentages for each single suspicion concept was calculated based on the number of STRs containing it, divided by the total number of STRs containing at least one single concept for that same sector and same year. For example, 9,219 STRs reported by banks and trust/loans in 2007 contained the "cash deposit" single concept, which accounted for 51% of all STRs (18,077) containing at least one concept for the same sector in 2007:

9,219 / 18,077 X 100 = 51%

Consequently, given that each single suspicion concept is independently assessed, and multiple single concepts can be found in one STR, the total of percentages per chart does not equal 100%.

As mentioned in the Report Methodology section, when assessed on their own (i.e. independently from others), single suspicion concepts cannot be easily linked to ML or TF techniques and methods. However, some trends can still be observed in Figures 9 and 10.

For example, it is not surprising that there are many similarities in reported suspicious trends in the banks and trust/loans, and credit unions/caisses populaires industries, as shown in Figure 9, since both sectors offer similar financial services. Nonetheless, there are a few notable differences between the two. The "unknown source" concept, which was one of the commonly reported reasons for suspicion in the banks and trust/loans sector for all three years, was not among the Top 5 for the credit unions/caisses populaires sector in any of those years. Another interesting finding in the banks and trust/loans sector was the emergence of "cash withdrawal" into the Top 5 suspicious reasons for the first time in 2009.

The Top 5 single suspicion concepts for the MSB sector, as shown in Figure 10, remained basically unchanged over time and some appeared to be associated with structuring activity.Footnote 14 This finding was not surprising as many of the MSBs reporting STRs to FINTRAC are money transmitters.

When analyzing the charts related to the casino sector in Figure 10, some notable shifts are observed between 2007 and 2009. Although the single concept "cash deposit/purchase"Footnote 15 remained consistent as the top one in each of those years, there was a significant movement and change in the next Top 4 single suspicion concepts. It is interesting to note that while "chip buy-in"Footnote 16 and "cash exchange"Footnote 17 were part of the most commonly reported suspicions in 2007 and 2008, they dropped off the Top 5 list in 2009.Footnote 18

Although more refining of the text mining vocabulary is necessary for the other sectors, we also analyzed the Top 5 single suspicion concepts for securities, life insurance and real estate sectors. "Third party involvement" was one of the Top 5 single suspicion concepts for both securities and real estate from 2007 to 2009. We also identified that "wire transfer" was one of the Top 5 single suspicion concepts reported in the Securities sector for each of those three years. Life insurance sector reporting revealed that "cheque received" single suspicion concept was commonly identified from 2007 to 2009. Again, these results should only be considered as preliminary and incomplete at this stage, since the vocabulary needs to be further developed. They are meant to provide a sense of what concepts are found in the Part G of some STRs reported by these sectors.

Figure 9: Top 5 single suspicion concepts for the banks and trust/loans, and credit unions/caisses populaires for the period of 2007 to 2009

Top 5 single suspicion concepts for the banks and trust/loans, and credit unions/caisses populaires for the period of 2007 to 2009 Top 5 single suspicion concepts for the banks and trust/loans, and credit unions/caisses populaires for the period of 2007 to 2009

View the text equivalent for Figure 9

These charts illustrate the top 5 single suspicion concepts for banks and trust/loans.

These charts illustrate the top 5 single suspicion concepts for credit unions/caisses populaires.


Figure 10: Top 5 single suspicion concepts for MSBs and casinos for the period of 2007 to 2009

Top 5 single suspicion concepts for MSBs and casinos for the period of 2007 to 2009 Top 5 single suspicion concepts for MSBs and casinos for the period of 2007 to 2009

View the text equivalent for Figure 10

These charts illustrate the top 5 single suspicion concepts for Money Service Businesses.

These charts illustrate the top 5 single suspicion concepts for Casinos.

Top 20 single suspicion concept for all sectors

The following table presents the Top 20 most common single suspicion concepts reported throughout all sectors from January 2003 to December 2009, and the total number of different STRs where such a concept appeared.

Table 5 highlights some interesting findings. Although "third party involvement" did not show in the Top 5 single suspicion concepts for all of the four major sectors (as illustrated in Figures 9 and 10), when results of all sectors are combined for the entire period covered for this report, it is the number one concept. This may be due in part to the fact that this concept applies to a variety of sectors, including the two major reporting sectors in terms of volume (as shown in Table 3), i.e. banks and MSBs. In addition, this concept is usually associated with activities such as cash deposits/withdrawals as well as wire transfers, which are often conducted by third parties. Therefore it is not surprising that, when results are combined, "third party involvement" becomes the number one concept, although closely followed by "below threshold" and "cash deposit".

Most of the single suspicion concepts listed in Table 5 are usually associated with structuring and/or layering activity. As explained previously, while the identification of single suspicion concepts is one of the first steps when developing a text mining methodology, they do have their limitations in terms of linking them to ML or TF activity. Later in this report, we will present results regarding the Top paired suspicion concepts, which provide a higher level of complexity and allow us to further link the suspicious reporting to ML/TF techniques and methods.

Table 5: Top 20 single suspicion concepts found in STRs
Rank Single suspicion concepts Number of STRs
1 Third party involvement 66,953
2 Below threshold 65,751
3 Cash deposit 62,145
4 Multiple wire transfers 58,288
5 Wire transfer 57,190
6 Multiple transaction locations 57,181
7 Multiple transactions 55,161
8 Multiple deposits 37,421
9 Unknown source 34,529
10 Large volume cashs 28,288
11 Previously reported 26,741
12 Cash withdrawal 17,494
13 Unknown purpose 15,223
14 Same day activity 14,141
15 Suspected structuring 13,701
16 Large volume deposit 13,521
17 Multiple transfers 11,665
18 Draft purchase 11,553
19 Cheque deposit 11,457
20 Multiple cheques 9,808

Top 2 single suspicion concepts by region and per capita

The map in Figure 11 illustrates the reporting frequency of the "third party involvement" single concept across the country per 100,000 people for all sectors and for the period of January 2003 to December 2009.

As discussed previously, "third party involvement" is most commonly reported by banks and trust/ loans, credit unions/caisses populaires, as well as MSBs. It is therefore not surprising that some of the highest per capita reporting emanates from Canada's major financial centres. When comparing to Figure 5, we can also observe similar hot spots in rural British Columbia, Alberta, Saskatchewan, and the Northwest Territories. Consequently, it appears that many of the STRs reported in those regions are associated with "third party involvement" activities, and probably involve structuring activity or the use of nominees.

Figure 11: Number of STRs, per 100,000 people, containing the "third party involvement" concept

Number of STRs, per 100,000 people, containing the 'third party involvement' concept

View the text equivalent for Figure 11

This map of Canada illustrates the reporting frequency of the "third party involvement" single concept across the country per 100,000 people for all sectors. The range of the "third party involvement" reporting frequency is from 0 to 321+. The map highlights rural British Columbia, Alberta, Saskatchewan, and the Northwest Territories as regions that have high rates per capita of "third party involvement" single concept.


Figure 12 shows the reporting frequency for the "below threshold" suspicion concept across the country per 100,000 people, also for all sectors, and for the period of January 2003 to December 2009. The "below threshold" concept is often associated with some form of structuring activity below the CA$10,000 threshold for reporting EFTRs and LCTRs, as well as the CA$3,000 record keeping requirement for MSBs. The major financial centres of Toronto, Ottawa, Vancouver, Edmonton, and Calgary are identified as having some of the most frequent reporting of this concept. The region in Northeastern Alberta that has seen high economic growth in the oil sands industry also has some of the highest per capita of "below threshold" reporting.

Figure 12: Number of STRs, per 100,000 people, containing the "below threshold" concept

Number of STRs, per 100,000 people, containing the 'below threshold' concept

View the text equivalent for Figure 12

This map of Canada illustrates reporting frequency for the "below threshold" suspicion concept across the country per 100,000 people. The map highlights financial centres of Toronto, Ottawa, Vancouver, Edmonton, and Calgary as having some of the most frequent reporting of "below threshold" concept. The map also identifies the region in Northeastern Alberta as having the highest per capita of "below threshold" reporting.

(B) Most Common Paired Suspicion Concepts

The charts (Figures 13 and 14), on the next two pages, identify the Top 5 paired suspicion concepts by sector (banks and trust/loans, credit unions/caisses populaires, MSBs, and casinos) for the period of 2007 to 2009.

The Top 5 paired suspicion concepts represented in Figure 13 for the banks and trust/loans, as well as credit unions/ caisses populaires are all related to cash transactions and therefore appear to be indicative of activities related to the placement stage of money laundering. The Top 5 paired suspicion concepts did not significantly change between 2007 and 2009 for the banks and trust/loans. It was similar for the credit unions/caisse populaires, for the exception of the 5th paired concept which was different for the three years.

Again, for MSBs, the Top 5 paired suspicion concepts (Figure 14) remained fairly consistent throughout 2007 to 2009, and were mainly indicative of layering activity. Because of the way the text mining vocabulary was developed to cover all sectors at once, it is suspected that the Top 5 paired concepts for MSBs are found at the same time in the majority of STRs.

The Top 5 paired concepts associated with the casinos showed more variations. For example, the paired concept "cash deposit/purchase chip buy-in" has been increasing since 2007 while "cash deposit/purchase & cash exchange" has been decreasing. In 2007, the paired concepts in positions 3 to 5 were all associated to refining activity, but dropped to lower positions than the Top 5 in 2008 and 2009.

Figure 13: Top 5 paired suspicion concepts for banks and trust/loans and credit unions/caisses populaires for the period of 2007 to 2009

Top 5 paired suspicion concepts for banks and trust/loans and credit unions/caisses populaires for the period of 2007 to 2009

Top 5 paired suspicion concepts for banks and trust/loans and credit unions/caisses populaires for the period of 2007 to 2009

View the text equivalent for Figure 13

This chart identifies the Top 5 paired suspicion concepts for banks and trust/loans for the period of 2007 to 2009.

This chart identifies the Top 5 paired suspicion concepts for credit unions/caisses populaires for the period of 2007 to 2009.


Figure 14: Top 5 paired suspicion concepts for MSBs and casinos for the period of 2007 to 2009

Top 5 paired suspicion concepts for MSBs and casinos for the period of 2007 to 2009 Top 5 paired suspicion concepts for MSBs and casinos for the period of 2007 to 2009

View the text equivalent for Figure 14

This chart identify the Top 5 paired suspicion concepts for MSBs for the period of 2007 to 2009.

This chart identify the Top 5 paired suspicion concepts for casinos for the period of 2007 to 2009.

Top 20 most common paired suspicion concepts for all sectors

Table 6 presents the Top 20 most common paired suspicion concepts that appeared in the same STR for all sectors, and for the period of January 2003 to December 2009. Paired suspicion concepts including "wire transferFootnote 19", "multiple transactions" and "below threshold" are dominant in the Top 10.

The large majority of Top 20 paired suspicion concepts appear to relate to some form of structuring and/or layering activity. It is also interesting to note that while "cash deposit" was the third most commonly reported single reason for suspicion, it only first shows up in 15th position when paired with another single concept. Paired concepts including the "cash deposit" concept are suspected to be mainly associated with the placement stage of money laundering.

Table 6: Top 20 paired suspicion concepts found in the same STRs
Rank Single paired conceptss Number of STRs
1 Multiple wires – wire transfer 50,377
2 Multiple transactions – multiple wires 47,499
3 Multiple transactions – wire transfer 47,487
4 Below threshold – multiple transactions 41,437
5 Below threshold – multiple wires 40,628
6 Multiple transactions – multiple transaction locations 40,530
7 Below threshold – wire transfer 40,225
8 Multiple transaction locations – wire transfer 39,734
9 Multiple transaction locations – multiple wires 39,524
10 Below threshold – multiple transaction locations 37,921
11 Multiple transaction locations – third party involvement 34,008
12 Multiple wires – third party involvement 33,950
13 Third party involvement – wire transfer 32,739
14 Multiple transactions – third party involvement 31,731
15 Deposit – multiple cash deposits 31,475
16 Below threshold – third party involvement 31,472
17 Cash deposit – unknown source 20,364
18 Cash deposit – large volume cash 20,137
19 Cash deposit – third party involvement 16,294
20 Below threshold – cash deposit 15,952

(C) Most Frequently Reported Reasons for Suspicion in a Sample of French STRsFootnote 20

Table 7 identifies the most commonly reported reasons for suspicion in a sample of French STRs submitted between 2003 and 2009 by reporting entities in Quebec, following a detailed manual review of Part G narrative of the STRs. Given that the review was conducted manually by a human being, the combination of concepts and the interpretation was at a more complex level. Although more complex and based on a small sample of French STRs, some of these results are consistent with the trends previously identified in English STRs. For example, the first two reasons for suspicion plus another four out of the 25 reasons involve cash deposits. There are also some differences such as reasons 3 and 9, which appear to be related to refining activity. In addition, there seems to be much more variety in the Top 25 reasons for suspicion, which may due to the higher level of complexity in the interpretation of the data, but also to the small sample. A more thorough review, using the same text mining methodology is, of course, necessary before drawing any firm conclusions or judgements.

FINTRAC's goal is to further refine the text mining technique and vocabulary as well as to conduct more complex analysis to get as close as possible to the interpretation of a human being. This will allow the Centre to analyze vast amounts of STRs at a higher complexity level, without the subjectivity and biases that can be involved when a human being is manually conducting such a review.

Table 7: Top 25 most frequently reported reasons for suspicion in a sample of French STRs from Quebec
Rank Most frequently reported reasons for suspicion in French STRs from Quebec
1 Large cash deposits
2 Even dollar amounts deposited/transferred
3 Bills of small denomination in large amounts
4 Unusual account activity/customer behaviour
5 Suspicious use of ATMs
6 Structuring (wires and large cash) below the $10,000 reporting threshold
7 Customer provides false identification or does not provide any identification
8 Deposits/transfers and immediate withdrawal/depletion of account balance
9 Client exchanges large quantities of small denomination bills for large denominations in the same currency
10 Casino activities/transactions are undertaken by third parties
11 Client/account is subject to previous STRs or reporting
12 Unable to ascertain source of funds
13 Suspicious transactions related to use of Inter Caisse System (client anonymity)
14 Account activity is inconsistent with the customer's stated occupation
15 Frequent cash deposits
16 Multiple cash deposits
17 Client leaves casino without cashing in all/portion of casino chips
18 Client requests transaction that does not correspond to client's casino activity (winnings and losses)
19 Account activity is inconsistent with the customer's banking profile
20 Flow through account(s)
21 Large cash withdrawal
22 Large cheque deposit
23 Third party deposits
24 Multiple transactions when a single transaction would be more efficient
25 Nature of client business poses potential risk

4. Conclusion

Criminals will continue to employ many of the money laundering and terrorist financing methods and techniques described in this report for as long as they believe they can be successful in doing so. FINTRAC is aware that many of these issues are already familiar challenges faced by reporting entities.

Our analysis revealed that many reporting entities appear to be detecting suspicious behaviour and submitting STRs that often revolve around structuring activity and the placement stage of money laundering. While reporting on these activities falls within the legal requirements, reporting entities must keep in mind that money laundering also includes the layering and integration stages. It is acknowledged that there have been some reporting that goes beyond these indicators of money laundering, but those STRs still largely appear to be the exception for many reporting entity sectors. With risk-based approach compliance obligations that came into force in June of 2008, reporting entities are now required to spend more effort to identify, assess and conduct ongoing monitoring of their highest ML and TF risks. It is hoped that FINTRAC will observe an overall increase in the level of variety and sophistication in STR reporting in the future.

It is anticipated that this will be the first in a series of FINTRAC analytical publications focusing on STRs. Additional and more complex analysis of all STRs will be conducted by FINTRAC using a more developed text mining methodology, and results will be provided in future reports similar to this one. In addition, we will be seeking the input of reporting entities regarding other possible themes for such reports focusing on STRs. Although there are many variables that will need to be taken into account and analyzed further, we recognize that there may also be opportunities to conduct comparative analysis with suspicious transaction reporting trends in other jurisdictions with similar financial systems.Footnote 21

FINTRAC hopes that this publication will further assist reporting entities in detecting and reporting suspicious transactions, as well as perhaps improving the quality of the information provided in STRs. This will, in turn, allow the Centre to produce financial intelligence which will continue to be relevant to our domestic and international anti-money laundering (AML)/anti-terrorism financing (ATF) regime partners.

Annex 1: Characteristics of a good STR

FINTRAC intelligence analysts, with several years of operational experience using STRs in case disclosures,Footnote 22 have identified a number of characteristicsFootnote 23 of analytical value that should be included in STRs when possible:

Main STR subject is adequately identified – additional identification information provided anywhere in the report that, when combined, can uniquely identify him/her;

Occupation/employer information is present – information regarding the individuals' occupation or employer is present in the report;

Accurate depiction of the transaction(s) – is the transaction(s) depicted accurately in amount, type, etc;

Time frame of financial activity is defined – a time frame is identified and clearly defined surrounding the 'suspicious' transaction activity;

Presence of ML/TF indicators – Part G narrative of the report identifies indicators of money laundering and/or terrorist financing;

Potential predicate offence is identified, if known – Part G narrative of the report identifies any potential predicate offences of ML (i.e. fraud, drug trafficking, etc);

2nd / 3rd parties are adequately identified – Part G narrative of the report identifies 2nd or 3rd parties to the transactions to the best of the ability of the reporting entity;

Relationships (business or personal) are clearly defined – Part G narrative section of the report identifies relationships between individuals and/or entities and defines them to the best ability of the reporting entity; and

Presence of information in Part H – Part H of the STR contains information regarding relevant action taken by the reporting entity.

The complete and consistent reporting of client details (name, address, identification documentation, date of birth, etc.) ensures that FINTRAC has accurate information to search its data holdings and properly identify the conductors of various financial transactions. Using the information in an STR, FINTRAC can also refer to open source information (e.g. media) to identify and confirm various links. A detailed description including, when possible, information regarding potential predicate offence of ML or TF and why the reporting entity identified the transaction as suspicious, is extremely valuable to assisting FINTRAC intelligence analysts.Footnote 24

Annex 2: Sample cases with STRs playing key role

As indicated earlier, between 2006 and 2009, an average of 72% of FINTRAC case disclosures to law enforcement and/or security agencies included at least one STR. This section of the report provides three examples of cases where STRs played a pivotal role in assisting FINTRAC to meet the threshold of reasonable grounds to suspect that the transactions included in the case were related to money laundering or terrorist financing. Sanitized examples of STRs used in these cases are also provided.

Case example #1
STR providing good overview of all known suspicious transactions and behaviour

Voluntary information received from a law enforcement agency indicated that a number of individuals, suspected to be part of an organized crime group, were under investigation by various law enforcement agencies in Canada. These individuals were alleged to be involved in the importation and distribution of cocaine. It was also suspected that a number of businesses were used to facilitate the laundering of illicit proceeds.

FINTRAC's analysis revealed a number of transactions associated with seven of the individuals identified by the law enforcement agency. Four additional individuals and eight businesses, not previously identified by law enforcement, were also found to be possibly associated with this organized crime group. The businesses suspected to be involved in the scheme appeared to be in the real estate, food and entertainment, or financial services industries.

Two individuals suspected to be family members (one of them previously reported in the media to be under an outstanding arrest warrant relating to conspiracy to import and traffic narcotics) conducted multiple large cash deposits in the accounts of various businesses for which they held various officer positions (e.g. Director, President, and Secretary). These deposits were often followed by wire transfers to other associated businesses, possibly in an attempt to layer the funds, that is to hide the money trail. In other instances, one of the two individuals purchased bank drafts payable to self, redeemed them, and purchased further drafts to self. A total of over 30 draft purchases were conducted in this fashion and totalled over CA$700,000. Other drafts were purchased and made payable to some businesses, including one draft which was suspected to be for a large hydro payment. The financial institution, reporting this transaction, suspected that one business was the owner of a property that may be used in a marijuana grow operation.

The transactions associated to these individuals and businesses, which were conducted during a period of five years, totalled over CA$6 million. One STR submitted by the reported entity was particularly key to this case. The STR provided a very useful overview of all the suspicious transactions and behaviour of this client at their institution. FINTRAC disclosed all relevant designated information to law enforcement agencies investigating the individuals and businesses involved in this scheme.

Suspicious Transaction Report from Case Example #1

PART G: Description of suspicious activity

The key information provided in this STR assisting FINTRAC in developing a case included the following:

Case example #2
Reporting entity's effective internal risk-based approach process initiated STR

A financial institution submitted a number of suspicious transaction reports to FINTRAC pertaining to an owner of a business involved in the entertainment industry. The financial institution indicated that the amount of funds deposited to the account within a short time period was excessive even for a cash-intensive business such as the one in question. Cash deposits were conducted by the business owner, employees, and the owner's spouse. The financial institution reported that the bulk of the funds deposited to the business account were immediately remitted, by way of bank draft, to an account held by the business at a second financial institution. Given that the cash could have initially been deposited directly to the account at the second financial institution, this type of activity suggested an attempt to layer funds. Ultimately, the financial institution could not verify the source of the funds deposited, and also found it suspicious that the business account exhibited minimal business-related expenditures, and no merchant credits.

As part of its customer due diligence and risk assessment processes, the financial institution conducted further research on this client who had been identified as posing a high money laundering risk, and relayed its suspicious findings to FINTRAC via an STR. The financial institution discovered that the business owner had previously been charged, although not convicted, on several drug trafficking charges in a foreign jurisdiction. In addition, the owner had served a prison sentence for tax evasion in the foreign country, had paid a substantial monetary penalty, and had subsequently been deported back to Canada from the United States.

The additional background information collected by the financial institution as part of its risk assessment process proved valuable to FINTRAC. Coupled with suspicious transaction reporting, the information provided FINTRAC with reasonable grounds to suspect money laundering activity. The financial transactions of the individuals and businesses involved were provided to the appropriate law enforcement agency for investigation.

Suspicious Transaction Report from Case Example #2

PART G: Description of suspicious activity

This case involved a total of 14 STRs. The key information provided in this STR assisting FINTRAC in developing a case included the following:

Case example #3
FINTRAC case disclosures initiated by STRs

FINTRAC received a significant number of suspicious transaction reports (STRs) from various reporting entities detailing US to CA currency exchanges. Although the reports pertained to currency exchanges conducted by a variety of individuals, the suspicious activity reported to FINTRAC appeared to be common to most, if not all of the subjects. This activity included individual customers conducting transactions at different branch locations within a limited time period, structured transactions, multiple customers sharing common identifiers (such as an address and telephone numbers) and occupations which did not justify the level of financial activity. STR reporting also indicated that many transactions appeared to be conducted by a group, or clusters of groups, of customers.

Certain STRs identified suspected associates of customers engaged in suspicious currency exchanges, which assisted FINTRAC in identifying what appeared to be networks of individuals engaged in money laundering activity. Moreover, the descriptions of suspicious financial activity contained in the STRs assisted FINTRAC in identifying patterns which benefited the Centre's analysis. This analysis resulted in several proactive disclosures to law enforcement. FINTRAC had not previously received any voluntary information from Canadian law enforcement on these individuals. The case was primarily initiated due to STR reporting.

Following receipt of these disclosures, a Canadian law enforcement agency provided voluntary information to FINTRAC. The information pertained to a criminal organization suspected of being involved in drug trafficking and money laundering. Several individuals, who were subjects of the aforementioned STRs from reporting entities, and subsequently subjects of FINTRAC disclosures, were identified in this information. According to law enforcement, the criminal organization was involved in transporting cocaine and marijuana across the U.S./Canada border, and employed couriers to collect, transport, and deliver cash across North America.

Further analysis by FINTRAC revealed a network of individuals and entities across Canada, including businesses offering a variety of financial services such as currency exchanges and wire transfers, as well as businesses involved in jewellery and/or precious metals. In addition to frequent and large US to CA currency exchanges, suspicious financial activity also included structured cash deposits followed either by purchases of bank drafts made payable to MSBs, or EFTs to entities located in Central America and South Asia.

The extensive suspicious transaction reporting on the part of various reporting entities was instrumental to FINTRAC's analysis, and resulted in disclosures to law enforcement at an early stage of the investigation. The eventual multi-agency, international law enforcement investigation resulted in the seizure of millions of dollars in cash, drugs, and property and ultimately, the dismantling of a global criminal organization involved in cross-border drug trafficking.

Key points about the information provided in the STRs leading to multiple disclosures included:


Return to footnote 1 For the purpose of this report, the term STRs comprises both regular STRs and attempted STRs, the latter totalling approximately 6,000 reports.

Return to footnote 2 Some sectors were combined in two groups since, for example, trust/loan services are often offered by banks. Given that credit unions and caisses populaires have a similar business model, they were also combined. Crown agents were grouped with banks or MSBs, as appropriate

Return to footnote 3 Refer to the list of sectors identified on p. 6.

Return to footnote 4 It should be noted that STR reporting volumes should not be interpreted to be a direct representation of the frequency in which a certain business sector is exploited for ML/TF activity.

Return to footnote 5 Nine of the ten reporting entities from this category were banks, while the 22nd reporting entity was a trust and loan company.

Return to footnote 6 In most cases, several different neighbouring communities/municipalities actually comprise one region. These 288 regional municipalities were based on Statistics Canada Census Divisions.

Return to footnote 7 ROYAL CANADIAN MOUNTED POLICE. "RCMP Seize Helicopter Used for Organized Crime",
Press Release by RCMP Border Integrity Program. Nelson, B.C., February 1, 2010.
ROYAL CANADIAN MOUNTED POLICE. "Fort St. John RCMP Continue to Target Drug Trafficking",
Press Release by Fort St. John RCMP, July 15, 2008. "Gang Activity in Fort St. John", Fort St.John, B. C.,
May 1, 2009, Online News Source, Energeticcity.ca] (consulted October 25, 2010).

Return to footnote 8 MATAS, Robert. "Marijuana Legalization: Proposition 19 could kill B.C's buzz", Globe and Mail, Toronto, ON, October 30, 2010.

Return to footnote 9 CRIMINAL INTELLIGENCE SERVICE CANADA. "National Monitored Issues; Organized Crime and the
Diamond Industry", 2004 Annual Report on Organized Crime in Canada, June 2004. "Prosperity behind Yellowknife's soaring crime rate, report says", CBC News, Online News Source, September 5, 2006 (consulted October 29, 2010).

Return to footnote 10 "Fort Mac unit will target organized crime: Northern Alberta hub next logical choice, police say", Edmonton Journal, April 21, 2010.

Return to footnote 11 "Police arrest 55 people in massive drug bust", Canwest News Service, Online News Source, October 17, 2008 (consulted October 29, 2010).

Return to footnote 12 CRIMINAL INTELLIGENCE SERVICE CANADA. Annual reports from 2001 to 2010.

Return to footnote 13 GOVERNMENT CONSULTING SERVICES. "2006-07 Formative Evaluation of the Akwasasne Partnership Initiative", Public Safety and Emergency Preparedness Canada, February 2007.

Return to footnote 14 Structuring activity was the most common technique identified in the Money Laundering and Terrorist Financing Typologies and Trends in Money Services Businesses, FINTRAC, October 2010, available on FINTRAC's website: http://www.fintrac-canafe.gc.ca/publications/typologies/2010-07-eng.asp.

Return to footnote 15 "Cash deposit/purchase" refers to cash deposits into casino front money accounts and cash purchases of casino chips.

Return to footnote 16 "Chip buy-in" also refers to purchases of casino chips but using various methods of payment not defined in the text such as credit card, bank draft, cheque or cash.

Return to footnote 17 "Cash exchange" refers to currency exchanges and cash being transferred between individuals (i.e. changing hands).

Return to footnote 18 These three single suspicion concepts are suspected to be associated with layering activity which were also observed and discussed in FINTRAC's Money Laundering Typologies and Trends in Canadian Casinos, November 2009, available on FINTRAC's website:
http://www.fintrac-canafe.gc.ca/publications/typologies/2009-11-01-eng.asp

Return to footnote 19 It should be noted that some major reporting entities use the term wire transfer to describe EFTs below the CA$10,000 EFT reporting threshold.

Return to footnote 20 As mentioned earlier in this report, the majority of French STRs were submitted by caisses populaires located in the province of Quebec, although other reporting entities in Quebec also provided some STRs. Therefore, the stratified sample included STRs provided by various sectors in Quebec. Once the text mining vocabulary will be developed for French STRs, all of them reported across Canada will be analyzed.

Return to footnote 21 For example, our partner FIU in the United States, FinCEN, regularly publishes Suspicious Activity Report (SAR) Reviews. The June 2010 document titled "SAR Activity Review – By the Numbers" indicated that 7,298,462 SARs were submitted to FinCEN between January 1, 2002 and December 31, 2009. During a slightly longer time period, FINTRAC received over 300,000 STRs. If one does a very rough comparison and takes into account the proportional size of our economies and population, FINTRAC is receiving an equivalent of approximately 4% of FinCEN's SARs volume. Although this may not seem unreasonable, given that there are differences in the business sectors with suspicious transaction reporting obligations between Canada and the United States, other variables would need to be factored in before making any conclusions.

Return to footnote 22 Examples of how STRs contributed to FINTRAC's case disclosures are provided in Annex 2.

Return to footnote 23 The characteristics can be found in mandatory fields or in Part G narrative of STRs.

Return to footnote 24 As a reminder, please note that a detailed list of both common and industry specific indicators of suspicious activity for money laundering and terrorist financing can be found in the following document: Guideline 2: Suspicious Transactions, available on FINTRAC's website at:
http://www.fintrac-canafe.gc.ca/guidance-directives/transaction-operation/Guide2/2-eng.asp.

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