Posted by & filed under AML General, Negative News.

AML Efficiency

Never-ending monitoring alerts.  Flipping from system to system to find customer information, transaction details, and negative news.  Documenting searches and investigation reports.  SAR filings.  Model validation.  Annual risk assessments.  Hiring new analysts to replace the ones that jumped to another bank for more money.  Audit one month, regulatory examination the next.   Constantly shifting priorities.

This sums up AML compliance for the past decade. No wonder every AML leader is looking to make programs more efficient. But is AML efficiency even possible? If it is, how?


What Is Inefficient About AML?

There are two primary causes of AML inefficiency:

  1. False Positives:  More than 80% of transaction monitoring alerts are false positives. Same goes for sanctions, watch list, and negative news results.  Yet all these false positives must be reviewed and resolved.
  2. Documenting case files with proof that every monitoring, sanction, and negative news alert was reviewed takes more time than the review of the alert in the first place.  Endless screen shots, copying, pasting, creating PDFs, all add considerable time and is not improving the way banks detect and report suspicious activity.

Compiling all this information takes time.  When this time is added up over the course of a day, a week, a month, and a year more than 60% of the work of alert analysis, case investigation and EDD reviews is actually copying, pasting, and “papering” files.

All jobs have components that are repetitive, necessary, and boring.  But, when those components account for most of the work time, something is wrong!

We cannot however simply stop all the documenting. Managers need to review work, audit must audit and regulators must examine.  The case file is the evidence each needs to assure the work and the decisions reached were reasonable.


Artificial Intelligence Solutions Are Mostly Just Hype


A day doesn’t go by without an article about the promise of Artificial Intelligence or “AI” and how it will transform transaction monitoring.  It will be years before AI has a widespread impact on improving AML (more on that here).

Machines will not replace the need for qualified humans to make decisions about what is suspicious. Machines are a long way from replacing human brain function.

However, what machines can replace are monotonous manual tasks.


How to Fix Reliance on Manual Processes

Think for a moment what transpires when an EDD analyst searches for negative news:

  • She must devise a search approach using key words she chooses herself or continually copy and paste a standard search string.
  • She then scrolls through some number of results – how many is anyone’s guess.
  • She opens some of the links.
  • She may re-do the search if the initial results she sees don’t appear useful.
  • She will click on more links.
  • She scans numerous articles.
  • She may decide something is relevant, but spends more time deciding what isn’t relevant.
  • She then either takes a screen shot of the article or she copies and pastes the text into a Word file and then converts it to a PDF.
  • And, on and on and on she goes.

Ponder for a moment, the inefficiency and risk of all this. Think of the time spent, over and over on this same process, and it is just one part of AML analysis.

This is where machines can help.  Applications that automatically capture the images on an investigator’s screen, enable one-click report creation, and standardize alert reviews all accelerate work.

This is all possible, in fact it is happening today and this is where AML officers can begin to bring better efficiency now as we wait for the promise of AI to arrive at some unknown point in the future.

Posted by & filed under Negative News, Research & Investigation.


The amount of digital information available to us at all times is continually increasing, and it is not all Pulitzer worthy.

It is almost impossible to watch cable news and not hear about fake news.  Often a hyper-political term that is interpreted different ways, actual fake news describes stories presented as true, but have no basis in fact.  There is no “spin” or subjectivity component; the stories are provably false.

As recently highlighted in, fake news can add additional challenges to the already complex role of compliance professionals.  Fake news stories are often negative in nature, and identifying negative news is a critical element for investigators and compliance officers.

Not a New Problem


While the term “fake news” has recently gained a lot of attention, the task of vetting the reliability of news and Internet sources has been part of the daily job of analysts for years.  During the course of any investigation, an investigator is faced with the task of determining whether information is found on a subject of interest.  Is the source a reputable newspaper or media outlet? A displeased client posting on a consumer complaints board?  These are the types of decisions analysts make whether they realize it or not.

While completely nonfactual news does add an additional wrinkle to source vetting, the process of vetting the credibility of a news source remains relatively unchanged.

Determining the Reliability of a Website

A useful resource for vetting source reliability is Northern Michigan University’s guide to Evaluating Internet Sources.  This website provides a handy resource that outlines the below six elements to consider when evaluating a website for its reliability of information.

Authority Is it clear who is responsible for the contents of the page?

Is there a way of verifying the legitimacy of the organization, group, company or individual?

Is there any indication of the author’s qualifications for writing on a particular topic?

Is the information from sources known to be reliable?

Accuracy Are the sources for factual information clearly listed so they can be verified in another source?

Is the information free of grammatical, spelling, and other typographical errors?

Objectivity Does the content appear to contain any evidence of bias?

Is there a link to a page describing the goals or purpose of the sponsoring organization or company?

If there is any advertising on the page, is it clearly differentiated from the informational content?

Currency Are there dates on the page to indicate when the page was written, when the page was first placed on the Web, or when the page was last revised?
Coverage Are these topics successfully addressed, with clearly presented arguments and adequate support to substantiate them?

Does the work update other sources, substantiate other materials you have read, or add new information?

Is the target audience identified and appropriate for your needs?

Appearance Does the site look well organized?

Do the links work?

Does the site appear well maintained?

Not mentioned, but inherent in all of these elements, is the requirement for internal judgment, experience, and common sense.

Technology to the Rescue! </sarcasm>

officeMany large Internet companies, like Google and Facebook, have undertaken efforts to reduce fake news (which Facebook defines as “clear hoaxes spread by spammers for their own gain”) in their products.   While one would think that these companies would implement the latest machine learning or artificial intelligence technology to easily root out the problem, it seems the most effective approaches have been providing tools that allow users to flag potentially false stories, and the use of human curators to review stories and sources.

From an investigative resource perspective, other websites have attempted to provide a solution in the form of “fake news checkers.”   Sites like Media Bias Fact Check attempt to not only identify sources associated with the publishing of fake news, but also seek to identify bias in news sources along the political spectrum using the following methodology.  This can be a very useful tool if you are unfamiliar with a website that may have a strong political leaning.




While the above sources can be helpful, it is extremely important to emphasize that the authors and groups who categorize websites should not be immune from the same analysis as outlined above.


While there has been an increase in the prevalence of completely nonfactual news, the techniques used to verify credible information online remain relatively unchanged.  The ever increasing amount of digital information will continue to generate new and evolving issues, but having access to this information is a net benefit to compliance, AML, and investigative professionals.

Posted by & filed under AML General, Negative News.

Experienced AML professionals know that negative news is the most useful source to uncover risk. Transaction activity alone does not tell the whole story; negative news completes the picture.



Yet financial institutions direct enormous time, money, and people to transaction monitoring, while allocating a small fraction of attention to negative news. Why take such a risk?

A news report about a customer’s involvement in a corruption investigation tells an AML investigator a lot more than a transaction monitoring alert flagging a $25,000 wire transfer from New York to Bermuda.

Nothing grabs regulator and law enforcement attention faster than a news story about money laundering that names banks. AML history is stacked with examples of regulators reading about some alleged or real crime and then hunting down the banks where money was funneled.

Riggs, Wachovia, Washington Mutual, Citibank, JP Morgan, HSBC, Deutsche Bank and numerous others have collectively paid billions in fines and spent billions to re-build AML programs after regulators and law enforcement sprang into action based upon news reports.


negative-news-questionIs Monitoring Negative News Possible?

Banks expend enormous financial and human resources on systems that monitor transactions. These systems constantly scour activity to find red flags and risk. Why don’t banks monitor negative news in the same way?

There are at least three reasons.

  1. A misperception that there is no way to monitor negative news in real time like is done with transaction monitoring.
  2. Fear among AML management that even if real-time monitoring of negative news was possible, the added work would overwhelm staff.
  3. Mistaken belief that “running batches” of names against a database is monitoring negative news.


Screening Databases is Not Negative News Monitoring

When banks take a list of names (a “batch” as many call it) and compare that list to a Risk Database, they are not monitoring negative news. Why?

Monitoring is defined as, “the continuous observation of an ongoing activity to gather information.” The key phrase here is “continuous observation of ongoing activity.” This is what transaction monitoring systems do, but not what negative news databases do.

Existing risk databases are not constructed to capture negative news in real-time and thus are not continuously observing ongoing adverse media for AML risk.

These databases add small numbers of negative news records well after the news has occurred. The significant limitations of these databases mean that 90% of the negative news needed by an AML investigator is not in these files.

So, when a bank “runs a batch” against a database thinking it is “monitoring negative news,” it is not. It’s only comparing a list of names to a small list of historical, and often outdated, records.


Real Negative News Monitoring

To properly monitor negative news, banks need to be looking at information as it is published.

To be considered truly effective, negative news monitoring must:monitor

  1. Monitor in real-time all published information that identifies financial crime and reputation risk;
  2. Weed out irrelevant articles;
  3. Be presented in way that enables AML investigators to work quickly;
  4. Automate supporting documentation and evidence; and,
  5. Reduce work time of investigators and analysts.


Since AML began nearly 20 years ago, every analyst, investigator and manager knows that negative news is the best source of risk information.

Until now, effectively monitoring negative news has eluded AML.  It is time that changed, and it has. Contact me to learn how.

correspondent banking investigation

Posted by & filed under AML General, Negative News, Research & Investigation.

It is well known that correspondent banking relationships result in heightened money laundering and terrorist financing risks, and deficiencies in AML programs relating to correspondent banking clients have led to billions of dollars in regulatory fines.

While there is a multitude of literature and commentary on the AML risks and challenges associated with foreign correspondent banking,  there is not much practical guidance for an AML investigator who is tasked with a correspondent bank investigation.

Below are six important tips for AML analysts conducting an investigation into a correspondent banking client.


1. Due Diligence

Conduct due diligence searches on the bank, its counterparty, and any additional names included in the payment.

Analysts should ask the following:

  • Does the relationship between the parties make sense?
  • Are any of the parties PEPs, sanctioned, or on any watchlist?
  • Has any negative news been identified on any of the parties?


2. Transactional Activity

Conduct searches for additional transactional activity involving the bank, its counterparty, and any additional names included in the payment.  Do not limit the search to the names; include account numbers, addresses, any additional information in the payment details, etc.

Analysts should ask the following:

  • Do the transactions make sense?
  • Do the transactions appear to be structured or conducted in such a way as to avoid a reporting requirement?
  • Do the individuals or entities appear to have a legitimate reason for transacting with each other?


3. Typologies

Consider known typologies involving the types of transactions, counterparties, industries, geographies, that are involved in the investigation.

Analysts should ask the following:

  • What geographies are involved, and do they make sense?
  • Does the activity appear consistent with any known typology or red flag?


4. Requests for Information

If possible or applicable, utilize your bank’s process to contact the bank’s affiliate branch for KYC, onboarding information, and an anticipated activity profile on the parties to the transactions.

Analysts should ask the following:

  • What information was provided at the time of onboarding?
  • What other activity is occurring within any additional account(s)?
  • Does the affiliate have any concerns with the client?


5. 314(b) Requests

Utilize the FinCEN 314(b) process, if your bank and the counter financial institution are participants.

Analysts should ask the following:

  • What information was provided at the time of onboarding?
  • What other activity is occurring within any additional account(s)?


6. Next Steps

Consider whether the activity appears to be unusual or suspicious, and what actions should be taken.

Analysts should ask the following:


Investigations into correspondent banking clients may initially appear to be a bit daunting, as client and transaction information are not always as easily accessible as with domestic clients.  These types of investigations are more challenging to get the “full picture” as to what is occurring in the account.  The tips above should provide some guidance as to how to approach these investigations.

Interested in seeing a better way to search for negative news on correspondent banking clients and the parties involved in your investigation?  Contact us here to set up a live demo of the TransparINT platform.

Posted by & filed under AML General, Negative News.

old aml technologyMany of us in AML are old.  Old enough to say things to our teenagers and college aged kids like, “When I was your age they played videos on MTV,” and, “What are you talking about, ‘The Safety Dance’ is a great song.”

Turns out today’s generation may fail to see the appeal of hair bands in leather pants wearing bandanas around their thighs.

To anyone paying attention, it should be clear there is also a growing generation gap in AML.   The eye rolls the new generation directs our way have a lot to do with the enormous technology gap plaguing financial crime compliance.

Here is a quick exercise for those in AML management who grew up watching movies where Burt Reynolds had a leading role:

Look at the software applications your department is using for transaction monitoring and adverse media research.  Then look at the age of the AML analysts and investigators recently hired and ask yourself this; “What grade were these folks in when this monitoring system and negative news application were developed?”

If you have anyone younger than 27 years old, the systems they are using were developed way back when they were in the 4th grade!   A recent college graduate entering the AML workforce was just beginning kindergarten when your monitoring system and negative news application became the standard in AML.

I know some readers may be thinking, “Yes, but the version of (fill in the blank) monitoring system or negative news application isn’t the same as it was 15 years ago.”

Really?  Whatever small changes have been made are still years behind what today’s newer generation of AML workers expect from technology.   Why has technology changed nearly every aspect of our lives, except it seems AML?

Whether it’s a new phone app, a new feature on our car’s video console, or how we order food, all of us expect technology in our lives to be simple, intuitive and efficient.

Applications makers don’t send us user manuals.  We expect that within a minute or two we will figure out how to use something new and, if we don’t, we drop it and move onto something simpler.

Yet in AML, the older generation accepts dysfunction, inefficiency, and the risks that come with it. 

The younger generation has different expectations.  We know they want their work to give them a sense of meaning and purpose.  They want fulfillment beyond a paycheck.  They are intrigued by new technology and the prospect of change.  They have a lower tolerance for frustration.  Maybe all this is for the better.  I don’t know.  That isn’t the point.

The point is, that if AML technology doesn’t improve – really improve – and start providing AML workers with much better tools, financial institutions, regulators, and policy makers will never keep pace with the growing risks.

New AML applications should be simple to use, regularly updated and fast.  Most importantly, AML applications should be designed to enable analysts to improve the quality and speed of their work.  

Existing monitoring and adverse media systems require AML users to navigate confusing and sluggish interfaces that look and feel like they are running 15-year-old technology, which, unfortunately they are.

When we use apps on our phones, we expect them to work “smoothly.”  There is no need to define what is meant by “smooth” – we all know what it looks and feels like.  In 2017, applications used by AML and Financial Crime analysts should be smooth too.  Instead they are clunky and

make users feel as though they are working against the application, in a struggle against wasted time and inefficiency.

Five years from now, will AML be using new applications and systems that look and feel like the technology we expect in our personal lives, or will we be seeing the current scene of dysfunction and inefficiency play itself out over and over again?

That reminds me a great movie all kids today should see, “Groundhog Day,” released in 1993 and starring Bill Murray (a really funny old guy).



Posted by & filed under AML General, Negative News, Research & Investigation.

It has recently been reported that a leaked draft document from HSBC’s monitor identified 13 British customers linked to Islamic terrorist groups in Syria.  While it is impossible to make any determination on HSBC’s AML policy without the full details of the report, this leak highlights a challenging topic for all banks.

There is no official number, but according to British authorities, approximately 850 people from the UK have traveled to support or fight for jihadist organizations in Syria and Iraq.  In many cases, those who have gone to Syria or Iraq have done so in clusters from the same regions or in a close time frame.  The UK is not alone, according to the EU’s Commissioner for Justice, Vera Jourova, about 6,000 Europeans have joined jihadi groups.  The US has also had hundreds of Americans travel to Syria And Iraq to fight.



Red Flags

Dennis Lormel, former FBI Terrorist Financing Operations Chief, wrote a detailed piece covering the Islamic State and like-minded terrorist groups from an AML perspective.  In the article he identified the below financial red flag taken from real-world case studies.

Financial Red Flags to Terrorist Financing

  • IP logins in areas of conflict such as near the Syrian border, to include Jordan and Lebanon, but particularly in Turkey
  • Periods of transaction dormancy, which could be the result of terrorist training or engagement in combat
  • ATM cash withdrawals in areas of conflict
  • Wire transfers to areas of conflict
  • Charitable activity in areas of conflict, particularly in Syria
  • Social media postings (many Western foreign fighters use social media)

The main challenge facing banks regarding terrorist financing is that in many cases it does not take much money to fund terrorist acts.   This makes it difficult for banks to detect because the account activity appears similar to what one would expect from a normal checking or savings account.  Many recent attacks were conducted on a budget of thousands, or even hundreds of dollars in some cases.

It is unfortunate, but sometimes there are only actionable step after a terrorist attack has occurred.  Specifically, the bank should identity and review the activity for all accounts connected to the alleged terrorist, and also identify transactions with any other parties that appear unusual or who may be involved in similar activity.  Suspicious activity reports (“SARs”) should be filed on all identified unusual activity.  This is also a good opportunity for the bank to go back look at the client’s activity to determine if there were gaps or red flags that were missed and could be corrected with enhanced procedures.

Open Source Data


Publicly available open information is continually growing and is an excellent source to identify individuals or companies with any direct or indirect terror links.  This can include domestic and international news, regulatory and law enforcement sources, social media, and corporate registries to name a few.

Specifically related to the topic of ISIS links in the UK, the BBC has complied an excellent public data set of Britons who have died, been convicted of offenses relating to the conflict, or are still in the region.  The information was compiled from open sources and BBC research.

The Counter Extremism Project (CEP) also maintains a listing of foreign fighters as part of their Global Extremist Registry.

While the BBC and CEP make this information available in visually pleasing and interactive formats, it can be difficult to work with for AML or investigative purposes.

If you work for a financial institution and would like this information in a more structured format, please send me an email at and I will be happy to send you a Excel file of the extracted data.


Posted by & filed under AML General, Negative News.

Artificial Intelligence or “AI” is the new buzzword in Anti-Money Laundering.  Nervous?

terminatorRecent AML news would have you believe we’re on the cusp of dramatic change that will wipe out thousands of compliance jobs.  AI will then transform those few remaining workers into Arnold-like Model T-101 Terminators annihilating alerts, cases, and SARs with emotionless robot-like precision.

My take is different. There are two likely outcomes of AI.

  1. AI will cure disease, advance all science and then lead mankind to destroy itself.
  2. AI will create more AML work, not less.

Let’s gloss over the first of these inevitabilities.  Once super AI is created and machines actually learn at speeds incomprehensible to human understanding, two things will happen:  First, machines won’t need us anymore, and second the political, economic, and social upheaval caused by AI will lead to cataclysmic war and famine.

But don’t worry, experts say this “super AI” is still probably 50 years away.


AI Impact on AML

For AML, the expectation is that AI will cure the overwhelming inefficiency the plagues us.  Billions of dollars are wasted as AML teams remain buried under false positives, hunt down information from clunky old databases, and make inconsistent, and sometimes really bad decisions.

An AI driven system that can gather data instantly and be programmed to make decisions when given a set of simple facts will no doubt change AML.  But this “weak AI” as it is known, won’t reduce AML workloads, it will actually increase them.

Let’s start with something everyone in AML agrees about:  There is too much time spent on finding stuff.  Take alerts and cases, for example, where 80% of the time on each matter is spent not on actual analysis and investigation, but on gathering transaction records, KYC information, and risk information such as negative news.  Or how about the AML risk assessment, which is just mostly a multi-month (or yearlong) data gathering exercise.  If AI can eliminate this wasted time and gather needed information in seconds, then indeed certain AML work will be reduced.


Peak Work?

peak-oil-graphIt wasn’t that long ago that the smart minds of science predicted the world was soon to run out of oil. The last 10 years has made it obvious that this theory, known as the “peak oil,” was utterly wrong.

A similar view, call it “peak work,” is what creates the hope that AI will transform AML:  All the work that needs to be done in AML is already being done, but this “real” work is overtaken by the “busy” work.  AI will eliminate the “busy” work, and we will finally be able to focus just on what remains (the “real” work) and banks will then start shrinking AML departments.

There is a problem with this thinking.  The “real” work of AML hasn’t even yet begun.


We Fail to Detect Most Money Laundering

The U.N. estimates that up to $2 trillion dollars a year is laundered.

Add together total money seized by credible law enforcement agencies from around the world each year and the amount of funds involved in activity reported on SARs and you get much, much less than the actual amount of money laundered.  The “real” work is to find this money.

So yes, weak AI will clear away a lot of the clutter, and it may even be able to report – without the need for human input – simple suspicious activity like cash structuring.

But imagine the activity that will be uncovered once the problem of disparate and inefficient data gathering is solved.  What will happen in banks when unknown customer connections are revealed or when data from innocuous looking wire transfers exposes critical information that up to this point is hidden?

Instead of shrinking AML departments, financial institutions will instead be hiring more investigators to deal with the flood of new, heretofore unknown (and more complex) suspicious activity.  And despite what AI developers may say, computers will not spontaneously learn how to analyze and investigate all this new activity.  It will take years for weak AI to work in banks and then it will take years for this weak AI to become super AI (general intelligence where machines can replicate or surpass human thinking).

Another thought:  Won’t the criminals, who are as well funded (or better funded) than financial institutions also be developing AI to suit their needs?  Perhaps their AI will be better than our AI.

Maybe we better hope John Connor really does take down Skynet.

Posted by & filed under AML General, Negative News.

flip-phoneIt was reported a few weeks ago that Andrew Luck, the star quarterback for the Indianapolis Colts celebrated his new $140 million contract by upgrading his flip phone to a… new flip phone.  It seems Luck is happy with a device that most of us last used a decade ago.

Hearing this took me back to 2003 when I was the AML officer at Riggs Bank and my investigations manager came into my office snapping pictures with his new flip phone.  Wow, a camera in a phone.  That was new back then.

Technology was beginning a breakout period that over the next decade would significantly change nearly every aspect of our lives, except AML compliance.

It was right around this time in 2003 that I signed a $300,000 a year contract for Riggs to subscribe to what remains the AML industry’s leading “Risk Intelligence Database.”  Finding negative news, PEPs, and sanctioned parties was emerging as a critical component of AML.

Nearly everyone (except a quirky All Pro quarterback) adapts to ever evolving technology.  The same cannot be said for AML however, because in over 10 years there has been little to no change in the tools available to AML investigators.

Take how we look for negative news and other risk relevant information: Institutions use applications developed in the 1990’s that still rely on the same 1990’s technology. No one reading this watches a tube television or is waiting for the new release of the latest Palm Pilot, yet AML officers accept using technology that is outdated, and actually undermines a critical component of AML compliance.  Why would they do that?

Legacy negative news and “screening” applications create serious risk for AML officers and their programs.

  • These applications actually contain very little data about negative news and other risks which means when analysts and investigators use these databases, they are constantly missing critical information that is actually available to the public.  How do you explain to a regulator that you missed a key piece of negative news, when they actually find it more easily than the AML group?
  • These applications bury users in false positives which means analysts are wasting time, allowing workloads to pile up which then force the AML team to work faster (and perhaps not as thoroughly).  How effective can analysts be when they spend so much time with their eyes glazed over wading through false positives?  These applications are actually creating risk when they are supposed to be helping to manage it.
  • These applications do not automatically create an audit trail of what was searched and the results. This leaves users, management, quality control, audit, and the regulators without evidence of how the work was completed (or even if it was completed).  What other AML compliance process exists that is based on the hope that the work is being done and being done correctly!?!  It’s 2016, shouldn’t critical compliance applications automatically record work and results?

Andrew Luck may not be missing much by using decade old technology, and what he does miss on Snap Chat or Instagram really isn’t that important.

The same cannot be said for AML officers, where missing key negative news and available risk relevant information has serious consequences.

Andrew Luck can afford to be quirky.  AML officers cannot.  Why would any AML officer push his or her luck?

Posted by & filed under AML General.

prepaid-cardsThe AML risks associated with prepaid cards have been known for some time, and with more than $623 billion loaded on gift cards and other types of prepaid cards in the United States in 2015 there continues to be a challenge for AML professionals to identify illicit activity in this sector.

Below are three separate lists of AML red flags related to the use of prepaid cards from the Network Branded Prepaid Card Association (NBPCA), the Financial Actions Task Force (FATF), and the Wolfsberg Group.  As highlighed in the below FATF paper,


“Red flags will be indicators of suspicious activity where a product’s actual use deviates from its intended use or does not make economic sense.  For example, cash withdrawals in foreign jurisdictions will be expected where the product is a prepaid traveller card, but unusual where the product is marketed to minors.  Red flags should therefore not be applied unthinkingly, but tailored to the product’s characteristics.”

Similar to most types of AML red flags, the majority of issues can either be grouped under transactions that do not make sense or fit the account profile, and red flags that involve discrepancies with the KYC of the customers.


Prepaid Red Flags the Network Branded Prepaid Card Association (NBPCA)

  1. A customer with an excessive number of cards (based on program parameters)
  2. A customer who is unwilling to provide information required by the CIP
  3. A customer who presents unusual or suspicious identification documents that the financial institution cannot readily verify
  4. A customer who requests a shipment of cards outside of the United States
  5. A customer uses different tax identification numbers with variations of his or her name
  6. A customer who is reluctant to provide the information needed for a mandatory report, to have the report filed, or to proceed with a transaction after being informed that the report must be filed
  7. A Cardholder that coerces or attempts to coerce a bank employee to not file any required record keeping or reporting forms
  8. High dollar deposits followed by numerous small withdrawals
  9. A Cardholder who makes multiple value loads on the same day at different load locations
  10. Large number of failed authorizations
  11. Transactions posted to the card account without corresponding authorizations
  12. Transactions occurring in more than one state or country on the same day
  13. Repetitive transactions occurring at the same time for the same amount each day or each week
  14. Transactions consistently occurring outside of the Cardholder’s residential area
  15. Unexplainable transactions with no logical purpose
  16. Repeated transactions outside of the Cardholder’s normal activity
  17. Multiple transactions slightly below reportable thresholds

 Source: Recommended Practices for AML Compliance for U.S.-Based Prepaid Card Programs


Prepaid Red Flags from the Financial Actions Task Force (FATF)

  1. Discrepancies between the information submitted by the customer and information detected by monitoring systems
  2. Individuals who hold an unusual volume of NPM (“New Payment Method” e.g. prepaid cards) accounts with the same provider
  3. A large and diverse source of funds (i.e., bank transfers, credit card and cash funding from different locations) used to fund the same NPM account(s)
  4. Multiple reference bank accounts from banks located in various cities used to fund the same NPM account
  5. Loading or funding of account always done by third parties
  6. Numerous cash loading, just under the reporting threshold of USD 10 000 (i.e., structured loading of prepaid cards), of the same prepaid card(s), conducted by the same individual(s) on a number of occasions
  7. Multiple third party funding activities of a NPM account, followed by the immediate transfer of funds to unrelated bank account(s)
  8. Multiple loading or funding of the same accounts, followed by ATM withdrawals shortly afterwards, over a short period of time
  9. Multiple withdrawals conducted at different ATMs (sometimes located in various countries different from jurisdiction where NPM account was funded)
  10. NPM account only used for withdrawals, and not for POS or online purchases
  11. Atypical use of the payment product (including unexpected and frequent cross-border access or transactions)
  12. Large  number  of  bank  accounts  held  by  the  same  prepaid  card  company  (sometimes  in different countries) apparently used as flow-through accounts (may be indicative of layering activity)
  13. Prepaid  card  company  located  in  one  country  but  holding  accounts  in  other  countries
  14. (unexplained business rationale which could be suspicious)
  15. Back and forth movement of funds between bank accounts held by different prepaid cards companies located in different countries  (may be indicative of layering activity as it does not fit the business model)
  16. The  volume  and  frequency  of  cash  transactions  (sometimes  structured  below  reporting threshold) conducted by the owner of a prepaid card company do not make economic sense

Source: Money Laundering Using New Payment Methods


Prepaid Red Flags from the Wolfsberg Group

  1. Information mismatch from application
  2. Application information/address/customer differs from pre-screened applicant
  3. Inability to verify card holder identity information
  4. Inability to provide government issued identification details
  5. Primary/secondary user name appearing on applicable government watch/sanctions lists
  6. Change of address to high-fraud area or to problematic jurisdiction, shortly after the card issuance or credit line increase
  7. Frequent and unusual use of the card for withdrawing cash at ATMs
  8. Structuring payments/Overpayments: balances on cards may move into regular credit where card holders pay too much or where merchants give credits to an account. Money laundering may be facilitated via refunds of the credit balance
  9. Unusual cash advance activity and large cash payments: the monitoring of incoming cash is critical, as excessive cash payments are often an attribute of money laundering. Credit balance accumulation resulting in refunds (CBRs) should be monitored as they can be used
    as part of a scheme to launder funds
  10. Cross Border: cash withdrawn via cards in another jurisdiction permits easy (and potentially high-value) cross-border movement of funds with a limited audit trail
  11. Unusual purchase of goods or services in countries regarded by an institution as posing a heightened risk for money laundering;
  12. Excessive payments on private label credit cards via gift card from the merchant
  13. Purchases at merchant on personal cards which are significantly out of pattern with historical spending behavior;
  14. Merchant credits without offsetting merchant transactions
  15. Excessive customer service calls
  16. Abnormal customer contact behavior (e.g., frequent changes of address)
  17. Multiple and frequent cash payment or money orders; large, cross-border wire transfer payments
  18. Where Issuers have access to this information, Settlements/partial settlements from unrelated third parties
  19. Where Issues have access to this information, unrelated checking/current account paying multiple credit card accounts
  20. Excessive/ongoing large credit refunds

Source: Wolfsberg AML Guidance on Credit/Charge Card Issuing and Merchant Acquiring Activities


Posted by & filed under Research & Investigation.

PEPWhile most financial institutions subscribe to a Political Exposed Person (PEP) list, there are many cases where these lists lack coverage or additional research is required.  Below is a list of seven free additional open sources to help you track down PEP information.

1. CIA World Leaders List

An online directory published by the CIA of “Chiefs of State and Cabinet Members of Foreign Governments.”  The directory is updated weekly and can serve as a great reference aid.



A project to “collect and share data about every politician in every country in the world, in a consistent, open format that anyone can use.”  Today the site has collected the data for 71,173 politicians from 233 countries.


3. CIBOD Biographies of Political Leaders (Spanish only)

Biographies on 766 political leaders from around the world.   The service aims to be “useful in the fields of education, research, consulting, journalism and politics” or for any user interested in global political leadership.


4. contains a list of heads of state and heads of government of all countries and territories, going back to about 1700 in many cases.


5. US Diplomat List

Provided by the U.S. State Department, this publication covers foreign missions (embassies, interest sections) in the United States.  It contains the names of members of the diplomatic staffs of these missions and their spouses.


6. Central Bank of Uruguay PEP List (Spanish only)

This is a PEP list made at the request of the Central Bank of Uruguay.  The list includes approximately 1,800 people who hold or have held public functions of importance in Uruguay and abroad.


7. cites itself as a “free database detailing the connections between powerful people and organizations.”  The site also offers a free visualization tool named Oligrapher.