New Requirements to Combat Money Laundering

By Charlie Rosenthal

Starting with the Panama Papers, a massive leak of confidential documents from a Panamanian law firm, much more light has been shed on the ways in which the rich and unscrupulous avoid government oversight of their assets. The Panama Papers—along with the Paradise Papers, which were released in a similar leak from another global offshore law firm—revealed that numerous politicians and celebrities have taken advantage of shell corporations and corporate secrecy to move money across borders.

Starting this month, banks now must comply with an extensive set of new due diligence requirements designed to combat money laundering and international money movement of the kind revealed in the Panama and Paradise Papers. The new rules, issued by the Financial Crimes Enforcement Network (FinCEN) of the U.S. Department of the Treasury, require financial institutions to gather additional information about the identities of the ultimate owners of entity clients. By requiring banks to gather information about the owners of anonymous shell corporations that they do business with, the Treasury Department and FinCEN hope to remove the incentive to hide shady behavior behind anonymous corporate ownership.

The new due diligence rules apply both to new and existing accounts. When a legal entity customer—such as a corporation or a limited liability company—opens a new account, banks are required to identify the actual people who control the entity. Banks can determine ownership either by identifying any party who holds more than a 25 percent stake in the entity or by identifying the party who controls the entity.

With respect to already existing accounts, the new requirements are intended to supplement the protections built into the Bank Secrecy Act. That law requires banks to create anti-money laundering programs. These programs generally consist of four parts: internal controls; training; a compliance officer; and independent oversight. FinCEN’s requirements now effectively add a fifth part: “customer risk profiles.” This new component is intended to ensure banks will understand better what their customers are doing and why.

Although money laundering’s very nature makes estimating its precise size difficult, it has become a global issue of the first order. Often using shell companies to hide their identities, oligarchs, tycoons, and criminals around the world avoid taxes, buy real estate, and transfer funds across borders.

It is estimated that money laundering results in a multi-trillion-dollar drain on the global economy. The French economist Gabriel Zucman, in his book, The Hidden Wealth of Nationsestimated that 8 percent of the world’s wealth—$7.6 trillion—was held in tax shelters, costing countries $200 billion in tax revenue.

According to a 2016 report issued by the Financial Action Task Force, the United States is exposedto significant money laundering and terrorist financing risks because of the massive size and global reach of the American financial system and its relative openness. Although the task force recognized that the United States has made tremendous progress in monitoring money laundering since the last task force evaluation in 2006, it did note that transparency issues remain a major weakness of the American anti-money laundering infrastructure.

The new FinCEN customer due diligence requirements are far from the first attempts by U.S. bank regulators to combat money laundering. The Bank Secrecy Act contains a number of anti-money laundering provisions, such as requiring banks to file reports every time a customer engages in a transaction involving more than $10,000 in cash and requiring customers to disclose foreign bank accounts. Beyond that, the USA PATRIOT ACT also imposed new know-your-customer requirements on banks to combat terrorist financing.

American regulators have imposed massive fines on numerous domestic and foreign banks who have violated money laundering regulations. Over the past two years, U.S. Bancorp was fined $613 million and Deutsche Bank was required to pay $630 million. Those fines pale in comparison to the nearly $2 billion in penalties inflicted on British bank HSBC in 2012 for allowing Mexican drug cartels to launder money.

FinCEN’s latest rule was initially finalized in May 2016, but banks were given two years to comply with its requirements. According to the banks, implementation of the rule was expected to be very complicated. For example, although the beneficial ownership test under the rule appears simple on its face, the real-life complexities of entity structuring and the numerous exemptions and exceptions to the rule make it much more complicated.

At least one member of Congress—U.S. Representative Blaine Luetkemeyer (R-Mo.)—recently argued that banks should be given more time to implement the regulations, given their complexity. But no reprieve was granted. The new requirements took effect on May 11th, 2018.

Authorities charge man with money laundering after traffic stop

By Sanford Schmidt

EDWARDSVILLE — Authorities have charged a California man with money laundering after state police found more than $263,000 in a car he was driving.

Charged with two counts of money laundering is Daniel J. Hovland, 36, of Hayward, Calif. He is accused of transporting criminally derived property and carrying the property in bundles with rubber bands to avoid a transaction requirement. Bail was set at $200,000.

The charge came after a state trooper stopped a 2018 Toyota Camry, driven by Hovland April 26 on Interstate 70 in Collinsville. The details of the case became public Friday.

He was stopped for improper lane use, and told an officer he was traveling from “out east” back to California. However, he was unable to specify exactly from where “out east” he came.

Police brought in a drug dog who alerted on the Camry. Hovland told police he had $6,000 in his position. Police searched the car and found a suitcase in the trunk containing a large amount of bundled cash. Officers also found seven cell phones in the car.

Hovland declined to be interviewed without an attorney present. The Madison County State’s Attorney’s Office filed suit under a state law that allows law enforcement authorities to obtain assets believed used in the drug trade.

The suit claims Hovland was unable to explain the money and that he did not have a legitimate source of income for that amount of money. The suit claims the cell phones were intended for use in concealing the proceeds from some form of unlawful activity.

Solving a blockchain conundrum: Biometrics could recover lost encryption keys

By Lucas Mearian

Blockchain could one day solve the online privacy problem by encrypting or scrambling personally identifiable information and issuing each person a random string of bits – a private key – created explicitly for unscrambling their data.

The person holding the blockchain private key could issue various public keys controlling who has access to the personal data on the blockchain. So, for instance, if a car rental agency needed to verify you have a driver’s license, you could use a public key to give them access to that information. You could later revoke access to that information.

The still-nascent distributed ledger technology, however, faces a vexing problem: what does a user do if they lose their private key? Essentially, a lost key means they lose access to all of their data – and if that data happens to include bitcoins or other cryptocurrency, they lose their digital money as well.

For example, Bitcoin scrambles user information through the use of the AES 256-bit encryption algorithm, which creates a 256-bit private key that can be represented by 32 or 64 alpha numeric characters.

“For Bitcoin, there simply is no key recovery. If you lose your private key, you’ve lost your Bitcoin,” said Martha Bennett, a principal analyst at Forrester Research.

Lance Morginn, CEO and co-founder of the Blockchain Intelligence Group, believes the blockchain industry and government regulators will need to collectively come to terms on a standard for reclaiming a lost private key.

The Blockchain Intelligence Group is a private company that offers blockchain search and data analytics tools; it has already been working on ID management with U.S. regulators and law enforcement agencies.

The most likely method for reclaiming a private key would be to physically go to a secure facility where the key’s owner would have to pass a number of security measures before the key is restored.

“It’s going to come down to a multitude of biometric devices. It could include a fingerprint scanner with a pulse detector, a retinal scanner and facial recognition all tied together,” Morginn said. “We’re in discussions with number of different regulators around world.”

Increasing regulatory scrutiny

While the idea of going to a private key reclamation facility may seem far-fetched, regulators in various countries are already boosting their scrutiny of cryptocurrency exchanges, including requirements that cryptocurrency be stored offline.

After a number of bitcoin thefts over the past seven years, Japanese regulators this month tightened their rules requiring exchanges to keep bitcoins offline or in “cold storage,” and bitcoin wallet access will require more than one person’s login information.

Conversely, most of the world’s other bitcoin exchanges today continue to keep the digital currency in “hot wallets” or online electronic depositories managed by the exchanges themselves.

Japanese bitcoin exchanges will also have to take more action to prevent money laundering, just as financial service companies in the U.S. must do today by following know-your-customer (KYC) and anti-money laundering (AML) guidelines.

Blockchain identity networks projects have also sprung up, offering the potential to satisfy new, more stringent requirements, such as KYC, to ensure that companies know with whom they’re doing business. KYC regulations were enacted in recent  years to address a rise in money laundering and terrorist activity funding.

Through a blockchain identifier network, banks could pre-verify who their customers are, and whether or not they’re tied to nefarious activities.

There are already blockchain networks that use biometrics to enable access to private keys and the personally identifiable information (PII) they protect.

Biometrics for accessing keys

For example, Civic, a blockchain identity-verification technology provider, pre-registers users and their identification data, encrypts it and issues a passcode accessible via a finger print scan using an app on a mobile device.

In March, Civic partnered with mobile voting provider Votem to launch a know-your-customer process that will pre-register and authenticate those participating in Votem’s crowdfunding initial coin offering (ICO). Once user IDs have been verified using blockchain, the identities are stored on the Civic App and can be reused for the ICO.

Civic’s private keys are generated by a third-party crypto wallet, providing a firewall between Civic and users’ keys app. The fingerprint scan eliminates the need for logins  with a username, password, third-party authenticator, or physical hardware token. Civic users can choose who gains access to their information and what data gets shared.

Just as physical keys only open the locks for which they were made, public keys can be used by blockchain users to control what data is released to whom; public keys are controlled through smart contracts, a blockchain business automation tool that determines what information is released based on the public key used.

There are several projects in the works to enable the worldwide exchange of PII via blockchain networks. The biggest benefit: there would be no central authority, such as a bank, governing the exchange of private data. The control would remain with the owner of that data.

For example, the Sovrin Foundation, a new nonprofit organization now developing the Sovrin Network, could enable anyone to globally exchange pre-verified data with any entity also on the network.

The online credentials would be akin to identify information that might already be in someone’s physical wallet: a driver’s license, a bank debit card or a company ID.

Instead of a physical card, however, the IDs in digital wallets would be encrypted and link back to the institutions that created them, such as a bank, a government or even an employer. Any of them, through the blockchain, would automatically verify  information to a requestor.

The owner of the digital wallet can limit what information a business receives via an electronic token.

“Let’s say I go to rent a car and you’ve got the 18-year-old behind the counter that I have to give all my information – my driver’s license, my credit cards. She doesn’t need all that information. She just needs to know that I’m authorized to drive that car. I have just given her the… token saying I’m licensed in the state of New York,” said Shone Anstey, president and co-founder of the Blockchain Intelligence Group.

“That way, if the car company has a break-in and someone steals all their databases, they don’t have my personal information,” Anstey added.

The ID2020 alliance, a global partnership, is working to create an open-source, blockchain-based digital identity system for people in the U.S. or other nations who lack legal documentation because of their economic or social status.

A blockchain-based identity token, one that contains PII, may be considered more sensitive because once in someone else’s possession it could be used to impersonate someone for any number of purposes. Witrh that in mind, regulators are considering how blockchain users would be able to revoke access to their identity tokens as well, Anstey said.

Michael Fauscette, chief research officer at G2 Crowd, a business-to-business software review site, expects that in the next five years, decentralized identity verification will no longer be a novelty; it will be the norm.

“Imagine hiring without reference checks or transcript verifications, where all that an applicant needs is a blockchain hash,” Fauscette said.

With identities, bank accounts and employer information all possibly stored online through blockchain, it will be more crucial than ever to ensure that a lost private key can be recovered.

Despite steps in the right direction, the industry isn’t even close to enabling how private keys will be recovered, Morginn said.

Combating fraud and money laundering with graph analytics

By Yu Xu at Tiger Graph

Dirty money and money laundering have been around since the existence of currency itself. On a global level, as much as $2 trillion is washed annually, estimates the United Nations. Today’s criminals are sophisticated, using ever-adapting tactics to bypass traditional anti-fraud solutions. Even in cases where enterprises do have enough data to reveal illicit activity, more often than not they are unable to conduct analysis to uncover it.

As the fight against money laundering continues, AML (anti money laundering) compliance has become big business. Global spending in AML alone weighs in at more than $8 trillion, says WealthInsight. This figure will continue to grow, considering how any organization facilitating financial transactions also falls within the scope of AML legislation.

But combating crime is never easy. Especially when organizations face pressing needs for cost reduction and faster time to AML compliance in order to avoid regulatory fees. Legacy monitoring systems have proven burdensome and expensive to tune, validate and maintain. Often involving manual processes, they are generally incapable of analyzing massive volumes of customer, institution and transaction data. Yet it is this type of data analysis that is so critical to AML success.

New ideas have emerged to tackle the AML challenge. These include: semi-supervised learning methods, deep learning based approaches and network/graph based solutions. Such approaches must be able to work in real time and handle large data volumes – especially as new data is generated 24/7. That’s why a holistic data strategy is best for combating financial crime, particularly with machine learning (ML) and AI to help link and analyze data connections.

Graph analytics for AML

Graph analytics has emerged at the forefront as an ideal technology to support AML. Graphs overcome the challenge of uncovering the relationships in massive, complex and interconnect data. The graph model is designed from the ground up to treat relationships as first-class citizens. This provides a structure that natively embraces and maps data relationships, even in high volumes of highly connected data. Conducted over such interconnected data, graph analytics provides maximum insight into data connections and relationships.

For example, “Degree Centrality” provides the number of links going in or out of each entity. This metric gives a count of how many direct connections each entity has to other entities within the network. This is particularly helpful for finding the most connected accounts or entities which are likely acting as a hub, and connecting to a wider network.

Another is “Betweenness,” which gives the number of times an entity falls on the shortest path between other entities. This metric shows which entity acts as a bridge between other entities. Betweenness can be the starting point to detect any money laundering or suspicious activities.

Today’s organizations need real-time graph analytic capabilities that can explore, discover and predict very complex relationships. This represents Real-Time Deep Link Analytics, achieved utilizing three to 10+ hops of traversal across a big graph, along with fast graph traversal speed and data updates.

Let’s take a look at how Real-Time Deep Link Analytics combats financial crime by identifying high-risk transactions. We’ll start with an incoming credit card transaction, and demonstrate how this transaction is related to other entities can be identified:

New Transaction → Credit Card → Cardholder → (other) Credit Cards → (other) Bad Transactions

This query uses four hops to find connections only one card away from the incoming transaction. Today’s fraudsters try to disguise their activity by having circuitous connections between themselves and known bad activity or bad actors. Any individual connecting the path can appear innocent, but if multiple paths from A to B can be found, the likelihood of fraud increases.

Given this, more hops are needed to find connections two or more transactions away. This traversal pattern applies to many other use cases – where you can simply replace the transaction with a web click event, a phone call record or a money transfer. With Real-Time Deep Link Analytics, multiple, hidden connections are uncovered and fraud is minimized.

By linking data together, Real-Time Deep Link Analytics can support rules-based ML methods in real time to automate AML processes and reduce false positives. Using a graph engine to incorporate sophisticated data science techniques such as automated data flow analysis, social network analysis, and ML in their AML process, enterprises can improve money laundering detection rates with better data, faster. They can also move away from cumbersome transactional processes, and towards a more strategic and efficient AML approach.

Example: E-payment company

For one example of graph analytics powering AML, we can look towards the #1 e-payment company in the world. Currently this organization has more than 100 million daily active users, and uses graph analytics to modernize its investigation methods.

Previously, the company’s AML practice was a very manual effort, as investigators were involved with everything from examining data to identifying suspicious money movement behavior. Operating expenses were high and the process was highly error prone.

Implementing a graph analytics platform, the company was able to automate development of intelligent AML queries, using a real-time response feed leveraging ML. Results included a high economic return using a more effective AML process, reducing false positives and translating into higher detection rates.

Example: Credit card company

Similarly, a top five payment provider sought to improve its AML capabilities. Key pain points include high cost and inability to comply with federal AML regulations – resulting in penalties. The organization relied on a manual investigative process performed by a ML team comprised of hundreds of investigators, resulting in a slow, costly and inefficient process with more than 90 percent false positives.

The company currently is leveraging a graph engine to modernize its investigative process. It has moved from having its ML team cobble processes together towards combining the power of graph analytics with ML to provide insight into connections between individuals, accounts, companies and locations.

By uniting more dimensions of its data, and integrating additional points – such as external information about customers – it is able to automatically monitor for potential money laundering in real time, freeing up investigators to make more strategic use of their now-richer data. The result is a holistic and insightful look at its colossal amounts of data, producing fewer false positive alerts.

As we continue into an era of data explosion, it is more and more important for organizations to make the most in analyzing their colossal amounts of data in real time for AML. Graph analytics offers overwhelming potential for organizations in terms of cost reduction, in faster time to AML compliance and most importantly, in their ability to stop money laundering fraudsters in their tracks.

Is money laundering easier in a digital world?

By Alexon Bell

The rise of social media, peer-to-peer platforms and online banks has had a huge impact on the convenience and ease of transactions between individuals. But these platforms have simultaneously opened new doors for fraudsters to trick people out of their money and particularly criminals looking for ever more innovative ways of laundering the proceeds of their crimes. In an increasingly digital world, is money laundering becoming easier to pull off?

New forms of money laundering

With ecommerce so commonplace and only on the rise, legitimate websites are being used as payment processors in order to launder vast amounts of money. Drugs can be ordered online and the transaction will appear as something innocuous on your statement, such as a floristry purchase. From the bank’s side, their customer appears to be an online florist, helping mask funds as cash is not used. Transactions are funnelled through other legitimate payment ecosystems for illegitimate purposes, including the financing of terror through criminal enterprises. Last year it was alleged that an ISIS operative in the US had used eBay to ‘sell’ computer printers and received payments for these transactions from overseas via PayPal.

Peer-to-peer marketplaces

The sharing economy is on the rise and some of the most recognisable peer-to-peer brands are being exploited through their online payment systems. The nature of a peer-to-peer marketplace enables direct transactions from criminals on one side and complicit players on the other side, thus laundering money through a legitimate platform. The ease of use of these apps and websites is fuelling such activity, and their popularity and global adoption allows criminals to hide amongst huge volumes of transactions between lay people.

Last year, it was discovered that Airbnb had been exploited by money launderers, with criminals booking fake stays in rooms with complicit Airbnb hosts. Such a scheme works by criminals using stolen credit cards to book rooms through the peer-to-peer marketplace and paying for their fake stay online – with complicit hosts closing the loop. The transaction turns criminal proceeds into ostensibly legitimate earnings. News sources claimed that online Russian forums were being used to connect criminals to complicit hosts. In many instances these funds were laundered across borders, allowing the money to be hidden even more effectively.

A similar scheme was recently reported in which Uber was being used to launder criminal proceeds through fake transactions. In this system, middle men use stolen credit cards to book fake rides which never actually happen, with complicit drivers. A cut is taken by the drivers and the middle men, leaving the rest of the now seemingly legitimate funds to the client.

Both these recent examples show the ease with which sharing economy marketplaces can be exploited. The current systems to police thousands of peer-to-peer transactions across the globe, monitoring transactions and flagging any suspicious activity, simply aren’t strong enough to spot scams that look very similar to the sea of legitimate interactions.

Social media

Social media has an increasingly dominant role to play in recruiting people to facilitate money laundering – whether they do so knowingly or unknowingly. Several recent reports have highlighted young people being recruited as money mules though social media. Last week, fraud prevention body, Cifas published their annual report, revealing that in 2017 there were 32,000 cases of 14 to 24 year olds allowing their bank accounts to be used to move the proceeds of crime – an increase of 27 per cent. Social media is fuelling the spread of images of young people with cash and luxury items, luring young people into schemes which promise to get them rich quick. Unwitting mules are also being recruited through social media offers of fake jobs or initiatives to make extra money. Messaging app WhatsApp is being used as a communication method with these young mules or victims.

Scale of the issue

Online platforms are an attractive option for money launderers due to their global reach, speed, low cost and simplicity. There is no need to create a fake ‘shop front’ or false identities and no goods need to be moved.

Online money laundering is only set to grow. Global retail e-commerce sales are estimated to top $2.2 trillion annually, providing greater opportunities for criminals to hide their laundering activities among high volumes of legitimate transactions. Likewise, the popularity of cryptocurrencies and alternative payment platforms are garnering growing criticism and concerns over the transparency of transactions and the potential for easier than ever money laundering.

A digital solution

The digital world we live in is opening new doors for criminals to launder their money in different and creative ways. Only a digital-first approach will help tackle the issue.

New and ground-breaking innovations in technology that monitor transactions are helping to identify suspicious behaviour and patterns amongst huge numbers of legitimate payments and interactions. In particular, monitoring software is being used to put transactions in their proper context: making links and connections between parties and their transactions, using internal as well as external data sources. This contextual monitoring approach helps companies to see a 360° view of their customers – making it easier to identify unusual and illegitimate transactions consistently and accurately amongst thousands of genuine interactions. Using a combination of this digitally compiled insight and human intelligence will challenge online money laundering with a digital-first approach.

Peer-to-peer platforms, online payments and banking, and social media have been adopted across the globe thanks to their convenience, speed and ease of use. However, it is exactly these qualities that criminals are increasingly exploiting to support illegitimate activity.

While technology is fuelling this new approach to money laundering, technology is also the solution. Just as the criminal spheres of fraud and money laundering are converging, many organisations see the solution as a fusion of human intelligence with Artificial Intelligence. The key is cutting through the noise.

Michael O’Donnell pleads not guilty to federal charges

By Rachel Skytta

WICHITA, Kan. (KWCH) Update 2: p.m. Wednesday, May 9:

Sedgwick County Commissioner Michael O’Donnell pleaded not guilty to 12 counts against him Wednesday afternoon in federal court.

A federal indictment unsealed Friday alleges O’Donnell took money from his campaign accounts to put into his personal account and to give to his friends and covered it up by making false reports electronically to the Kansas Governmental Ethics Commission.

O’Donnell is charged with five counts of wire fraud, five counts of bank fraud and two counts of money laundering.

In court Wednesday, the judge imposed a $5,000 unsecured bond. As part of the condition, O’Donnell must forfeit his passport, an obligation the judge says he already fulfilled.

O’Donnell says he’s had the opportunity to look at the indictment detailing the charges against him, understands what the government is alleging and the potential penalties associated with the crimes for which he’s accused.


Factfinder 12 continues to push for information on the federal charges against Sedgwick County Commissioner Michael O’Donnell.

O’Donnell was indicted on charges of fraud and money laundering. He’s set to make his first appearance in court Wednesday. He confirmed to Factfinder 12 he will be at the regular county commission meeting before his court appearance.

We tracked down O’Donnell as he was coming and going from his office at the Sedgwick County Courthouse. He said he couldn’t comment, and asked that we contact his attorney.

O’Donnell did confirm he plans to be at the next county commission meeting. Factfinder 12 also asked if he’s prepared to answer questions after the meeting.

“I do not know. It is up to my attorney to tell me. But yeah, I’ll definitely be there tomorrow.” said O’Donnell.

We also asked if he wanted to say anything to his constituents who are wondering what will happen to his district.

“We’ll know more later this week.”

The federal indictment unsealed Friday says O’Donnell transferred money from his campaign accounts to his personal account. It says he wrote checks to other people as campaign expenditures, then had those people give the money back and deposited it into his personal account.

Commissioner Richard Ranzau has already called for O’Donnell’s resignation. It’s unclear if other commissioners plan to bring up the charges against O’Donnell at Wednesday’s meeting. That meeting starts at 9 a.m. O’Donnell will be in federal court at 1:30 p.m.

Stocks rise as oil rallies after Iran deal fallout

By Fred Imbert & Alexandra Gibbs

Stocks rose on Wednesday as energy shares jumped on the back of a strong rally in oil prices. The move higher in stocks and oil follows President Donald Trump’s decision to pull the U.S. out of the Iran nuclear deal.

The Dow Jones industrial average climbed 37 points, with Chevron and Exxon Mobil as the best-performing stocks in the index. The S&P 500gained 0.3 percent as energy rose 1.7 percent. The Nasdaq compositeadvanced 0.1 percent.

Chevron and Exxon Mobil both rose more than 1.5 percent, while the Energy Select Sector SPDR Fund (XLE) gained 1.8 percent. U.S. oil rose 2.4 percent to trade at $70.70 per barrel.

Trump said Tuesday that the U.S. would be walking away from the Iran deal and that sanctions on the Middle Eastern country would be reinstated. In the run-up to the 2016 presidential election, this was a campaign promise that Trump had pledged.

“This would have been much more shocking a year ago (when [Brent] oil was US$50) than now (with oil at US$75),” said Hasnain Malik, head of equity research at Exotix Capital, in a note to clients.

“Longer term, this event further narrows the space for countries that would benefit from cooperation with both the US (and its closest regional allies Israel, Saudi and the UAE) and Iran to chart a neutral path, and may portend a weakening of the US-EU strategic relationship,” Malik said.

Following the announcement, countries around the world reacted differently. While some nations in the Middle East commended the move made, U.S. allies in Europe did not. The president of Iran, Hassan Rouhani, said that his country would continue to commit to the nuclear deal, according to Reuters.

Equities closed flat on Tuesday after a choppy trading session. Since late March, stocks have traded in a tight range, with the S&P 500 bouncing between its 50-day and 200-day moving averages, two key technical levels.

“The market had traded up so much late last year and earl y this year,” said Greg Luken, CEO of Luken Investment Analytics. “It takes time to digest that.”

In the bond market, the 10-year Treasury yield reclaimed its position above the 3 percent mark on Wednesday, a level that recently put markets on edge. The two-year note yield also traded at its highest level in nearly a decade.

Meanwhile, in corporate news, shares of Walmart fell 3.2 percent after the company agreed to buy 77 percent of Flipkart for $16 billion. Flipkart is am e-commerce company based in India.

Money laundering in a digital world

By Alexon Bell

With the advent of online platforms came fraudulent schemes used to scam people out of their money, hack accounts and defraud internet users. The proliferation of peer-to-peer websites, online banking and cryptocurrencies is now having a huge impact on the ways criminals launder the proceeds of their crimes.

Going to the cleaners
Modern e-commerce is fuelling money laundering schemes that use legitimate websites as payment processors. This means it’s now possible to make illegal purchases online and have them appear as lawful transactions on your bank statement.

Modern e-commerce is fuelling money laundering schemes that use legitimate websites as payment processors

‘Dirty’ money moves straight to online merchants, who funnel it through other legitimate payment ecosystems for criminal purposes such as financing terrorist activity.

Last year, it was alleged that an ISIS operative in the US had pretended to sell computer printers on eBay to move money. The operative received payments for these transactions from overseas accounts via PayPal.

Peer-to-peer marketplaces
Some of the internet’s biggest marketplaces are now being exploited by money launderers thanks to their online payment systems, ease of use and huge global adoption (which allows criminals to hide in plain sight among thousands of other users).

Last year, reports found that criminals were booking fake stays in Airbnb properties with complicit hosts in order to launder dirty money. The perpetrators used stolen credit cards to book rooms through the peer-to-peer platform and pay for their ‘stay’ online, turning illicit proceeds into ostensibly legitimate earnings.

News sources revealed that online Russian forums were linking criminals with corrupt hosts, allowing them to quickly and easily launder funds, in many instances across borders. No one ever stays in the advertised accommodation and fake reviews give the illusion of real transactions having taken place.

A similar scheme was recently discovered, with fraudsters laundering their criminal proceeds through fake Uber transactions. Here, middlemen use stolen credit cards to book ‘ghost rides’ – rides that never actually happen – with complicit drivers. The middlemen and drivers take a cut, leaving the rest of the now-laundered money with the client.

The ease with which this can be done is testament to the difficulty of policing thousands of peer-to-peer transactions across multiple territories. The current systems, put in place to monitor transactions and flag suspicious activity, simply aren’t stringent enough to spot these types of cons.

Social media scams
A number of recent reports have highlighted that social media is increasingly being used to recruit young people as money mules, often without them realising this is the case. The annual report from fraud prevention body Cifas found that the number of 14- to 24-year-olds allowing their bank accounts to be used to move the proceeds of crime hit 32,000 in 2017, a 27 percent increase on the year before.

Social media is increasingly being used to recruit young people as money mules

Young account holders are lured into the schemes through images of people enjoying expensive lifestyles, promoted on social media. Social media is increasingly being used to recruit unwitting mules through offers of ‘make money quick’ schemes or fake job offers. WhatsApp is a known communication method used by criminals to contact would-be victims.

Scale of the issue
Laundering money through online platforms is attractive to criminals for its simplicity, speed and low cost, as well as its global reach. Using these platforms, there is no need to create a fake business or other identities, and no goods need to be moved to maintain the illusion of legitimacy.

Online money laundering is only set to grow. Worldwide retail e-commerce sales are estimated to top $2.2trn annually, providing greater scope for criminals to conceal their laundering activities among high volumes of legitimate transactions. Likewise, the rise of cryptocurrencies and alternative payment platforms raises well-documented concerns about how such technology will make untraceable money laundering easier.

The solution is digital
The ever-expanding digital world is opening new avenues for criminals to launder their money in different and creative ways. But just as technology is supporting money laundering, it is also the solution to the problem. Technological developments that monitor transactions are helping to identify suspicious patterns amid the noise of legitimate payments and interactions.

Big data analytics is being used by contextual monitoring software to make links between transactions and parties, across internal and external third-party data sources. The aim is to place each transaction into a wider context. Only by looking at this wider network can companies gain a full view of their customers and identify unusual and illegitimate transactions consistently and accurately among thousands of genuine interactions


Teppanyaki owners charged with money laundering, hiding $8M in sales

INDIANAPOLIS — Marion County Prosecutor Terry Curry and officials from the Indiana Department of Revenue announced criminal charges Thursday in an investigation into Indianapolis buffet restaurants accused of money laundering.

Police raided two Teppanyaki Grill & Buffet locations in Marion County in August 2016 and seized more than $600,000 in alleged money laundering proceeds.

Prosecutors also filed a civil complaint again Teppanyaki Grill, Teppanyaki West, Union Broker Limited, Hokkaido Japanese Buffet in Terre Haute and dozens of the restaurants’ managers and affiliates.

At the time, prosecutors left open the possibility of criminal charges being filed in the case.

On Thursday, the Marion County Prosecutor’s Office announced it had filed charges of corrupt business influence, theft and failure to remit taxes against seven people accused of underreporting more than $8 million in sales from seven Teppanyaki and similarly branded restaurants.

The defendants charged in the case are as follows:

  • Shua Li, owner of Teppanyaki Grill Supreme Buffet (Indianapolis)
  • Chunhua Wang, owner of Teppanyaki Grill Super Buffet (Lafayette)
  • Guo Wu Wu, owner of Teppanyaki Supreme Buffet 285 (Fort Wayne)
  • Jin Qui Zhao, owner of Teppanyaki Buffet, Inc. (Marion)
  • Ji Rong Lin, owner of Hokkaido Japanese Buffet (Terre Haute)
  • Guang Feng Li, owner of China King Feng, LLLC (Plainfield) and Teppanyaki Grill Supreme Buffet (Indianapolis)
  • Sheng Yi Li, owner of Teppanyaki West (Indianapolis)

According to a probable cause affidavit filed in the case, investigators allege the defendants used cash sales to hide hundreds of thousands of dollars a year in sales revenue – which they then failed to pay sales taxes on.

The investigation began with search warrants served at a single Teppanyaki location in Indianapolis in October 2014. Ultimately it expanded to restaurants in Terre Haute, Plainfield, Lafayette and Marion, as well as a second Indianapolis location.

Although the charges only cover alleged activities during the 2014-2016 period, Marion County Prosecutor Terry Curry said they have “no reason to believe that it hasn’t been going on at these restaurants for years and years.”

Former Netflix VP Charged With Fraud, Money Laundering

SAN JOSE (CBS SF) — A lawyer for a former Netflix executive indicted in federal court in San Jose on charges of taking an alleged $690,000 in kickbacks said Wednesday his client “vigorously disputes the allegations of the indictment.”

Michael Kail “looks forward to vindication at trial where these allegations will be proven untrue,” said defense attorney Joseph Ainley.

Kail, 49, of Los Gatos, was vice president in charge of internet technology at the Los Gatos-based video streaming company from 2011 to 2014. His position gave him the authority to enter into contracts with outside technology companies providing services to Netflix.

He was indicted by a federal grand jury in San Jose on April 26 on 29 counts of fraud and money laundering in connection with his alleged receipt of kickbacks in cash and stock options from nine technology companies that had contracts with Netflix.

The indictment was issued under seal and was unsealed after Kail was arraigned before a federal magistrate in San Jose Tuesday and pleaded not guilty to the charges.

U.S. Magistrate Nathanael Cousins allowed Kail to remain free on a $200,000 property bond while awaiting trial.

Kail’s next court appearance is a status conference on July 10 before U.S. District Judge Beth Labson Freeman, the trial judge assigned to the case.

The indictment alleges Kail’s total gain from the kickbacks was $690,000.

The charges include 19 counts of wire fraud for documents sent electronically to and from the outside companies in 2013 and 2014, three counts of mail fraud for documents sent by postal mail and Federal Express, and seven counts of money laundering of alleged profits.

The fraud counts each carry a maximum sentence of 20 years in prison and the money laundering counts 10 years, if Kail is convicted.

He could also be fined twice the amount of his gross gain from fraud.

The indictment additionally seeks forfeiture of any property Kail bought with the alleged proceeds, including his Los Gatos house.

The Los Gatos house served as the address of a one-person consulting company Kail set up called Unix Mercenary LLC. The indictment alleges Kail created the company for the purpose of having the kickbacks sent to its bank account. He allegedly then transferred the payments to his personal accounts.

Ainley said in his statement, “As a known technology leader in Silicon Valley, Mr. Kail frequently advises cutting edge startups on next generation technology.

“This indictment is unfounded and takes direct aim at the spirit of innovation and entrepreneurship that makes the valley such a vital part of the economy,” Ainley said.

After leaving Netflix in August 2014, Kail went to work for Sunnyvale-based Yahoo as chief information officer. He left that job the following May in the wake of a civil lawsuit filed against him by Netflix in Santa Clara County Superior Court in November 2014.

Netflix’s lawsuit included claims of fraud, unjust enrichment, fraudulent concealment and breach of fiduciary duty. It alleged that Kail fraudently took so-called “commissions” of 12 to 15 percent on the contracts he approved. The lawsuit was settled on a confidential basis in 2015.

After leaving Yahoo, Kail co-founded a Boston-based cyber security company called Cybric.