THIS POST IS CONTINUED FROM PART 31, BELOW--
The FATF standards on money laundering and terrorism financing category as “preventive measures”.
These preventive measures require financial institutions to identify their clients, create client profiles, weed out those who from the start look like they may be bad guys or controlled by bad guys, and then monitor the account activity of accepted clients to see if that activity varies from what is expected or reflects the kind of activity that known bad guys have undertaken in the past.
Financial institutions are then supposed to look further into the questionable client activity and report to the government when they suspect the client may be a criminal, including a terrorist. Key to the process of successful activity monitoring is an understanding of what known bad guys have done in the past. Studies of these past actions are known as typologies, which can include special “red flag” indicators for particular types of nefarious activity.
The problem with adding terrorism financing to the list of activities that financial institutions were required to look for, and requiring them to report to the government when they suspected they saw it, was that the FATF didn’t actually know how bad guys financed terrorism.
It was one thing for governments to use their considerable investigative resources to identify terrorists or terrorist organizations and then pass those names along to financial institutions so that those institutions could verify whether they had any such clients, but yet another to ask financial institutions to identify terrorists based on their clients’ transactions alone.
Until recently, the FATF’s and member governments’ attempts to develop terrorism financing typologies and red flags had been fitful, incomplete, and based largely on a small number of cases that were often not even relevant. The United Nations Counter-Terrorism Implementation Task Force (CTITF) undertake a comprehensive study of terrorism financing.
The Counter-Terrorism Committee is a subsidiary body of the United Nations Security Council. the United Nations Security Council unanimously adopted resolution 1373, which, among its provisions, obliges all States to criminalize assistance for terrorist activities, deny financial support and safe haven to terrorists and share information about groups planning terrorist attacks.
The 15-member Counter-Terrorism Committee was established to monitor implementation of the resolution. While the ultimate aim of the Committee is to increase the ability of States to fight terrorism, it is not a sanctions body nor does it maintain a list of terrorist groups or individuals..
While the Counter-Terrorism Committee is not a direct capacity provider it does act as a broker between those states or groups that have the relevant capacities and those in the need of assistance
In 2012, HSBC, one of the world’s largest banks, settled with the U.S. Government, avoiding criminal prosecution of its executives, for helping to launder money for Mexican drug cartels as well as Al Qaeda. HSBC provided a “gateway for terrorists to gain access to U.S. dollars and the U.S. financial system.”
HSBC agreed to forfeit 1.256 billion dollars, the largest forfeiture amount ever by a financial institution for a compliance failure. They don’t care as long as there is NO jail term. The lost money can be made up in days .
Because they were let off with zero criminal charges, the bank was allowed to go back to crooked business as usual.
The Organized Crime and Corruption Reporting Project published a comprehensive narrative that details how billions of dollars were moved from Russian sources to bogus shell companies before traveling further into various banks, and ultimately numerous companies that inadvertently accepted corrupt funds.
Money entered the Laundromat via a set of shell companies in Russia that exist only on paper and whose ownership cannot be traced. Some of the funds may have been diverted from the Russian treasury through fraud, rigging of state contracts, or customs and tax evasion.
Money that might have helped repair the country’s deteriorating roads and ports, modernize the health care system, or ease the poverty of senior citizens – was instead deposited in a Moldovan bank.
HSBC, which is headquartered in London, processed US$545.3m in Laundromat cash, mostly routed through its Hong Kong branch
A great number of banks accepted these funds easily, and the scheme touched upon at least 96 countries receiving the tainted money including the United States, with money ending up at Citibank and Bank of America. The OCCRP reported that “the 21 shell companies fired out 26,746 payments from their various Trasta Komercbanka and Moldindconbank accounts” between 2011 and 2014.
Earlier estimates of laundered money were wrong, recent projections have increased that number to as much as $80 billion.
The suspected “architect” behind this massive undertaking is Moldovan businessman Vyacheslav Platon.
US Congress could close this loophole by passing a simple, two-page law requiring the beneficial owner of a company to be identified whenever a U.S. company is formed. Treasury submitted a legislative proposal to Congress that provides a framework for closing this loophole once and for all.
Delaware is well-known for its incorporation businesses, but it’s no worse than any other state in this regard. With about $100 and 20 minutes, you can go to a U.S. state’s website and form a company without disclosing the name of the person who will own or control it.
Professional incorporation agents set up hundreds or even thousands of these companies and then sell them, in some cases to those looking to move money surreptitiously.
Criminals have learned that American companies have an easier time obtaining bank accounts, and so they incorporate here in large numbers. Financial investigators often come across U.S. shell companies in their money hunts — and that may be where the trail ends.
WE ASK DONALD TRUMP TO STOP THIS NONSENSE !
U.S. shell companies have the dubious distinction of being the only money laundering method where secrecy is provided by a government entity.
Stopping terrorist financing and money laundering are bipartisan issues, and Congress’s support for the work of my office is broad and deep on outside –but shallow and fickle inside . Whenever legislators have tried over the years to pass laws similar to the one recently proposed by Treasury, interested stakeholders have defeated the bills every time.
This is simply unacceptable.
To mitigate the threat, the Treasury Department issued a rule that will require U.S. banks opening accounts for a company to obtain and verify the identity of the company’s beneficial owner. That will help with companies that choose to bank here, but it won’t stop criminals who use U.S. front and shell companies to open bank accounts abroad.
And the burden for disclosing the true owners of companies should fall primarily on those incorporating the companies in the first place. To set this right will take an act of Congress—but as long as US congressmen are in Jew Rothschild’s payroll this wont happen.
After all Rothschild’s world financial empire is held together by shell companies
Chun Doo-hwan was the the fifth President of South Korea from 1980 to 1988. President Chun was convicted in Korea in 1997 of receiving more than $200 million in bribes from Korean businesses and companies.
President Chun and his relatives laundered some of these corruption proceeds through a web of nominees and shell companies in both Korea and the United States.
The former president and chief executive officer of BizJet International Sales and Support Inc., a U.S.-based subsidiary of Lufthansa Technik AG with headquarters in Tulsa, Oklahoma, that provides aircraft maintenance, repair and overhaul services, was caught in a scheme to pay bribes to foreign government officials.
Bernd Kowalewski, 57, the former President and CEO of BizJet, pleaded guilty in US federal court in, to conspiracy to violate the Foreign Corrupt Practices Act (FCPA) and a substantive violation of the FCPA in connection with a scheme to pay bribes to officials in Mexico and Panama in exchange for those officials’ assistance in securing contracts for BizJet to perform aircraft maintenance, repair and overhaul services.
Kowalewski and his co-conspirators paid bribes directly to foreign officials to secure aircraft maintenance repair and overhaul contracts, and in some instances, the defendants funneled bribes to foreign officials through a shell companies.
WELL, HUNDREDS OF SUCH CRIMES ARE HAPPENING IN INDIA.
WE NOT KNOW HOW TO CATCH THESE CRIMINALS.
UNCLE OTTAVIO QUATTROCCHIs WIFE MARIA BABY ONCE KICKED AN UNIFORMED JAWAN WITH HER POINTY ITALIAN PUCCI ( OR WAS IT GUCCI ) SHOES , JUST BECAUSE HE DARED TO RUN A METAL DETECTOR ON HER.
I WILL BECOME McWOLF AT THIS RATE
Most naturally occurring data sets follow a strange rule called Benford's Law.
This rule allows you to predict how often each number 1 through 9 will appear as the first non-zero digit in the data set.
Benford's Law can be used to analyze financial data and identify red flags. If the data doesn't look anything like the distribution predicted by Benford's Law it may mean the numbers have been manipulated.
Benford's law, also called the first-digit law, is an observation about the frequency distribution of leading digits in many real-life sets of numerical data. The law states that in many naturally occurring collections of numbers, the leading significant digit is likely to be small
For example, in sets which obey the law, the number 1 appears as the most significant digit about 30% of the time, while 9 appears as the most significant digit less than 5% of the time.
By contrast, if the digits were distributed uniformly, they would each occur about 11.1% of the time. Benford's law also makes (different) predictions about the distribution of second digits, third digits, digit combinations, and so on.
It has been shown that this result applies to a wide variety of data sets, including electricity bills, street addresses, stock prices, house prices, population numbers, death rates, lengths of rivers, physical and mathematical constants, and processes described by power laws (which are very common in nature). It tends to be most accurate when values are distributed across multiple orders of magnitude.
The law could be used to detect possible fraud in lists of socio-economic data submitted in support of public planning decisions.
Based on the plausible assumption that people who make up figures tend to distribute their digits fairly uniformly, a simple comparison of first-digit frequency distribution from the data with the expected distribution according to Benford's Law ought to show up any anomalous results.
Following this idea, Mark Nigrini showed that Benford's Law could be used in forensic accounting and auditing as an indicator of accounting and expenses fraud. In practice, applications of Benford's Law for fraud detection routinely use more than the first digit.
Benford’s Law gives the expected patterns of the digits in tabulated data and it has been used by auditors and scientists to detect anomalies in tabulated data
If somebody tries to falsify, say, their tax return then invariably they will have to invent some data. When trying to do this, the tendency is for people to use too many numbers starting with digits in the mid range, 5,6,7 and not enough numbers starting with 1.
This violation of Benford's Law sets the alarm bells ringing.
TIME FOR A KHAINI BREAK !
ALL THIS IS COPIED FROM ANCIENT KERALA MATH
THE VEDIC GOLDEN MEAN 1.618 ( SRI YANTRA ) , THE FIBONACCI SERIES ( VEDIC SERIES ) AND BENFORDs LAW , ARE ALL INTERRELATED.
The Fibonacci numbers are
0, 1, 1, 2, 3, 5, 8, 13, ... (add the last two to get the next)
The golden section numbers are
0·61803 39887... = phi = φ and
1·61803 39887... = Phi = Φ
In numbers that appear in tables of physical and chemical constants. and similar tabulations, the digit 1 appears as first digit almost three times more often, as one would expect
Fibonacci and Lucas numbers tend to obey Benford's law
Benford offered a general "law of anomalous numbers. The probability that a random decimal begins with digit p is
log (p + 1) - log p
The first digits of Fibonacci and Lucas numbers tend to obey very closely the formula of probability offered by Benford.
The Lucas numbers or Lucas series are an integer sequence named after the mathematician François Édouard Anatole Lucas ( stolen from Kerala Math ) who studied both that sequence and the closely related Fibonacci numbers.
Lucas numbers and Fibonacci numbers form complementary instances of Lucas sequences.
Similar to the Fibonacci numbers, each Lucas number is defined to be the sum of its two immediate previous terms, thereby forming a Fibonacci integer sequence.
The first two Lucas numbers are L0 = 2 and L1 = 1 as opposed to the first two Fibonacci numbers F0 = 0 and F1 = 1. Though closely related in definition, Lucas and Fibonacci numbers exhibit distinct properties.
All Fibonacci-like integer sequences appear in shifted form as a row of the Wythoff array; the Fibonacci sequence itself is the first row and the Lucas sequence is the second row.
The Wythoff array ( stolen from Kerala Math ) is an infinite matrix of integers derived from the Fibonacci sequence .. it can also be defined using Fibonacci numbers or directly from the golden ratio and the recurrence relation defining the Fibonacci numbers.
Like all Fibonacci-like integer sequences, the ratio between two consecutive Lucas numbers converges to the golden ratio.
THE RATIO OF SUCCESSIVE TERMS IN A FIBONACCI SEQUENCE TEND TOWARDS THE GOLDEN MEAN.
THE DIGITS OF ALL NUMBER MAKING UP THE FIBONACCI SERIES TEND TO CONFORM TO BENFORDs LAW
THE FIRST DIGITS OF THE FIRST 100 FIBONACCI AND THE FIRST 100 LUCAS NUMBERS APPROXIMATED THE EXPECTED FREQUENCES OF BENFORDs LAW
( IT FITS BETTER IF WE INCREASE THE NUMBER FROM 100 TO 1000 AND THEN FURTHER TO 2000 )
My revelations now jump to 35.0%
ALL THOSE WHO THINK HINDUS ARE HEATHEN PAGAN SAVAGES , PLEASE RAISE YOU FUCKIN’ HAND .
ALL RIGHT SHOVE IT RIGHT BACK INTO YOUR ASSHOLES
Below: The Sri Yantra which contains TOE, is drawn with the Vedic Golden Mean as the base ( 1.618 )-- it was drawn in ancient days , when the white man was was doing GRUNT GRUNT for language and living in caves, clubbing down animals and eating them raw..
TO BE CONTINUED-
CAPT AJIT VADAKAYIL