“Our society depends on a number of highly complex and highly interconnected networks that process and distribute energy, information, goods, etc. They form an immense system of systems that has one key characteristic – huge complexity. As this system of systems evolves and grows its complexity also increases. And this is a problem. First of all, high complexity implies fragility. This is because highly complex systems can behave in a myriad of ways – called modes – and can often switch from one mode to another without any early warning. Many of these modes of functioning can be counterintuitive. In each mode a complex system offers different ‘concentrations of fragility’, points of weakness which may open the door to an attack. The more complex a system is the more concentrations of fragility it possesses in each mode. Think of all the things that go wrong in a modern car with its sophisticated electronics.
More gadgets means more trouble. Why? Because gadgets interact with each other, even though this if often unintended. More gadgets more possible interactions. The tens of thousands of possible circumstances that can arise is impossible to test. The only way to proceed is on a trial and error basis and let customers debug a product.
Anomaly detection has become a popular subject nowadays. The detection of malfunctions or anything suspicious, such as hacker attacks or illicit operations of any sort, is obviously of great interest. There are obviously various types of anomalies or malfunctions. Certain attacks may be undetected for prolonged periods of time, until the damage become visible. Some attacks are immediately obvious, as is the case of blackouts. Then there exist anomalies that are permanent but are never discovered. They make systems less efficient, less profitable, but, very often due to high complexity they remain masked. Monitoring of this universe can performed periodically – even in real-time if sufficient computational power is available – to track its complexity over time. The above logic can be applied to a universe of financial transactions to detect anomalies, in particular Ponzi schemes.”
Introduction: Anomaly-based Anti-Money Laundering Software (A-AMLS) with QCM
In finance, Complexity can become inextricably linked to the rise of fraud. Complexity is the reciprocal of transparency. In a simple transparent system it is difficult to disguise fraudulent anomalies. The system remains resilient. However the number of financial products and product complexity is increasing; some are made deliberately complex, others escape their creator’s control by refusing to follow a Gaussian distribution here or a linear correlation there.
The presence of highly complex products increases the complexity of financial markets, offering new opportunities for fraudulent and illicit operations. High complexity is a great way to hide incompetence, inefficiency, fraud and makes it difficult to identify responsibilities. Ponzi schemes (a form of fraud and money laundering) like Bernie Madoff were born out of investor desire to apply Complexity to escape market volatility. Likewise the incompetence of the custodians who accept deposits, monitor assets and pay on maturity must be addressed.
Could the use of Complexity for Bank Deposit Anti-Money Laundering (AML) software stop the next Madoff fraud?
A complete rethink of Anti Money Laundering (AML) software is needed; both in how it is structured and actioned. Banks can be negligent through a combination of human error or poor AML systems, as was the case with Madoff Securities and JP Morgan (JPM). Quantitative Complexity Management (QCM) offers a solution. Without which Banks can be unwitting accomplices to fraud; yet with QCM they can become safeguards in the system.
Could the use of Complexity for Bank Deposit Anti-Money Laundering (AML) software stop the next Madoff fraud? How can a Ponzi scheme be detected in a universe of money transfer transactions? Complexity monitoring of such universes may be of help. Fraudulent attacks may be undetected for prolonged periods of time, until the damage become visible.
In the world of possible applications of Paytech; stopping criminality and protecting customers must surely rank right up there but is it possible? If judged against the full complexities of the Madoff case then the answer might sadly be no. Confined to the payment system, possibly. Reviewing the Madoff case, the basics of AML systems, and AML failings all help to provide a framework for applying QCM.
- Prevent the placement of assets from criminal, terrorist or sanctioned sources
- Prevent the layering of assets, from prohibited sources, into deposit and investment
- Prevent the integration of prohibited assets being paid back
- AML is designed around client identification controls
- AML relies on humans monitoring and escalating
- AML identifies anomalous payments based on past customer behaviour
What is a Ponzi scheme
A Ponzi scheme can be defined as a structure that attracts cash deposits on the prospect of future returns but actually pays out existing investors using the deposits from new investors. These schemes display high cash burn rates but can exist for decades as long as investors are content and redemptions are covered. Ponzi schemes have dogged the Finance industry as long as they have existed. They cast a long shadow and perhaps none more so than Bernie Madoff.
The Psychology of Ethics in the Finance and Investment Industry, CFA Institute Research Foundation Publications (June 2007) available free at: https://www.cfainstitute.org/research/foundation/2007/the-psychology-of-ethics-in-the-finance-and-investment-industry
Why did it happen? I could cite you Orwell, Nietzsche or even Confucius; or any other commentator of the human condition. It is an ethical question but also a system based problem. The Chartered Financial Analyst Institute consider the ethical aspect here.
It is more useful to consider how? Eradicating the causality of Ponzi schemes is a rubicon that regulators have failed to succeed. However for all the complexity of a Ponzi scheme; they are often perpetuated through an unassuming bank account. Payments in; payments out. Yet over time and thousands of accounts this is itself becomes a complex network.
For those who don’t recall, this case involved the largest known Ponzi scheme in history; $65 billion defrauded out of $177 billion. All deposited into a reputable bank. The fact that the collapse of the Ponzi was the consequent of the Great Financial Crisis only made the losses all the more painful. Something in the American psyche broke.
Madoff pleaded guilty to 11 federal crimes and admitted to operating the largest private Ponzi scheme in history
On March 12, 2009, Madoff pleaded guilty to 11 federal crimes and admitted to operating the largest private Ponzi scheme in history. In his guilty plea, Madoff admitted that he hadn’t actually traded since the early 1990s, and all of his returns since then had been fabricated. The New York Post reported that Madoff “worked the so-called ‘Jewish circuit’ of well-heeled Jews he met at country clubs on Long Island and in Palm Beach. Over the years many accusations and investigations were initiated against Madoff over the years, both externally and internally at the depositing Bank, but none led to action.
In 2000 Harry Markopolos alerted the SEC. His analysis concluded almost immediately that Madoff’s numbers didn’t add up. After four hours of trying and failing to replicate Madoff’s returns, Markopolos concluded Madoff was a fraud. He told the SEC that based on his analysis of Madoff’s returns, it was mathematically impossible for Madoff to deliver them using his claimed strategies. Either Madoff was front running his order flow, or his wealth management business was a massive Ponzi scheme. The culmination of Markopolos’ analysis in his third submission, a detailed 17-page memo entitled ‘The World’s Largest Hedge Fund is a Fraud’ specified 30 numbered red flags based on just over 14 years of Madoff’s trades.
He approached The Wall Street Journal in 2005, but WSJ editors decided not to pursue the story.
Watch Harry Markopolos CFA testimony on Madoff here: http://www.c-spanvideo.org/program/283836-1