Master Criminals don’t usually confess in public. If prosecutors’ charges are true, Sanjay Shah is the leading figure in the largest reported tax swindle in history. Yet, Mr. Shah, unbowed, pleading his case to reporters, has openly admitted to borrowing the assets of widows and orphans in one country to kick-start a pyramid scheme of dividend capture trades, so as to swindle widows and orphans in other countries. Mr. Shah’s attorneys argue that his trades were not illegal. Mr. Shah, according to the reporters, claims everything he did was legal, and then he appeals to the Law of the Jungle:
“If there’s a big sign on the street saying, ‘please help yourself’,
then me or somebody else would go and help themselves.”
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Ed Blount, executive director of CSFME, reacts to the €150 billion “Cum-ex II Papers” controversy, as reported on October 21st. Ed was the lead investigator on our 2010 Empty Voting project and testifying expert in the $450 million Lehman unsecured creditors vs. IRS suit, as well as two dozen litigation and compliance matters in securities finance since the onset of the credit crisis.
Q. What would you say to a judge hearing this case?
A. He’s not a trader. Criminals like Shah do not meet threshold standards for markets. He’s just a thief.
Just because the money is lying in the middle of the street is no defense for theft. As a society and an industry, we reject that premise. Money is never abandoned in the real world.
We’re discussing standards for acceptable market behavior, and Shah is responding with a fairy tale, just like a rogue trader explaining away the fact that his books won’t balance.
Civil society cannot tolerate Shah’s behavior, much less his pyramid manipulations. Securities finance has an existential risk, but there is a serious reputational risk here for all financial institutions. Borrowing pension assets to siphon from a government treasury, no matter how clever, is just as evil as stealing from its social safety nets.
We all have to repay in taxes the money they steal. Real traders create wealth; they don’t steal it. We don’t need legal language to describe a thief.
Q. How can we expose rogue traders like Mr. Shah in the future?
A. Strip away their cover.
Just like pickpockets, rogue traders work in places that are very busy with lots of distractions.
Record dates are popular because of the many positioning trades made in advance of the entitlement postings. After record date, reversals may truly be as they appear, unwindings of dividend capture or similar legitimate trades. But some will be tax-driven, without economic substance. That’s what we’re looking for.
If we can scan and tag the legitimate, socially benign trades, tax auditors will have fewer left to examine in our search for the fraudulent trades. Rogues, as a result, will have fewer places to hide.
Q. What then?
A. Look for signs of desperation or excess in the rest.
Fees are a good tell. When Bear Stearns was failing, their cage managers would pay any price for liquidity.
Collateral is another. Lehman’s “Repo 105” trades were overcollateralized to appeal to unsuspecting counterparties. But it sent a signal to the Market Posse that Lehman’s securitization pipeline was slowing, and their liabilities were coming due. I later described those “Liability Dynamics” for Bear Stearns, Lehman Brothers, and other distressed firms in the RMA Journal.
In particular, I wrote, look for evidence of distress in the form of unusual margins, positive and negative, in the remaining trades.
Then audit the outliers.
Q. Where is the data for that analysis?
A. Some of it is available from vendors, and other useful data can be derived from regulatory filings. Service providers have most of the data, but it’s spread out.
Commercial data vendors such as FIS ASTEC, S&P Global (IHS Markit), and Datalend all have the ability to look for outlying loans and collateral. However, those vendors don’t have access to the “Know Your Customer” (KYC) profiles, contracts, trust indentures, and other policy documents that guide and constrain a trading desk. And data vendors must always keep in mind their own business models. The profit opportunity from surveillance may not be as appealing as other areas into which their resources can be directed.
Regulatory reports, like those required by the European regulations SFTR and MiFID II, can be foundational to the analysis. There’s now an enormous data lake of details on loans from the summer of 2020, when SFTR went live for securities loans.
Q. Can’t government agencies use that data to catch rogues and fraudsters?
A. They’re certainly trying, but they also have limits, both in reach and resources.
Government agencies cannot exceed their jurisdictions, except with the cooperation of foreign agencies willing to share intelligence. Foreign agencies might want to help, but their own regulations constrain them. Some of the documents they would need are firewalled in other agencies. Only the actual asset owners can access all the records required, either for compliance or surveillance. But even if the foreign KYC documents and legs of the trade were known, domestic regulators would have to revise their data models to build or manage an account-level registry for cross-border loans.
Q. As you say, Banking itself has serious reputational risk in this scandal. Are existing bank systems equipped to expose the rogues?
A. Banks have great systems, but they’re not designed for surveillance.
Compliance systems are regularly upgraded to shadow changing regulations. But there are very few regulations in the cross-border markets. Any systems to track best practices would require a redesign. Bank legacy systems are excellent for the work they do, but they are often two or three generations old.
It should be no surprise that regulators, led by ESMA, are pressing banks to build distributed ledger-based (DLT) infrastructures that can be used for market surveillance. The 2016 EU directive to disclose loan records by the Securities Financing Transaction Regulation (SFTR) was the opening gambit by regulators. Others have taken up the challenge. For example, compliance consultancies are exploring the use of blockchains and smart contracts to find fraudster networks that are operating in the covid-welfare distribution space. Some of those techniques may be useful.
Q. How can all that data be compiled?
A. Forensic and data analysts are very experienced in creating specialized databases.
For the Wells Fargo account-opening fraud, the forensic auditors at FTI Consulting, Inc. reportedly analyzed 35 million documents and unstructured data from more than 300 custodians. Their report to the independent board members concluded that “events show that a strong centralized risk function was most suited to the effective management of risk.”
That’s what securities finance needs now: a centralized loan database and registry to minimize the entire financial sector’s reputational risk from cross-border stock loan frauds.
Q. What about the privacy and confidentiality issues?
A. Bitcoin brought encryption into the mainstream, and Facebook’s profiling algorithms pushed data trusts into the spotlight. Let’s use the new DLT tech if it survives testing.
Traders are rightly concerned about exposing positions to raids in the GameStop squeeze era. I think that can be solved by lags and by puzzles. That is, if we are only building a compliance filter for banks, not a surveillance tool for regulators, there is no time sensitivity for the loan postings. A three-month posting lag would protect trading confidentiality but still be sufficiently current to filter the tax auditors’ screens for suspicious loans. Encryption can protect sensitive fields in the records, creating puzzles that defy access without the private keys.
For asset managers and owners, a data trust can provide a legal framework to protect the resources used to validate borrower strategies and even to monitor style drift. Data trusts are a just-in-time solution for this problem. Let’s use the new tools available and reassure asset owners about the social propriety of their loans -- and let’s give banks an ESG feather for their bonnets.
 The Massachusetts Institute of Technology (MIT) has named “Data Trusts” as one of the “10 Breakthrough Technologies of 2021”, along with Messenger RNA vaccines, lithium-metal batteries, digital contact tracing and Tik-Tok’s feed algorithms. |
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Q. Your old firm, ASTEC Analytics, created the first benchmarking systems for securities loans in the 1990s. Can’t a powerful database like that do the job?
A. Not likely. Purpose-built databases are inadequate for surveillance work.
I’m not privy to the tech just introduced in Lending Pit II, but, as a rule, vendor systems in securities finance were optimized for benchmarking. Their table structures, key fields, and SQL queries weren’t designed for surveillance or even for compliance. However, the new distributed tech of blockchains and shared ledgers offers data scientists a fresh start and may well be flexible enough to platform the analytics. Down the road, smart contracts can help banks to sort through the data and tag suspicious trades for further inspection. That level of functionality wasn’t in my original design specs for the Lending Pit.
Q. Is this the project that brought you out of ‘semi-retirement’?
A. Yes, I was intrigued to answer the critics, who have become quite vocal.
Those who say that securities finance is a platform for widespread fraud and manipulation, where thieves routinely deploy the assets of widows and orphans to steal from government treasuries, are wrong. There are also those who claim that proxy votes are being unknowingly sold to hedge funds. Every industry has a few bad apples. But the men and women in securities finance, by and large, are honest and dedicated stewards of the assets they’re given to manage.
We can create an answer to the critics’ charges of malfeasance, just as we did ten years ago when we educated the regulators about the mistakes of the empty voting critics. Personally, I’m not interested in ancient history. I’m sure others are working diligently on researching old loans. But I would like to leave a way for the new loans to be seen as legitimate, so the field is accepted as honest and I don’t have to scratch off the last 30 years of my CV.
Q. Will we work with RMA, SIFMA, and DTCC again, as during the Empty Voting project?
A. We will work with any organization that can help the Market Posse.
We will certainly work again with trade groups and industry utilities and with our forensic consulting colleagues and the platform vendors for distributed ledger technologies.
My own history working with industry utilities goes back to 1974 when I opened the first ADR account at the brand-new Depository Trust Company. That’s me on the left, in my double-knit pinstriped suit, proudly showing our pin-feed position report to Bill Spencer, president of First National City Bank; to Dick Banks, my boss; and to our DTC rep. NSCC was one of ASTEC’s first consulting clients, for a technical assessment of challenges onboarding the custodian banks into the brokers’ Continuous Net Settlement system. In fact, the first time that I ever saw a personal computer was a Heathkit that Jack Nelson, NSCC’s first president, had on his conference table in 1982.
More on that another time, perhaps.
Q. Who else will be helping the Market Posse?
A. In our next blog, I will introduce Eric Poer, lead forensic accounting partner at FTI Consulting, to explain how he and his team exposed the largest consumer fraud in U.S. history.
FTI Consulting, on behalf of the independent directors on the Wells Fargo board, was engaged by the law firm of Shearman & Sterling to organize and examine data held in scores of systems going back many years. Eric Poer will explain how his team approached the challenge of collecting, analyzing, and collating the data to determine the breadth of the sales practice issues and determine their origins. FTI’s analysis was conducted in the cloud in virtual sandboxes, then collated with unstructured data (i.e., emails, interviews, etc.) and summarized in expert reports and exhibits.
Eric, with 25 years of experience in regulatory inquiries, investigations, and disputes, was also my analytical partner in our support of the tax claims pursued in federal bankruptcy court by Lehman’s unsecured creditors committee. Together, we will explain how we mapped the cross-border loans by Lehman’s subsidiaries to show their economic substance and confirm the legitimacy of the $450 million in foreign tax credits that the U.S. Internal Revenue Service had disallowed.