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Consolidated Audit Trail - Surveillance Without Kicking The Can Down The Road

Date 16/07/2021

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The civic concerns on the Consolidated Audit Trail (CAT) about Massive Government Surveillance should not be treated lightly. According to M.I.T. professor Gary Marx’s statements in this study“…most people in our society would object to this solution, not because they wish to commit any wrongdoings, but because it is invasive and prone to abuse … fails to take into consideration a number of important issues when collecting personally identifiable data or recordings such practices create an archive of information that is vulnerable to abuse by trusted insiders … In addition, allowing surreptitious surveillance of one form, even limited in scope and for a particular contingency, encourages government to expand such surveillance programs in the future. It is our view that the danger of a ‘slippery slope’ scenario cannot be dismissed as paranoia …”

 

 

CAT’s Limitation of Liability Provision, Revised Funding Model, and Enhanced Data Security proposals if adopted are inconsistent with §11A of the Exchange Act, the Fourth Amendment of US Constitution, the Department of Justice’s latest edition of the Privacy Act of 1974 and other applicable laws and new bills introduced recently.

CAT has an Outdated Design and is an Outsized Elephant. National security and privacy ordinance matters are Outside the Jurisdiction of the SEC and the SROs. The building of this mega warehouse and on-going operating costs Outweigh its Benefits.

 

We assert that the SEC should not approve these CAT proposals, whilst emphasizing that we despise “kicking the can down the road”. In our comment letter, we counter suggested an innovative design that draws analogy to the IRS’s successful ‘my free tax initiative’. It consists of the following steps and components:

A.     If the SIPs or the Competing Consolidators (CCs) expand core data to include depth-of-book, odd-lots, auction, etc. (i.e. ‘order level’ details), then there is no need to overlap this publicly available information at CAT.

B.     Cross tabulate early warning signals from the mining of SIP or CC data with intelligence gathered from the SROs’ surveillance systems (i.e. onset signal detection from better data (captured data at SIPs, CCs and SROs are at nanoseconds rather than CAT data with 50± milliseconds tolerance).

C.     Enabling the crowd with an open platform consists of: (a) a community library of basic trade patterns, similar to a music editor tool for the crowd to modify basic patterns into new trade strategies to discover alpha (or the unknown unknowns), a simulation tool where new strategies will be back tested, and a reward scheme if back-testing results shown useful insights into reducing unknown unknowns.

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D.     By leveraging crowd intelligence in step ‘C’ (learn from the field that is closest to the market and in real time) and combining with surveillance findings gathered from steps ‘A’ and ‘B’, it would substantiate enough supporting arguments for identified ‘symptoms’ of market or trade irregularities.

E.      Then, whatever residual data that are not otherwise available at SIPs or SROs would be collected through CAT, which substantially reduces CAT storage (avoid unnecessary regurgitation or repetitive copies of data) to only those data elements that are essential for law enforcement or prosecution investigation related to specific cases.

F.      Through pre-defined automated pre-screening of data that broker-dealers are about to submit to CAT (i.e. targeted to look for specific ‘red-flag(s)’), if no ‘red-flag’ is found relevant to previously identified symptom(s), then trade activities may be certified ‘clean’ and that batch of data is no longer required to be stored at CAT.

G.     With substantiated ‘symptoms’ and identified ‘red-flag(s)’, retrieve or subpoena evidence by querying relevant data field/ records would be permissible.

Our suggested solutions would analyze suspicious trading behavior and unusual market events directly and quickly, as well as yield substantial savings while enhancing security for all parties. In turn, the essential data stored at CAT would be much more manageable, data control would be more robust, and by then, insurers should be more willing to provide liability coverage for CAT processor, i.e. FINRA CAT LLC. It will allow the SEC and CAT Participants to focus on those high-risk candidates for scrutinized exams. We envisage a crowd model to reduce unknown unknowns, other benefits of our suggested approach are:

a)     Dramatically reduce CAT footprint or data storage and traffic by avoiding unnecessary redundant copies of data and minimize ‘data-in-motion’; 

b)     Confine access to CAT data to ‘targeted search’ of relevant data that fits the ‘defined purposes’; and

c)      Better intelligence for market monitoring by enabling and rewarding the crowd for identifying early warning signals to potential flash crash or other trade irregularities.

CAT’s development and deployment should not be a sprint, we must be persistent and thoughtful, and we must not give up to pursuit the very best approach with perseverance. We hope our “win-win” solution will help everyone charging forward on CAT and receive bipartisan support.

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At Data Boiler, we see big to continuously boil down the essential improvements that fit for your purpose. Between my patented inventions and the wealth of experience of my partner, Peter Martyn, we are about finding rare but high-impact values in controversial matters, straight talk of control flaws, leading innovation and change, creation of viable paths toward sustainable development and economic growth.

 

Founder and President at Data Boiler Technologies