H&R Block Analogy for CAT and Combating Fraud

It is possible to use data exhaust from Order/ Execution Management Systems (OMS/ EMS) to report data into Consolidated Audit Trail (CAT). Firms, however, will most likely run parallel systems (build on top of existing OATS reporting platform, clearing, and/or trade capture systems) given different departments operate in silos. [IMGCAP(1)]

I despise unnecessary duplicating or triplicating of data that increase vulnerability of hackers’ attacks. I also despise the burden on broker-dealers to report data to a “stale vault” when data could have been analyzed directly at its originating source. Given that, I have a “2-for-1 solution” that draws on an analogy from H&R Block for CAT data collection and combating fraud.

H&R Block is one of the 13 tax preparation companies that partnered with IRS to offer FREE* online software for Federal Tax Return reporting. The average taxpayer spends 8 hours and $110 filing personal income taxes each year (see this). To address that, H&R Block and United Way championed the ‘My Free Taxes’ initiative. Noteworthy facts from this story:

  • The IRS does not have the budget to build and provide this service on its own;
  • While collecting tax return data, the tax firms concurrently analyze the data for likelihood of IRS audit;
  • The initiative eases taxpayers’ burden in preparing income tax return, thus reducing taxpayer non-compliance and complaints.

The Flash Crash and market surveillance drivers propelled CAT as a mission critical project for the SEC. It will cost several hundred million dollars to build. The expected annual maintenance cost is more than a billion dollars. From day one, I was one of the critics of CAT project. As proposed it lacks an analytical framework embedded in the design and includes clock-synchronization challenges (see my 2016 submitted comments to the SEC here). Now, however, I see an opportunity to make it work; following is my diagnosis of the CAT project:

  1. The SEC does not have the resources to build the platform on its own;
  2. Reg. NMS mandates the Self-Regulatory Organizations (SROs: FINRA and Stock Exchanges) upgrade their surveillance systems in anticipation of CAT new and improved information;
  3. The SEC investigations team may focus their exams and limited resources on “high risk” trade irregularities, and may rely on automated surveillance to “boil the ocean” for a quick-check of everything;
  4. The current SEC commissioners are more receptive to innovative ideas from the industry;
  5. With FINRA replacing Thesys, the project may move forward quicker given their experience with OATS and their ability to rally industry support.

Putting myself into the shoes of OMS/EMS vendors, I think their reporting propositions offers advantages over the current CAT proposal: (a) the data is already there and analyzing the data where it is originated is better than secondary source/ regurgitated copies; (b) CAT data reporting can be part of the ‘front-to-back’ integration strategy for firms such as SimCorp and State Street – Charles River; and (c) FlexTrade’s cross-OMS aggregation function can be a huge competitive advantage if it can ease market participants’ concerns for data reporting differences between the U.S. regulatory requirements and Europe’s MIFID II requirements.

For us at Data Boiler, we would love the opportunity to partner with OMS/EMS vendors in helping manage the data submission part of CAT project. More so, we are interested in solving the analytical challenges for CAT and supporting the SROs in combating fraud. One of the key takeaways from the 2018 SEC roundtable on Regulatory Approaches to Combating Retail Investor Fraud is that “acting quickly is very important”. This includes: preventing more people becoming victims of fraud scams and recouping losses, as well as how to improve the FINRA trade halt authority so that it can act more quickly.

It is unfortunate that the biggest disconnect between existing ‘ex-post’ fraud investigation process and acting quickly to prevent fraud and protect investors is the sense of urgency, which only arises weeks/ months after the incident happens.  T+5 days regulatory access to CAT data (especially for flash crash investigation) definitely is too late. Typically, the first 48 hours is the most critical time to curb further abuses and prevent unrecoverable losses. Scammers/ rogues are slickdetails and speed are required to curb modern day abuses and agilely unwind to resolve complex issues across asset-classes and markets.  Given that a thousand trades can happen in between the 50 +/- millisecond tolerance time allowed by CAT, investigators need the ability to recognize irregular trade patterns despite unsynchronized clock issues.

For that, I propose the following values-added features associated with the CAT data collection process:

  Partner with a technology firm such as Data Boiler that can “boil the ocean” to handle the preliminary trade analytics for and on-behalf of the SEC, FINRA and the SROs, so as to enable a real-time detection and early warning of trade irregularities for prompt actions;

  Provide the filer with a percentage indicator that the broker/ dealer’ trade activities may be subjected to the SEC/ FINRA/ SROs exams (giving the data submitters a comfort level if their transactions are “clean” or need to be further reviewed);

  Provide a report of all identified trade irregularities to the filer, so firms can incorporate it into their Suspicious Activity Report (addressing concerns that investigators often found SARs missed reporting many issues);   

  Also, review any consistency matters, monitor changes in risk profile and other indicators to assess if firms are acting in clients’ Best Interest (rather than in conflict or disregard of fiduciary principle);

  Work with the SEC, FINRA, and SROs to help build the industry’s next generation systems that consist of: trade reconstruction, order book replay simulator, advanced pattern recognition techniques, RENTD calculator, crowd computing, and more.

  Last but not least, support small investors by granting them a FREE* basic version of related analytical tools in order to level the playing field in the equity market.

The US public stock market is envy of the World. Yet, its significance is thwarted by a few greedy participants who take advantage of the system. Thankfully, the SEC and FINRA support investor protection, including but not limited to, enhanced transparency and disclosures, re-examining of 15c2-11 piggyback exception, possible revision to penny stock definition, scrutinizing transfer agent and other practices.

Last, I’d like to use a quote by Jonathan Swift – “Laws are like cobwebs which catch the small flies and the wasps and hornet break through” – to remind everyone that combating fraud isn’t just about pinning down small advisors who may have few lapses; there should be comprehensive investor protection against rogues of all sizes.

In the next article, I’ll unveil the solutions in solving the NMS market data fairness issue, so stay tuned.

Revisit previous articles in the series by clicking below links:

  1. Pilot May Lose Direction When New Exchanges Appear
  2. Animal Farm and Market Data: Negotiate to be ‘More Equal’
  3. Warring States Period, Finding New Equilibrium
  4. Missed Opportunities for Average Investors
  5. Indirectly Helping the Thinly-Traded Securities Segment

Kelvin To is Founder and President of Data Boiler Technologies