The SEC is in the midst of an unprecedented transformation in the way the agency plans to utilize state-of-the-art monitoring systems and enforce securities law violations. But that means arduous and costly new data reporting obligations for the financial services industry.

Currently, the SEC in sci-fi-like fashion is losing its battle with the robot traders of Wall Street, where high-frequency trading now dominates the market. With the scope and quantity of market data reaching breakneck speed, the SEC must continuously seek out new and innovative ways to catch up to, and keep pace with, the rapidly changing securities market by leveraging advances in technology.

“Throughout the agency, we are increasingly harnessing technology to better identify risks, uncover frauds, sift through large volumes of data, inform policymaking, and streamline operations,” former SEC Chair Mary Jo White once remarked in congressional testimony. The SEC’s enhanced monitoring capabilities continue to pay dividends, creating efficiencies and capabilities that were once impossible, she said.

The Commission took its biggest leap forward in November 2016, when U.S. market regulators unanimously approved a national market system (NMS) plan to create the largest data repository of securities trading activities that has ever existed, widely known as the “Consolidated Audit Trail” (CAT). Representing the culmination of years of effort, the CAT will capture—in a single, data warehouse—financial transaction information from a variety of equity markets.

Such Big Data capabilities will be leaps and bounds ahead of the SEC’s current dependency on an ad-hoc aggregation of disparate data from a wide variety of existing information systems lacking in completeness, accuracy, and timeliness.

The CAT will even go beyond the data analytics capabilities of the SEC’s Market Information Data Analytics System (MIDAS). MIDAS enables the SEC to collect one billion records of trading information data per day, each time-stamped to the microsecond—a process that once took SEC staff months to achieve.

MIDAS captures all orders posted on national exchanges; modifications and cancellation of those orders; trade execution of those orders; and off-exchange executions. Whereas MIDAS collects vast quantities of public trading data, however, the CAT will capture non-public data as well—for example, the identities of the customers behind the trades, not just the brokers who handled them.

That means the CAT effectively will make it more difficult to spread orders across different brokers and mask illegal trading activity. “The expected benefits of the CAT for regulators include improving our ability to conduct market research, reconstruct market events, monitor market behavior, and identify and investigate market misconduct,” White said.

The CAT will be to the SEC what satellite imaging is to land surveyors, recognizing patterns that otherwise would be impossible to identify by surveying land atop a hill one plot at a time. “The CAT would essentially be the Hubble Telescope for the securities markets,” said Commissioner Kara Stein.

“Throughout the agency, we are increasingly harnessing technology to better identify risks, uncover frauds, sift through large volumes of data, inform policy-making, and streamline operations.”
Mary Jo White, Former Chairman, SEC

Approval of the CAT NMS plan now puts the wheels in motion for selecting a plan processor to build and manage the $2.4 billion system. According to the SEC, the CAT should be largely operational by 2018, when large broker-dealers must begin reporting their activity, followed by small broker-dealers the year after that.

Data reporting requirements. Broker-dealers who trade in U.S. equity and options markets will have to meet stringent new data reporting requirements. Throughout the various stages in an order’s lifecycle—from inception through routing, modification, cancellation, or execution—broker-dealers must submit certain information about the order to the central repository.

Such information will include:

A unique identifier, provided by the broker-dealer, for the customer submitting the order;

An identifier for the broker-dealer originating, receiving, routing, or executing the order;

The date and time of the order event; and

The security symbol, price, size, order type, and other material terms of the order.

According to the CAT NMS plan, broker-dealers would be required to synchronize their business clocks to within 50 milliseconds of the time maintained by the National Institute of Standards and Technology (NIST). Business clocks used for manual orders or the time of allocation would be able to be synchronized to within one second of the time maintained by the NIST.

Although it’s still too early to say at this point exactly what type of changes broker-dealers will have to make to their process and systems, “we certainly know that it’s going to have a major impact on the technology side,” says Kevin Trimble, a managing member of Global Markets Advisory Group (GMAG).

Furthermore, the CAT eventually will eliminate current legacy systems—such as the Order Audit Trail System (OATS), electronic blue sheets, and large-trade reporting—but such isn’t expected to happen overnight. Instead, these legacy systems will have to be sunsetted on a rolling basis. From a compliance standpoint, that means broker-dealers will have to dual report on some of these systems until the CAT is up to speed and working correctly, which may not be for another three to five years, says Charlie Dolan, also a managing member of GMAG.

Cost implications. Meeting these data reporting requirements also will impose significant new cost burdens on broker-dealers, who are going to have to foot most of the bill. The SEC estimates that total annual cost of the plan would be $1.7 billion, of which $1.5 billion will fall on broker-dealers to meet their data reporting requirements.


Below are some examples of Frequently Asked Questions about the Consolidated Audit Trail.
What is the Consolidated Audit Trail (CAT)?
The CAT is a comprehensive audit trail that will track orders throughout their lifecycle and identify the broker-dealers handling them, thus allowing regulators to more efficiently and accurately track activity in Eligible Securities throughout the U.S. markets. The CAT is being created by a joint plan (CAT NMS Plan) of the 20 national securities exchanges and FINRA (collectively the SROs). The CAT NMS Plan details the creation, implementation and management of the CAT. When complete, the CAT will be the world’s largest data repository for securities transactions tracking approximately 58 billion records of orders, executions, and quote life-cycles for equities and options markets on a daily basis. Broker-dealers will be required to report into the CAT all reportable order events, including quotes, orders, executions, and allocations, as well as customer data associated with these orders.
What steps are the SROs taking now that the CAT has been approved?
With the approval of the CAT NMS Plan, the SROs are focusing on the implementation of the CAT Central Repository. A Plan Processor to build and operate the Central Repository must be selected by January 15th 2017. SROs must begin reporting by November 15th 2017, large broker-dealers by November 15th 2018, and small broker-dealers by November 15th 2019.
What securities will need to be reported to the CAT?
Initially, the CAT NMS Plan will cover all NMS Securities (which includes NMS stocks and listed options) and OTC Equity Securities. Within six months after the effectiveness of the CAT NMS Plan, the SROs must outline how information with respect to equity securities that are not NMS Securities or OTC Equity Securities and debt securities, including Primary Market Transactions in securities that are not NMS Securities or OTC Equity Securities and debt securities, could be added to the CAT.
What orders are reportable?
SEC Rule 613 and the CAT NMS Plan define the term "order" as any order received by a member of an SRO from any person; any order originated by a member of an SRO; and any bid or offer.
Who is required to report?
The SROs and all members of an SRO on a rolling basis:
By one year after the Plan becomes effective, all SROs.
By two years after the Plan becomes effective, all members of an SRO, except small broker-dealers, as defined in SEC Rule 0-10(c).
By three years after the Plan becomes effective, all SRO members that are small broker-dealers.
What is required to be reported to the CAT?
The following events in the lifecycle of an order must be reported to the CAT:
Receipt or origination;
Routing of an order to another broker-dealer, national securities exchange or foreign exchange;
Routing of an order between desks or departments within a broker-dealer;
Cancellations; and
In addition, certain customer identifying information must be reported to the CAT.
Source: CAT NMS plan

One of the biggest unknowns for the broker-dealer community is how costs will be allocated: Will it be by the amount of data submitted by the member, or by the size of the firm? “There is a lot of unknown on the cost of this, which is not inconsequential,” Trimble says. 

Another significant issue for broker-dealers is not having the ability to access information submitted to the SEC and self-regulatory organizations (SROs). From a compliance standpoint, broker-dealers want as much information as they can get to mirror the SEC’s surveillance capabilities by using the same data.

If the SEC is looking at a specific sequence of trading data, for example, the ability of broker-dealers to see if they’re capturing all of that same information would be invaluable, Trimble says. “The fact that broker-dealers have to pay for it, and not be able to access the data, I think, is problematic.”

Staff expertise. Aside from technological advances, the SEC has also made enhancements to its staff, further advancing the agency’s ability to handle data with more rigor. An important part of this effort has been the SEC’s Center for Risk and Quantitative Analytics (CRQA).

Armed with experts in the field of accounting, computer programming, economics, and mathematical finance, the CRQA plays an important role by assisting the SEC Enforcement Division in several ways. For example, sometimes when SEC enforcement staff is working on an investigation, they may need further evidence for a case, but don’t know how to find the data, “so we work with them as subject-matter experts to help get the data they need, get it in the form that it’s needed, run the analysis, and provide them with the results,” says Lori Walsh, chief of the CRQA.

Examples of primary areas the CRQA focuses on include insider trading, market manipulation, accounting fraud, financial fraud, as well as trading abuses in structured products and municipal securities, “but we’ll focus on just about anything that is of potential interest to enforcement,” Walsh says.

SEC staff is also getting much more adept at working with one another. “We are becoming much more coordinated across the different divisions and offices in terms of how to handle data, how we store data, how we manage data, the types of analytics we do, not duplicating efforts in different divisions and offices, and finding synergies across different types of analytical initiatives within the Commission,” Walsh says.

“I believe our coordination across the Commission is going to provide a lot of value in terms of being able to use the data,” Walsh adds, referring to the CAT. “We have a tremendous amount of valuable data in the Commission already that we haven’t fully utilized, and this going to help us more fully utilize this data.”

Proactive risk mitigation. Between the SEC’s advanced monitoring capabilities and its skilled staff, compliance departments in the financial services space are being challenged to be equally innovative in their ability to detect and deter unwanted or illegal behavior.

Right now, the financial services industry is at an inflection point, where the use of Big Data, done right, can drastically improve a firm’s risk mitigation techniques. “You need to make sure you’re investing in not just the right technology, but the right team,” says Brian White, chief operating officer at RedOwl, an information-security and regulatory surveillance firm.

Many compliance teams still depend too heavily on antiquated technologies that look only at small subsets of data, often concentrating on the highest risk individuals in the organization. Financial services firms today, however, have the ability to integrate vast and various amounts of data sources—both structured and unstructured—to get holistic visibility of human risk across the entire enterprise.

Best practice data analytics capabilities include, for example, the simultaneous monitoring of things like e-mails, social networking chat, trades, physical trading activity—such as entering and exiting a trading floor—and much more. “To us, it is multiple techniques,” White of RedOwl says.

First and foremost, a financial services firm needs to be honest about its unique level of risk tolerance and what it defines as a threat. “You need as much context as possible,” White says. Defining risky behavior comes first.

Information-sharing initiatives can be an important aspect of that educational piece. “There is a real thirst from our customers and our partners to learn what others are doing in this industry,” White adds. They’re starting to realize that they don’t on their own have all the answers and that they need to leverage knowledge, he says.

One way financial services firms can proactively mitigate illegal trading activity, for example, is to collaborate with one another through a “lexicon sharing initiative,” says David Pogemiller, vice president of customer success at RedOwl. RedOwl is working with a few financial services firms on one such initiative right now, Pogemiller says.

Currently, compliance departments at many financial services firms create their own confidential lexicons that they use to conduct automated searches of employees’ e-mails, monitoring for key words and phrases that may indicate illegal activity. “We’re basically trying to build an initiative in which firms can collaborate and share the knowledge of the lexicon instead of doing all those time-intensive efforts on their own,” Pogemiller says.

After the company has a firm grip on what it considers risky behavior, then the question becomes how to bring all that information together. That’s where the technology aspect comes into play.

“You want a piece of technology that is a force multiplier,” White says. It’s about efficiency and effectiveness, he says.

Real-time monitoring also will become increasingly important. “That’s one of the challenges that legacy monitoring tools have,” says Jim Berkman, head of global marketing at cPacket Networks, a next-generation network performance monitoring and analysis solutions provider.

To help address the increasing volume and velocity of financial data networks, cPacket recently announced the launch of cBurst, a high-resolution stream analysis and predictive behavioral analytics feature for trading exchanges and financial service firms. cBurst is capable of real-time monitoring of 1,000 data streams per port at one-millisecond resolution, which purports to offer 1,000 times higher resolution than competitive solutions.

Such real-time monitoring capabilities enable detection of microbursts and proactive alerts of imminent network performance issues before they impact end-users. By identifying problems in advance, financial services firms can take corrective action before their user’s trades are impacted.

Additionally, because every single trade is time-stamped with “atomic clock-level accuracy,” Berkman says, cPacket can also help detect illegal trading activity. “Time-stamping gives that level of transparency,” he says. If one trade comes in before another, the time stamp will reflect that, ensuring that trades are happening in a fair and equitable way.

As data analytics become more sophisticated, the implementation of any technology should never replace the human aspect, but rather help people do their jobs quicker, better, more efficiently, and in a way that they can derive insights that they wouldn’t normally be able to do without an innovative solution in place.

The good news is that financial services firms today have all the tools they need to detect and deter unwanted and illegal behavior, ensuring they stay one step ahead of SEC oversight in the Digital Age. Now they just need to start to harness all that power.