Mapping a Maze of Data
To understand the complexities, it is helpful to review the process as it relates to the NASD's Order Audit Trail System. OATS requires member firms to report each event in the life cycle of an order -- from receipt or origination through routing, execution or cancellation -- for all Nasdaq-listed stocks.
A single order to sell a block of shares via an algorithmic engine potentially is broken into thousands of smaller orders. Some of these orders are executed in-house, while others are sent to ECNs, direct market access (DMA) providers and market centers. Each of these "child" orders must be tracked via a unique order identification number, traced back to the original parent order and reported to OATS by 4 a.m. the next day.
This may seem like a straightforward data extraction exercise. But as broker-dealers have grown over the years through mergers and acquisitions, it is common for a single firm to operate more than a dozen order-entry and middle-office systems, many hosted on mainframes or on distributed computing platforms. The complexity of transactions and processing systems, the volume of data records, and the potential for errors are enormous. And new requirements, such as Reg NMS, further increase reporting complexity.
With the enormous volume of security trades occurring every business day, regulators are concerned that fraud and noncompliant activities have become increasingly hard to find. The potential for discovering front-running -- the unethical practice of brokers trading for their own accounts before filling a customer's order -- means sorting through potentially millions of transactions and looking for suspicious activities.
In addition to trade reporting, which enables regulators to uncover unethical activities, firms also are required to perform their own due diligence to uncover these activities as part of their supervisory procedures. To stay one step ahead of regulators, firms are beginning to enhance their trade reporting and surveillance processes and technology solutions. The following are ways in which some firms are reacting to the evolving regulatory requirements:
• Implementing data warehouse systems to assist with regulatory reporting and trade surveillance.
• Enforcing common source systems data interfaces to reporting and surveillance technologies.
• Augmenting existing controls and supervisory procedures.
• Performing analytical procedures on source system trading data and data warehouses to determine whether regulatory reports have been accurately submitted.
• Enhancing the monitoring of matching customer orders.
• Adding to the functionality of smart-order-routing engines to ensure best execution via Intermarket Sweep Orders.
• Adding links to more market quotation services.
• Increasing computing power to provide for the requirement of real-time market data.