In December 2013, the Office of Comptroller of the Currency (OCC), Board of Governors of the Federal Reserve System (The Fed), Federal Deposit Insurance Corporation (FDIC), US Securities and Exchange Commission (SEC), and the US Commodity Futures Trading Commission issued regulations implementing section 619 of the Dodd Frank Act, commonly known as the Volcker Rule. Of all the requirements of the Volcker Rule, Reasonably Expected Near Term Demand (RENTD) remains the most abstract, prescriptive, and challenging for financial professionals to interpret and implement.
The Volcker Rule is complex and as such, we will not explore it in its entirety here. Below is a brief overview of key areas*:
- Proprietary trading: This prohibits a banking entity from serving as a principal for its own trading account in the purchase or sale of financial instruments.
- Covered funds: Activities and Investments prohibiting banking entities, as a principal, directly or indirectly acquiring or retaining an ownership interest or sponsoring a “covered fund.” The definition of covered funds no longer captures foreign retail funds, certain loan securitization vehicles or most commodity pools.
- Compliance programs: Designated as standardized and enhanced programs based on gross trading assets and liabilities, requires annual CEO attestation on the compliance design and effectiveness.
- Hedging: Activities that distinguish between market making, hedging and risk mitigating hedging.
- Trading activities of foreign banking entity.
- Trading in government obligations.
- Quantitative measurements: Entails seven metrics across three categories.
- Liquidity management: Requires financial institutions to have documented liquidity plan.
Fundamentals of Reasonably Expected Near Term Demand (RENTD)
RENTD is essentially a measurement of financial instruments and related risks that a trading desk carries at any point in time. In short, to qualify as reasonably expected near term demand, the amount of securities or derivatives positions held in inventory needs to be reasonably related to external demand. That is, what the desk needs to maintain to be able to trade with its customers, when and in the amount, they want to trade.
Huh? This is the common reaction from financial professionals within the industry. The definition of RENTD is not descriptive in what financial institutions must do to adhere to the regulation. Simply put, financial institutions must separately manage each desk’s market maker inventory and overall financial exposure. They must do the following:
- Identify and measure its trading desks that engage in market making related activities.
- Document ownership interests in covered funds and desks (securities, derivatives, and futures)
- Develop a process for measuring and documenting RENTD
Key Regulatory Challenges and Solutions: RENTD
The section below provides examples of specific challenges that arise from RENTD along with how native visual analytics address those challenges. Native visual analytics optimizes regulatory programs because it enables the subject matter experts to run their own analytics natively (where the data resides) and join any type of data. This capability is critical for enabling accurate and timely reporting that can adapt to evolving interpretations of requirements.
|Regulatory Challenge||Enablement Via Visual Analytics Capabilities|
|Adapt to Change: Firms are faced with the daunting challenge of aggregating enterprise-wide data for both market making and customer trading activities while the definitions of the two continue to evolve.||Native visual analytics enable business and regulatory analysts to adapt to an evolving definition of “market making” through on-demand access to multiple data sources and by creating data apps that they can revise and edit as needed.|
|Measuring Customer Facing Activity: The essence of RENTD is not the measurement of product inventory, but aligning that inventory to customer demand. This requires constant monitoring, measuring, and reporting of three factors: how fast products are bought and sold, how long those product remain in inventory, and the expected trend of demand for those products.||Native visual analytics greatly enhances a firm’s ability to monitor, measure, and report changes in RENTD and its market maker inventory because direct access to both real-time and historical data sources provides business users with deeper insight into quantitative relationship between customer and desk trade activity.|
|Transparency of Market Making Conduct: Firms need to distinguish between trade activity that is done on behalf of a customer and direct to market activities within the context of RENTD in a transparent fashion.||The correlation between customer trading demand and market making activities can be made transparent with native visual analytics. Subject matter experts can join trade data from respective sources on-demand and enrich their analysis further by connecting secondary data sources as needed. Transparency provides a timely and insightful understanding of how customer demand relates to trading inventory.|
Native visual analytics unifies data discovery, business intelligence, and real-time visualization in a single, integrated platform. It provides users with direct access to big data (it runs natively on Hadoop clusters to leverage its capabilities) through an intuitive and self-service interface. Referring to the examples above, a team can explore billions of rows of highly varied data, join views into interactive packages, and share that package with relevant colleagues to solve problems in a timely, secure, and collaborative way.