The Road to Dodd-Frank: Best Practices for Information Management – Part II


Partha S. Chatterjee, Principal, SunGard Global Services

Given the paucity of time, it is critical that trading and marketing organizations quickly determine the approach best suited for their organization so they can start making progress on the road to Dodd-Frank compliance.

From our perspective, we are often seeing a multi-pronged, phased approach to Dodd Frank implementation compliance, where a firm starts off with an analysis of current systems and processes in place to meet the various CFTC deadlines. This analysis is done based on comparing detailed requirements for the various Dodd-Frank rules and a thorough analysis of the current transactions – what instruments, exchanges, indexes and other key attributes determine the classification of market participant and what information to report.

Once this analysis is done, various work streams to be compliant with the different applicable rules are started. Data requirements and report creation for various rules need to be started – position limits, large trade reporting, swap data recordkeeping and real-time reporting.  This rule analysis, data requirements and design/implementation approach has borne the best fruit for many firms.


Diverse information is needed for Dodd-Frank compliance. It stretches from the deal details and primary economic terms (PET), to confirmations, position information (large trader report) to valuation data (including prices, calculated discounted delta exposure).  Information needs span counterparty, product and swap data.

Key feature of the information management approach is to create one consolidated single source of truth where the information is updated timely. From our client interaction, much of this information is already available – but, it may need to be consolidated, transformed or mapped to the proper data elements for CFTC reporting. While some new data labeling and attributes are missing and need to be created. We are seeing several pieces of information currently missing too.

This missing information falls into the following three categories:

  1. Counterparty data (e.g. legal entity identifier (LEI), swap dealer (SD)/major swap participation (MSP) classification
  2. Product data (e.g. unique product identifier, multi-asset swap indicator, asset class)
  3. Swap data (e.g. unique swap identifier (USI), block trade indicator, execution timestamp, SDR submission timestamp)

Energy marketing and trading organizations should take remediation steps after careful analysis of the data gaps, current business processes and system configuration.  Some next steps could include:

  • Capture the new data elements as part of the deal capture or through automated rules where reoccurring
  • Store the new data elements in a trading system database or a centralized data repository
  • Create mapping and/or calculation for new data elements based on existing data elements to meet new reporting, monitoring and retention requirements


Once the analysis of the rules is complete, an organization’s solution will be heavily dependent on the current systems and processes in place and their flexibility. We are seeing an emerging trend: as part of the information management solution, firms with multiple energy trading systems in play are choosing to go to an integrated risk and trading data repository. Main drivers for this decision are consolidation of information across disparate sources, single version of truth, easier reporting, and data archival requirements.

On the road to Dodd-Frank compliance, are you ready? In part III of our information management blog series, learn more about reporting, integration, and how to take the next step


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