DTCC Connection

This year, regulatory reporting requirements introduced under the Dodd-Frank Act—impacting financial institutions engaged in cross-border derivatives transactions with US counterparts—have brought attention to the management of client data. The U.S. reporting requirements form part of the global effort to reduce systemic risk and improve transparency in the derivatives markets, and in a few short months, Europe will follow suit with similar but not identical rules that necessitate the reporting of listed and OTC derivatives transactions to a trade repository. Notwithstanding some of the technical nuisances in the reporting mandates of various jurisdictions, the increased focus on trade reporting provides some thematic similarities with which institutions should consider when reviewing the impacts and action plans for compliance. Namely, more than ever before, client or counterparty data management is becoming a critical function of the new derivatives markets, increasing the focus on this area well beyond the current client on-boarding function, and Know- Your-Customer processes. In the context of the increased burden of reporting requirements, ineffective management of counterparty data has the potential to disrupt client relationships. To mitigate this, the different functions within an institution—including the front, middle and back office—will have to demonstrate a more integrated approach to client data management in order to support the compliance function, ensure successful and streamlined implementation and in turn, minimise impact on the customer experience.

Industry Concerns

Broadly speaking, the industry has supported the G20 goal to make the financial markets more stable and less risky by reforming the over-the-counter derivatives market and introducing new requirements, such as reporting. However, for institutions, the process of working out what specific rules they are required to comply with has been, in truth, a challenging process. Industry participants have already expressed concern around the complexity of reporting requirements. This is a charge that has been levied at almost all areas of the Dodd-Frank Act and the European Market Infrastructure Regulation. The concept behind reporting, of course, is a simple one: know the economic details of your trade and who you traded with; maintain accurate, up-to-date information about that trade and your counterparty; and report this information to a trade repository for the purposes of monitoring the build-up of systemic risk.

In practice, coordinating compliance with the requirements is, seemingly, much more complex. Each regulator requires a minimum set of data fields to be reported; under EMIR, additional data sets include extensive counterparty information with complex classifications, trading information and collateral data. For reporting firms, the task of cross referencing data is a daunting one but it urgently requires attention. Significant upgrades need to be made to institutions’ data recordkeeping and capture processes, and this, in turn, is prompting a wholesale examination of data quality and maintenance across the industry.

Successful implementation of reporting regulations will be determined by an institution’s ability to quickly and accurately identify, report and classify their trades and clients according to reporting criteria. The most efficient firms will work to enrich and enhance the required data with clients’ or counterparties’ legal entity data. The word ‘successful’ is important not only from a compliance perspective, but also from the customer perspective since reporting has the potential to either negatively or positively impact on the customer experience and client relationship. Essentially, if regulatory reporting is not effectively managed, and if accurate information pertaining to a particular client cannot be obtained in a timely manner and without duplicate requests, it has the potential to disrupt relationships with that client. If well-managed operationally, across the entire organisation, negative impacts can be mitigated and the client experience could even be improved, since the relationship will be based on an efficient collection process and true, meaningful, and useful information.

Holistic Approach To Data Systems

The foundation of successful implementation of reporting is integration, wherever possible, on three fronts: between departments and business functions; between processes and technology systems; and with other areas of regulatory compliance.

Firstly, different functions within an institution must share their understanding of how regulations will impact their use of data. Often times, compliance functions wait until they have a clear understanding of all aspects of a final regulation before communicating the details to other departments. This means that the wider business, including operations departments, do not fully appreciate the size and scope of the changes needed to respond to a regulation until very late in the day. An institution-wide approach is needed to develop or execute an action plan for regulations that take into account each function’s client data requirements, with the aim of developing the best regulatory response, ensuring compliance and safeguarding the client experience.

Secondly, there must be integration between processes and technologies. Currently, institutions store data and documentation in technology silos and disparate operational processes. For example, KYC data used in the on-boarding function, required for customer due diligence and reporting requirements for the purposes of curtailing money laundering practices, is rarely shared among other levels of the institution, who instead rely on their own data sources. Disparate systems and multiple views of a single customer can increase the challenges of complying with new regulations, introducing unnecessary complexity and costs, as well as frustrating clients with duplicate requests for information. This approach is inefficient and increases the risk of error, and it needs to be addressed, ideally, ahead of the implementation. The majority of firms will recognise this challenge but all too often aggressive regulatory deadlines and internal complexities push these organizations to develop more tactical fixes and perpetuate the problem. Ultimately, those institutions that are able to produce an integrated, single view of the customer benefit from a foundation for effective and efficient compliance, risk management and reporting.

Finally, the Dodd-Frank Act and EMIR should be viewed within the context of the wider regulatory reform programme, including FATCA, MiFIR and AIFMD. While these regulations are different in purpose, scope and technical requirements, they all share a common core of information and necessitate efficient and up-to-date client data processes. Institutions should therefore identify opportunities to develop a flexible, scalable model in their data management systems and processes that can address multiple regulatory requirements around a common framework.

Quality Is Key

Data quality has attracted increased industry attention as a result of the cumulative effect of forthcoming regulations. The problem of poor data has grown over time: excessive duplication; records have become dormant; and, at the same time, clients have undergone multiple changes to their legal structures and company details that, subsequently, may not have been updated in the information held by institutions. Maintaining one version of the ‘truth’ is hard enough but when you consider the complex system architecture that many firms run as a consequence of mergers and product or geographic silos, it becomes almost impossible to separate good data from bad. At best, this results in a significant operational clean-up effort, and at worse, it leads to heightened business risk. Therefore, in order to ensure compliance with regulatory requirements, data must be validated on an ongoing basis. However, each institution’s ability to manage this process is being held back by the need to focus resources on core business operations, tested by budgetary constraints, and undermined by the sheer volume of data that institutions interact with. Moreover, data management, despite perceptions, cannot survive on automated processing alone--unlike other areas of processing, automation is not the holy grail of client data management. Instead, it requires dedicated research and expertise, knowledge of where data can be sourced and checked, the ability to adapt to hundreds of languages and, ultimately, human oversight to find the definitive answer. For these reasons firms are turning to external providers to help with the process.

Collaboration Will Help

Institutions should also look to their peers to ease the burden on regulation when it comes to the process of collecting and reporting the granular information required by regulators. Sharing data cleansing and maintenance efforts across the industry and via a shared pool increases efficiency, and reduces costs. At the same time that institutions are outsourcing their requirements around data cleansing, validation and maintenance they are, perhaps in equal measure, also turning to each other, and embracing a collaborative approach to data management. Indeed, a recent report on wholesale banking by Oliver Wyman and Morgan Stanley highlighted some interesting observations on how banks faced with a drastic need to cut their cost bases should be focusing on more collaborative projects.

Integration and collaboration should be top of mind, since successful implementation will be dependent on an institution’s ability to organise themselves internally so that all functions impacted have the ability to access up-to-date, accurate information about their clients, and their status. And, ultimately, ongoing compliance will be helped by having one single point of access to the validated information needed to meet regulatory requirements—reducing the complexity of compliance and allowing firms to concentrate on core business performance.

This article first appeared in Derivatives Week, 7 June 2013.