Open Platform: Don’t Drop EDM Efforts Based on Deregulation Assumptions

For the past decade, investment in EDM has been driven primarily by regulatory compliance requirements—at least, in the European Union. In the US, where regulation has tended to be lighter-handed, and where Basel capital rules tended to be applied to only the larger institutions, the emphasis has been towards leveraging EDM to attain cost reduction, operational efficiency and business enablement. While the full implications of upcoming Brexit negotiations are hard to predict, as is the extent of Dodd-Frank reform, it is clear that some financial markets could soon be operating without the shackles of tight regulation.

EDM Business Case

The implications of the potential rollback on regulation—from Dodd-Frank to the unpicking of the UK’s commitment to regulations such as EMIR and MiFID during Brexit negotiations—are hard to predict. While some financial institutions would clearly prefer to shake off the constraints of regulatory compliance—and the massive associated cost—others recognize that some aspects of regulatory compliance also offer operational benefits.

Stress testing and scenario management, for example, while mandated for banks in some markets, have actually been adopted by organizations outside the regulated areas because of the risk mitigation benefits they deliver. Similarly, while the retention of data for up to seven years is mandated by regulators, there are also benefits associated with the retention of long histories of quote streams or the use of data mining to improve trading strategies.

The difference, of course, in a market not dominated by regulatory demands, is the way organizations approach the timing and evolution of EDM projects. Furthermore, having spent a decade providing EDM solutions as a “must-have” option in response to specific regulatory demands, in a “regulatory-light” environment, vendors will have to step up and make a new business case for investment that reflects cost and business value as well as just compliance.

Cost Vs Control

Different approaches to EDM deployment have evolved over the past decade on either side of the Atlantic. In the heavily regulated EU, banks have invested heavily in EDM in a bid to attain, retain and report on the diverse and complex information sources required by regulators. And costs associated with data management continue to rise: for every £1 spent obtaining data, organizations spend upwards of £10 managing that data. While escalating data volumes are playing a part in this cost, the complexity of regulatory classification demands is exacerbating the problem. Legacy systems cannot manage the new data demands, leading some organizations to opt for the additional cost of fast-track, external reporting solutions.

In the US, in contrast, a lighter regulatory touch has enabled firms to take a different approach towards EDM. These companies have primarily looked to harness the technology to drive down the cost of data ownership through the adoption of scalable, flexible, subscription based, and often cloud solutions. With the right model, that data management cost can be cut in half.

However, the situation is not as clear cut as a regulatory versus cost-based EDM deployment. While the deadlines created by specific regulations have clearly led to a spike in costs as organizations scrambled to meet requirements, today many firms are actually on the cusp of gaining significant financial benefit from the additional data rigor created in response to regulatory expectations.

Data Rigor

The focus on data modeling and data scope, combined with the prescribed adoption of data standards—such as Legal Entity Identifier (LEI) for counterparties, CFI classification for financial products, and the wider adoption of standard product identifiers outside bonds and equities—provide long-term benefits. Once the initial compliance requirement has been met, organizations can begin to operationalize these standardized reporting processes and look for internal efficiencies. Of course, this is not a quick process, depending on the gradual replacement or enhancement of the current stack. However, with a robust standards-based model in place, organizations can begin to move away from the cost and risk associated with managing multiple data sources across multiple databases.

There are undoubtedly data collection and retention strategies in place today that are 100 percent focused on regulatory compliance, which may not be required within a less-regulated market. However, the ability to leverage this standards-based approach to data that has been mandated by regulators will provide organizations with an opportunity to address the data management cost by eradicating much of the expensive data duplication currently in place.

With this foundation, organizations can embrace the cost-driven approach already in place within the US. With an emphasis on buying data efficiently and achieving the lowest possible cost of ownership, firms can explore cloud deployment, scalable infrastructure, cost models that flex with usage, and a scalable data model that supports any new data structures required and created for new products.

Conclusion

Predicting the regulatory landscape is a difficult game. In 10 years, will the US and UK have turned away from Basel, MiFID II and Dodd-Frank, or will another crisis have sparked a further tightening of regulation? Organizations that have embarked upon the hard work associated with the regulatory environment created over the past decade, have embraced new data standards and invested in technologies and data management models designed to support the new data retention and reporting requirements, should not face a battle between an investment in EDM to support regulatory objectives versus one focused on operational improvements. Instead, their decisions should be driven by a combination of the two.

By leveraging the benefits of a standardized data model within a cost-first mindset, organizations can attain both data flexibility and data rigor. They can slowly evolve from interim, regulatory focused solutions towards fully operationalized systems that deliver essential data insight and, critically, they can do so using more cost effective technology, including flexible, scalable and cloud based solutions.