By Martijn Groot, Vice President of Product Strategy, Asset Control
The implications of a potential roll back on regulation, from Dodd-Frank to a new level of commitment to European Market Infrastructure Regulation (EMIR) and Markets in Financial Instruments Directive II (MiFID II) as a result of Brexit negotiations, are hard to predict. While regulatory compliance, and the associated cost, is seen by some financial institutions as a significant constraint, others have come to recognise the operational benefits associated with better data management.
The difference in a market not dominated by regulatory demands is the way in which organisations can approach the timing and evolution of their enterprise data management (EDM) projects, as well as the way in which vendors will have to respond and make a new business case for investment that reflects cost and business value.
Indeed, the different approaches to EDM deployment that have evolved over the past decade on either side of the Atlantic reflect the potential for data management best practice. In the heavily regulated EU, banks have invested large sums in EDM in a bid to attain, retain and report on the diverse and complex information sources required by the regulators. And the costs are indicative: for every £1 spent obtaining data, organisations spend upwards of £10 in managing the data due to the combination of escalating data volumes and the complexity of regulatory classification demands.
In contrast, the US has a lighter regulatory touch that enables firms to take a different approach towards EDM. The approach harnesses technology largely to drive down the cost of data ownership through the adoption of scalable, flexible, subscription based and, often cloud based, solutions.
However, the situation is not, in fact, as clear cut as a ‘regulatory versus cost-based’ EDM deployment. The additional data rigour created in response to regulatory expectations has actually placed many firms on the cusp of significant financial benefit.
The focus on data modelling 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, the ability to leverage this standards-based approach to data that has been mandated by regulators will provide organisations with an opportunity to address the data management cost by eradicating much of the expensive data duplication currently in place, while also looking for internal efficiencies.
With this foundation, organisations can embrace the cost driven approach. 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.
Data management professionals should not face a battle between an investment in EDM to support regulatory objectives versus one focused on operational improvements, but a combination of the two. By leveraging the benefits of a standardised data model within a cost first mindset, organisations can attain both data flexibility and data rigour. They can slowly evolve from interim, regulatory focused solutions towards fully operationalised systems that deliver essential, long term data insight.