Regulatory reform, competitive pressures and the need to optimize data across the enterprise are pushing custodians, service providers, consultants and securities firms to refine their data management strategies.
Organizations have been trying to reach a golden source for reference data for some time, but the lack of data standards have made this difficult – different exchanges, asset classes (e.g. equities versus equity options), different regulatory environments, different systems utilize different elements of data.
“Few organizations have been able to implement a single data source,” said Alberto Corvo, managing principal, financial services at eClerx. “However, up and coming initiatives like LEI should make this easier to achieve.”
Legal entity identifier (LEI) is a global program designed to create and assign unique identifiers to every financial organization that engages in a financial transaction.
Regulators will use LEIs to better gauge systemic risk, and risk managers at financial institutions will use LEIs to better understand and aggregate counterparty exposures and risk.
“A lot of investments are now being carried out in the space to achieve the golden source status,” said Corvo. “We are helping a lot of organizations both on the consulting/design phases and the implementation and data normalization/clean-up phases.”
Counterparty exposure underpins most derivatives transactions, yet both regulators and market participants have yet to come up with an all-encompassing approach to measuring it.
“The first wave of derivatives targeted under the Dodd-Frank Act was credit derivatives, but regulations need to include all types of derivatives,” said Else Braathen, domain manager for risk management at SimCorp. “Reference data is the glue that ties all these things together.”
Although Dodd-Frank has not specifically identities all types of counterparty exposures, it’s inevitable that firms will be mandated to account for them.
“As a result, Dodd-Frank is an obligation, but more importantly, an opportunity for firms to comprehensively address exposures across the enterprise,” said Braathen. “Dodd-Frank should be a catalyst for change, prompting a move from risk management to risk ownership.”
Firms have created multiple hierarchies for classifying data, such as organizing data by client, process and system levels, which adds to the complexity.
“Data tends to be scattered across different systems, and with different formats/naming conventions and nomenclatures,” Corvo said. “Maintaining multiple hierarchies can have a detrimental effect on data quality. The key is to have a coherent strategy and optimization of the approach to the implementation, maintenance and distribution of golden source data across the institution.”