Data Management Insight Data Quality The latest content from across the platform

Embracing Automation and Collaboration Tools to Inject Reference Data into the Trade Lifecycle

Digital transformation in the financial services sector has raised many questions around data, including the cost and volume of reference data required by each financial institution. Firms need flexible access to the reference data required to ensure workflows can proceed without interruption. ‘One-size-fits-all’ bulk data licensing models are increasingly less fit for purpose. Emerging solutions…

Can ‘Observational Learning’ Help Improve Data Quality?

Data quality is a pre-requisite for financial institutions seeking to automate their operations. But given the huge volumes of transaction data, often in a wide array of formats, it is very difficult to achieve. Can newer AI-based techniques such as observational learning actually help or are they just hype? This white paper explores: What observational…

How to leverage the LIBOR transition to improve your data management game

The final goodbye to Libor has been described as the Y2K moment for data managers in financial services – and with the phase-out slated for the end of 2021, firms need to act now to ensure a smooth transition. The replacement of Libor with alternative benchmarks presents an immense challenge for financial institutions, especially given…

A Holistic View of Risk Across the Enterprise: How Data Linkages Help

Gaining a comprehensive view of their risk exposures has long been a challenge for financial institutions. Standard measures have been embraced to measure and manage market risk, and the emergence of a standard legal entity identifier in the form of the LEI has gone some way toward addressing the issues of counterparty and credit risk…

Preparing for MiFID II Data Requirements

Markets in Financial Instruments Directive II (MiFID II) is a wide-ranging regulation that aims to add transparency to Europe’s financial services sector in order to ensure investor protection and integrity of markets. The regulation extends the scope of MiFID, which focused on equities, to cover pre-trade, trade and post-trade activities across many asset classes. This…

Applying Open Data Principles to Financial Data Governance

To ensure sound data governance, an enterprise needs a centralised framework for understanding all data, typically an online data catalogue that lists data sources and the metadata that describes data characteristics and provenance. With a data catalogue in place, data quality and data management can then be addressed. Getting started on data governance can be…

Building the Business Case for Joining the Reference Data Utility

The benefits of joining a reference data management utility include the ability to improve data quality, simplify complex data management infrastructures, meet constantly expanding and changing regulatory requirements, and realise significant reductions in operating costs. This White Paper, sponsored by SmartStream, describes four business cases that can be addressed by adopting a utility-based approach to…

Entity Data Quality: New Approaches and the Four Categories of Data Quality Management

Legal entity data is critical to data strategy, business decisions and regulatory compliance, but it can be a challenge to ensure the data is accurate and reliable as the entity universe is large, millions of attributes change every year and inconsistent codes and symbologies identifying  entities, corporate hierarchies and ultimate beneficial owners must be managed….

The Reference Data Utility: How Goldman Sachs, JPMorgan Chase & Co and Morgan Stanley are breaking the reference data mold

The Reference Data Utility (RDU) built by SmartStream and backed by Goldman Sachs, JPMorgan Chase & Co, and Morgan Stanley is up and running and ready to deliver reference data management services to the banks. The concept of multi-tenant data utilities is not new, but none have achieved buy-in at the level of the RDU,…

The Role of Technology in Data Management

Data managers are tackling the issues of managing and distributing accurate and timely data across their organisations with the assistance of highly automated technology solutions. While technology plays a leading role in data management, there are other issues to consider, including product selection, procurement, project management and ongoing business development. MJC Data Management Solutions suggests…