About a-team Marketing Services
The knowledge platform for the financial technology industry
The knowledge platform for the financial technology industry

A-Team Insight Blogs

Data Management Experts Discuss the Dilemmas of Data Quality

Subscribe to our newsletter

Data quality has become an imperative for financial institutions as they face increasing regulation and look to data for business benefits and opportunities – but it is not always easy to achieve and requires significant investment in time and resources.

For many institutions, a definition of data quality is based on some or all of the data characteristics set out in regulation BCBS 239 and including accuracy and integrity, completeness and timeliness. Defining data quality can be a good start to improvement projects, but how good should data quality be, how can it be measured and demonstrated, and how can data quality be geared to different business processes?

These are just some of the issues that will be discussed during a panel session on data quality at next week’s A-Team Group Data Management Summit in London.

Fiona Grierson, enterprise data strategy manager at Clydesdale Bank and a member of the panel, has been developing data quality at the bank for about three years. The bank defines data quality as data that is complete, appropriate and accurate, and uses the Enterprise Data Management Council’s Data Management Maturity Model to score data quality and drive improvement. It also has a data management framework for projects to ensure they are implemented using best practice around data quality.

Grierson explains: “We look at the business case for particular strategies and consider the data quality requirement. For example, we look at regulations and the extent of their data quality requirements and at customer initiatives and their need for data quality to ensure seamless customer service.”

Grierson will be joined on the data quality panel by practitioners including Jon Deighton, head of global efficiency and strategy for UK data management at BNP Paribas Securities Services; James Longstaff, vice president, chief data office, at Deutsche Bank; and Neville Homer, head of RWA reference data, regulatory reporting, at RBS.

To find out more about:

  • Regulations driving data quality
  • Approaches to improvement
  • Data quality metrics
  • Technology solutions
  • Practitioner experience

Register for next week’s A-Team Group Data Management Summit in London.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: How to organise, integrate and structure data for successful AI

Artificial intelligence (AI) is increasingly being rolled out across financial institutions, being put to work in applications that are transforming everything from back-office data management to front-office trading platforms. The potential for AI to bring further cost-savings and operational gains are limited only by the imaginations of individual organisations. What they all require to achieve...

BLOG

Growing Modern Data Platforms Adoption Seen as Benefits Become Apparent: Webinar Review

Take-up of modern data platforms (MDPs) is expected to accelerate in the next few years as financial institutions realise the greater agility, scalability and deeper insights offered by the innovation. Organisations that have so far been relatively slow to adopt the streamlined platforms – because they have been unsure of the technologies’ benefits – will...

EVENT

Eagle Alpha Alternative Data Conference, London, hosted by A-Team Group

Now in its 8th year, the Eagle Alpha Alternative Data Conference managed by A-Team Group, is the premier content forum and networking event for investment firms and hedge funds.

GUIDE

Regulatory Data Handbook 2025 – Thirteenth Edition

Welcome to the thirteenth edition of A-Team Group’s Regulatory Data Handbook, a unique and practical guide to capital markets regulation, regulatory change, and the data and data management requirements of compliance across Europe, the UK, US and Asia-Pacific. This year’s edition lands at a moment of accelerating regulatory divergence and intensifying data focused supervision. Inside,...