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: Detecting and preventing market abuse

Market abuse – unlawful disclosure of inside information, insider trading, circular trading, “pump and dump” schemes, etc. – poses significant threats to the integrity of capital markets. In 2024, global trading house Trafigura agreed to pay a $55 million fine to the U.S. Commodity Futures Trading Commission (CFTC) for trading with non-public information, manipulating a...

BLOG

FinScan Data Quality Chief Seeks to End Compliance Failure Excuses

The dog ate my homework. The train was delayed. The postman mislaid your birthday card. At one time or another, we’ve all used a weak excuse to forestall censure for an error of behaviour or judgement. And mostly, we’ve got away with it. In financial regulatory compliance, however, excuses won’t wash. Especially when it comes...

EVENT

ESG Data & Tech Briefing London

The ESG Data & Tech Briefing will explore challenges around assembling and evaluating ESG data for reporting and the impact of regulatory measures and industry collaboration on transparency and standardisation efforts. Expert speakers will address how the evolving market infrastructure is developing and the role of new technologies and alternative data in improving insight and filling data gaps.

GUIDE

AI in Capital Markets: Practical Insight for a Transforming Industry – Free Handbook

AI is no longer on the horizon – it’s embedded in the infrastructure of modern capital markets. But separating real impact from inflated promises requires a grounded, practical understanding. The AI in Capital Markets Handbook 2025 provides exactly that. Designed for data-driven professionals across the trade life-cycle, compliance, infrastructure, and strategy, this handbook goes beyond...