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

Finding a Balance Between Standards and Flexibility in Data Architecture

Subscribe to our newsletter

The integration of standards and flexibility into data architecture is an ongoing challenge for financial firms that must not only improve operational efficiency, but also sustain adaptability to support business and regulatory change. Both are important, but potentially opposed to each other, begging the question of how best to find an optimal balance between standards and flexibility. This question will be discussed at A-Team’s forthcoming Data Management Summit in New York, but before the event we caught up with Brian Buzzelli, senior vice president, head of governance at Acadian Asset Management, and John Yelle, vice president at DTCC, to canvas their opinions on how to balance standards and flexibility.

Buzzelli describes a continuum from flexibility and no standards to numerous standards and suggests the optimal balance is the right amount of standards to ensure operational efficiency and a framework providing an understanding of data and business processes that allows flexibility and can position a firm for change.

He balances flexibility and standards to deliver what he calls Service Level Expectations (SLEs), which ensure the inclusion of data aspects such as quality, accuracy and timeliness in business processes. When business functions with SLEs send data to the next machine, this machine also has an SLE. He explains: “This integrates standardisation between business functions at the business level. It’s like a manufacturing process for finance data that includes metrics such as data quality, completeness and packaging.”

Yelle agrees on the importance of integrating both standards and flexibility, and takes into account different types of standards, particularly external standards such as ISO standards and messaging specifications that benefit interoperability and internal standards that are designed to support policies and influence behaviours.

He sees a move away from standards that were historically based on technical issues and a move toward standards for the business side, such as standards for data governance processes. Most firms will use a mix of external and internal standards, but more external standards are expected to be implemented to improve interoperability between financial institutions and provide better regulatory insight into risk.

On flexibility, Yelle says: “It could be argued that standards improve flexibility as solid foundations built on standards can be adapted without the need for reinvention. This is ideal, but not easy to get to as most firms are dealing with legacy systems.”

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: Strategies and solutions for unlocking value from unstructured data

Unstructured data accounts for a growing proportion of the information that capital markets participants are using in their day-to-day operations. Technology – especially generative artificial intelligence (GenAI) – is enabling organisations to prise crucial insights from sources – such as social media posts, news articles and sustainability and company reports – that were all but...

BLOG

Ensuring AI-Focussed Institutions Take out the Garbage: A-Team Group Webinar Preview

As data quality rises up institutions’ AI-implementation agendas, the next A-Team Group Data Management Insight webinar will take a deep-dive look into how they can ensure the information they feed into their models will give them accurate and valuable outputs. Avoiding Chaos The data management maxim of “garbage in, garbage out” can’t be more appropriate for artificial...

EVENT

AI in Capital Markets Summit London

The AI in Capital Markets Summit will explore current and emerging trends in AI, the potential of Generative AI and LLMs and how AI can be applied for efficiencies and business value across a number of use cases, in the front and back office of financial institutions. The agenda will explore the risks and challenges of adopting AI and the foundational technologies and data management capabilities that underpin successful deployment.

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...