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

A-Team Insight Blogs

Divisions Between Market and Reference Data Causing Issues for Transparency, Says GoldenSource

Subscribe to our newsletter

A major hurdle to achieving a consistent view of pricing, positions and exposure lays in the divide between market data feeds and reference data repositories, according to GoldenSource, a provider of enterprise data management (EDM) solutions.

“By definition, enterprise risk management and reporting should go front to back as well as across assets,” says Gert Raeves, vice president of strategic business development at GoldenSource. “A trusted data environment for interdependent front and back office processes now relies on the centralisation of market and reference data. With market data, there is a convergence point where a snapshot of the market can be captured and validated for downstream applications.”

Pricing mechanisms in the front office and valuations for P&L in the back office often depend on the same price and rate data, yet both areas derive this information from disparate sources. According to research from consultancy A-Team Group, 87% of risk managers are interested in centralising market and reference data. This is to address issues including volatility, accuracy, consistency and the elimination of asset-based silos.

Unprecedented market movements are impacting portfolios, customers, counterparties and issuers faster than ever, meaning back office risk and P&L systems can no longer wait until end of day to access critical market data. Regulators are expecting much of the same data used in the trading decision process to be extended to valuation, P&L and risk management, thus bringing the same issues around accuracy and consistency to both data areas.

Regulatory and client demands for insight into how a value was derived means that golden copy pricing needs to extend beyond static reference sets and include multiple market data sources, says the vendor. Furthermore, siloed desks have traditionally been blamed for the inability to get a complete view of risk and exposure; these silos are now being broken down, yet the divide between market and reference data persists.

Subscribe to our newsletter

Related content

WEBINAR

Recorded Webinar: The ROI of Data Trust: Quantifying the Business Value of Data Observability

Data is the fuel that keeps modern financial institutions’ motors running but if that data can’t be trusted then the decisions made based upon it, or the uses to which its put, will be compromised. That’s especially important for data that’s fed into artificial intelligence models. If the data isn’t clean, accurate and complete, then...

BLOG

AI Agents Need Better Data, Not Bigger Models – Daloopa Benchmark

AI-powered fundamental and historical data provider Daloopa has published new benchmark research examining how well leading AI agent systems perform on real-world financial research tasks. Titled Benchmarking AI Agents on Financial Retrieval, the study evaluates whether recent advances in agentic AI translate into reliable outcomes when accuracy matters most. The benchmark focuses on a core...

EVENT

AI in Capital Markets Summit London

Now in its 3rd year, the AI in Capital Markets Summit returns with a focus on the practicalities of onboarding AI enterprise wide for business value creation. Whilst AI offers huge potential to revolutionise capital markets operations many are struggling to move beyond pilot phase to generate substantial value from AI.

GUIDE

AI in Capital Markets Handbook 2026

AI adoption in capital markets has moved into a more disciplined phase. The priority is now controlled deployment: where AI can be used safely, where it can deliver measurable value, and how outputs can be governed, monitored and evidenced. The 2026 edition of the AI in Capital Markets Handbook examines how AI is being applied...