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

ING Investment Management Has Banned the Term ‘Golden Copy’, Says Murphy

Subscribe to our newsletter

Proving that for some institutions the approach to data management is changing dramatically, Nick Murphy, data specialist for pricing and evaluations at ING Investment Management, told delegates to last week’s FIMA that his own firm has banned the term “golden copy” from use. The focus is on maintaining centralised and standardised data for instruments, but it is also about meeting the requirements of the internal business users, he said.

The number one priority for data management is to get recognition of the fact that reference data is an asset to an organisation, said Murphy, reprising a theme that many other speakers elaborated upon at this year’s FIMA. It is often undervalued by the business and quality is frequently sacrificed to lower costs, he said.

Other priorities at the moment include coping with the globalisation and standardisation of data by tackling the issue of data governance (a point also raised by fellow buy side representative from UBS Ian Webster) and the continual challenge of dealing with a siloed environment. In order to help it deal with this environment, the firm is currently implementing a new data management solution from Cadis for its static and market data, which Murphy hopes will allow it to better judge data completeness and accuracy.

“Everywhere I have worked I have seen the difficulties caused by letting end users change or create classifications downstream,” he said. “Changing data fields and attributes at the individual business level causes a lot of complexity down the line.” By having a centralised structure to monitor data quality across the institution, Murphy anticipates that some of these problems can be picked up more easily.

Firms also need to draw up quality indicators on data to check whether their requirements are being met by vendor systems and internally built solutions, he suggested. To this end, Murphy is keen to draw up internal client service level agreements (SLAs) in order to ensure data quality is being maintained.

Murphy noted that vendors have been slow to properly service the needs of the buy side, however, many firms are also unsure about the requirements of their own internal end users. “The industry has to be brave but cautious about what we opt to do with vendors in a managed services environment, for example,” he said. “You don’t want to give away control over your data quality.”

So, vendors may have their faults, but they can be useful partners in bringing technology expertise to the table, according to Murphy. “Don’t bash your vendors too much,” he joked. “They are people too.”

Subscribe to our newsletter

Related content

WEBINAR

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

Date: 8 July 2026 Time: 10:00am ET / 3:00pm London / 4:00pm CET Duration: 50 minutes 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...

BLOG

Data as a Product: From Collection to Control in Modern Markets

For much of the past decade, data strategy in capital markets focused on accumulation. Firms invested heavily in market data feeds, alternative datasets, data lakes, and analytics platforms. Yet despite this abundance, many organisations have still struggled to answer basic operational questions with confidence, particularly during periods of market stress. The problem is no longer...

EVENT

Data Management Summit New York City

Now in its 15th year the Data Management Summit NYC brings together the North American data management community to explore how data strategy is evolving to drive business outcomes and speed to market in changing times.

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...