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 Summit Innovation Showcase Presents The Investment Data Utility

Subscribe to our newsletter

Join us tomorrow at our London Data Management Summit to find out how to make data an opportunity rather than a risk, what still needs to be done to ensure Markets in Financial Instruments Directive II (MiFID II) compliance, how to make the most of alternative data and next generation analytics, the latest technologies adding a new dimension to data management – and more!

Looking at emerging technologies and their vendors, the Summit will include a data innovation showcase. We caught up with Robin Strong, founder and CEO of The Investment Data Utility, ahead of the event to find out how his company can help resolve some of today’s data management challenges.

Q: What data management problems do financial institutions have that you believe you can solve?

A: Unknown, probably poor, data quality across the business, the inability to measure data quality versus peer groups, and incorrect data that is not spotted until it’s too late – failed trades, skewed risk reports, compliance breaches and so on.

Q: Why do financial institutions have these problems?

Typically, because data comes from disparate sources and is processed by different systems in different ways. Even a well-produced ‘gold copy’ lacks any meaningful comparison point to assess its quality.

Q: How do you solve these problems?

A: I have developed crowdsourcing, collaborative technology that allows data to be compared across institutions, generating an industry benchmark that identifies incorrect data before it is used by the business.

Q: What technology do you use?

A set of proprietary algorithms implemented using low-cost standard software tools linking to a central processing cloud.

Q: How does your solution fit into a financial institutions architecture and data flows?

The beauty of this model is that it does not impinge on existing toolsets, workflows and governance processes. It can be added as an additional layer in the architecture at low cost, resulting in very high ROI.

Q: Which emerging technologies do you see as having the most potential to improve data management and why?

I am a big believer in industry standards, yet so many firms reinvent the wheel with proprietary tools to store, reconcile and govern data. Industry collaboration is key and unless operational costs are reduced, new entrants will establish lower overhead models to undercut the competition.

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

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

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...