Eighteen months into his stewardship of GoldenSource, chief executive James Corrigan says the company is entering its next phase with a clear, practical three-year plan.
Corrigan describes a disciplined approach: decide where the firm will compete, be explicit about what sets it apart, and align the organisation behind a short list of priorities.
“If you don’t evolve your business model, if you don’t evolve your technology, you get left behind,” he tells Data Management Insight. “And I think GoldenSource has always had a very advanced innovation mindset that lets us stay ahead of each new wave of market change.”
Changing Business Models as Markets Change
GoldenSource has adapted to market changes throughout its history and the rapid evolution of markets witnessed now is ushering in yet more change.
The company began life as a master data specialist and, as data became more critical to financial institutions’ broader operations, it moved to enterprise data management supporting both buy-side and sell-side firms
Now, with market dynamics, geopolitics and economic systems in a state of flux, investors are reaching for new strategies. Diversification has become a clear option in the past few years, and in response modern data platforms and artificial intelligence are emerging as the best solutions for these times.Corrigan sees this as an opportunity to switch gears again.
This time the focus is on the emerging trend away from single, front-to-back data workflow solutions as modern data management platforms enable customisation through the seamless integration of best-of-breed “components” tailored to specific use cases.
“You’re more likely to see newer products from specialist providers… that are going to solve more narrow, complex use cases,” Corrigan says. “And they need to be integrated with other platforms. And all that data needs to be understood. All that data needs to be fed and cleansed and enhanced.
“Regardless of where the industry goes or what happens with AI, data is going to be at the centre of it, and that’s where you’re going to hear a lot about data platforms in this new era of AI, because without them, AI doesn’t work effectively. Our role is to provide that trusted, integrated platform so those specialist tools actually deliver governed, auditable and usable insights.”‘Componentising’ Data Provisions
An expression of GoldenSource’s embrace of the new is found in the OMNI cloud-native data warehouse deployed natively on Snowflake. This has helped implement total-portfolio views for diversifying asset managers and ushers a major step by GoldenSource into analytics provision, another part of the “componentising” of its services and products.
Corrigan’s game plan has already hit many of GoldenSource’s goals. Last year the company completed a wholesale transition of its platform to a cloud-native one, making it easier for clients to access its products and streamlining its own engineering, development and product delivery processes.
The early indications are that the shift has been welcomed by clients. Many of whom have made the move, and GoldenSource is seeing shorter implementation times and faster delivery of new features. Corrigan and his team have also made improvements to GoldenSource’s customer services procedures with the creation of customer success managers. This has helped the company gain a closer understanding of what’s wanted in the market, Corrigan said, and to behave more as a long-term strategic partner than a one-off software supplier.
AI Agents Marshalled to Boost Productivity
AI, of course, plays heavily in GoldenSource’s plans. Agents have been deployed to act as “productivity enhancers” and the company is also looking at using AI to aid customer support and service functions.
“We are rolling out AI-powered features in targeted areas first, where they solve real client problems and can be governed properly.”, Corrigan said.
Among them is a new initiative within GoldenSource’s AI programme that will simplify day-to-day workflows by letting users engage with the platform through natural language prompts.
The rollout of products for client use is intentionally focused on areas where AI solves practical client problems and can be governed properly. Corrigan says GoldenSource is determined to ensure that what it implements is fit for purpose.
“We actually see ourselves as being an enabler of AI for our clients. I liken it to the gold rush analogy – a lot of people made money looking for gold, but a lot of people made money selling picks and axes. We think we’re the picks and axes, because we provide the quality-controlled data, auditability and governance that every AI initiative depends on.”Smoothing the Transition Experience for Clients
In this way Corrigan sees the future of GoldenSource as providing the glue that joins the components to the new data management platform concept. That’s going to be especially important as markets fragment and new niche data tech players emerge to meet nascent use case demands.
“When you have this level of specialisation, products get created that meet that need really well, they get market share, and companies that do business with them have to figure out how to stitch those together. And that’s always a data transfer. Stuff gets created and then it must work together.
“Stitching and wrangling data is what we do well and that’s the value we add in that ecosystem.”
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