AI-driven transformation: Discover the possibilities
Data-Driven Success: Leveraging AI to Transform Asset Management
As a cloud sales consultant at HSO, I’ve had the privilege of working with asset management firms grappling with a challenge that’s become more pressing than ever: how to harness the overwhelming amount of data they handle daily. From client interactions and portfolio data to external market insights, these organizations are sitting on a gold mine of information—but much of it is fragmented, siloed, and underutilized.
Enter artificial intelligence (AI). While AI has been around for decades, recent advances in cloud computing and data processing have brought its full potential within reach of asset managers. AI is no longer a distant concept but a practical solution that can help firms gain critical insights, automate routine tasks, and ultimately drive better business outcomes.
As Tom Berger, HSO’s global financial services leader, said during a recent discussion on AI in asset management: "We are limited in our ability to recognize patterns... but the impact of pattern recognition and testing models is where the machine can help us." AI enables asset managers to process vast amounts of data more effectively and recognize trends that would be impossible to spot through manual analysis.
We are limited in our ability to recognize patterns... but the impact of pattern recognition and testing models is where the machine can help us.
Current Data Landscape in Asset Management
Asset management firms handle data from various sources, both internal and external, ranging from Excel spreadsheets to paid datasets like Broadridge and SS&C. However, as I’ve seen firsthand, this data often remains siloed across the organization, preventing managers from gaining a unified view. As Tom Berger put it, "We're talking about data in the form of anything—Excel spreadsheets sitting on somebody's desktop, free data, paid data...
"All these data sources are fragmented, underutilized, and siloed." This fragmentation makes it difficult for firms to extract meaningful insights, let alone leverage AI to make sense of it all.
I’ve found that many organizations are aware of this challenge but struggle with where to begin. The first step is consolidating and organizing this data, laying the foundation for AI to work its magic.
Data Cleanliness: The Foundation of AI
One of the biggest misconceptions about AI is that you can simply plug it in and expect immediate results. In reality, AI can only be as effective as the data it’s working with. That’s why data cleanliness—organizing, cleansing, and integrating data—is critical.
Tom emphasized this point during our conversation, "This is not a one-and-done or set-it-and-forget-it exercise. You need to think about AI in an organization at large because silos do not enable AI conclusions. Everything works together to generate AI." It’s crucial to take a prescriptive approach, ensuring that all data sources are clean and ready to be used by AI models.
At HSO, we’ve developed methods to help firms bring together their disparate data sources, whether from internal systems or external datasets, and prepare them for AI analysis. As I often tell clients, there’s not a reactive success model. We need to be very prescriptive, very intentional with how we manage our data. This disciplined approach ensures that AI can deliver reliable, actionable insights.
WATCH On-Demand: Unlocking the Untapped Potential of Data with AI
Breakthroughs with AI: Real-World Use Cases
AI’s ability to recognize patterns and deliver insights is where it truly shines. In asset management, AI is being used to solve real-world challenges, from portfolio management and risk assessment to client engagement.
I recently worked with a client to develop a churn prediction model using Microsoft Fabric. By analyzing factors like the recency and frequency of client interactions, transaction values, and demographic data, we are building a model that predicts when investors are likely to buy or sell. This kind of AI-driven insight allows asset managers to take proactive steps to retain clients and drive revenue growth.
Tom shared a similar example: "I was having drinks last night with the technology executive for one of the largest hedge funds in New York City, and he said, ‘Look, we’ve been working with [AI]... but what has changed is the computational capabilities and the capacity for taking on data in the cloud.’" The cloud, particularly platforms like Azure and Microsoft Fabric, has made AI far more accessible, allowing firms to process and analyze massive datasets efficiently.
Even small tasks, like automating post-trade thank-you emails, can be transformed with AI. Something as simple as post-trade thank-you emails... just automating processes like that can really make a difference. AI can handle routine tasks, freeing up time for asset managers to focus on higher-value activities like strategy and client relationships.
Real-world Example Use Cases
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Enhance decision-making processes
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Optimize processes
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Improve customer experiences
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Unlock new opportunities
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Gain a competitive edge
Overcoming Challenges: The Reluctance to Invest in AI
Despite its promise, some firms are hesitant to invest in AI, often due to concerns about cost, complexity, or the perception that AI is too advanced for their needs. During our conversation, Hazem Gamal from the SME Forum made a great point: "These are early examples of where you can get good traction for your businesses... but this is a marathon, and not a sprint." AI adoption requires patience and a long-term perspective.
The good news is that modern tools like Microsoft Fabric make AI more accessible than ever, even for smaller firms. Fabric has the ability to pull data in without requiring massive infrastructure to support it. It’s a solution that even smaller firms can leverage without the need for a large IT team. The barrier to entry for AI is lower than many realize, especially when firms have the right partner to guide them.
Microsoft Fabric for Asset Managers: A Game Changer for Data Management
Unlocking the Full Potential of Your Data with AI
The goal for any asset management firm is to unlock the full potential of its data, and AI is the key to doing that. But it’s not just about deploying AI for the sake of it. It’s about making sure that AI drives better decision-making, empowers teams, and ultimately impacts the bottom line.
As Tom succinctly put it, "Even if you create next best action with 60 to 80% confidence, that's pretty good efficacy." AI doesn’t need to be perfect to be impactful. Small, incremental improvements can lead to significant competitive advantages over time.
At HSO, we’re proud to partner with asset managers to help them harness the power of AI. By consolidating their data, ensuring it’s clean, and deploying AI strategically, we enable firms to gain the insights they need to thrive in today’s competitive market.
If your firm is ready to unlock the untapped potential of data with AI, now is the time to take the first step.
Learn more about how we support Asset Management firms