Partner Research

Unlocking the Untapped Potential of Data and AI in Asset Management


A Whitepaper by HSO


The data is already there


Asset and investment management firms are awash in data, which is constantly being generated from a combination of internal sources, free sources, and paid sources.

However, much of this data remains underutilized within the organization. It is fragmented across the firm, with each department maintaining its own data repository and using different databases and data structures. For many firms, the task of combining and integrating these disparate data and formats into a single source of truth is too daunting.

By not taking full advantage of the data they already have at their disposal, asset management firms are missing the stories within the data. As a result, the firm fails to develop a coherent strategy to extract the critical information held within the data and leverage that information for greater customer engagement, more strategic decision-making, and better data governance and compliance.

In this paper, we discuss how an investment in artificial intelligence (AI) can transform the data you already have into information that will help you meet your organization’s goals, such as increasing sales, increasing or retaining your assets under management, fewer liquidations, and lowering costs.

Harnessing data’s potential

A consequence of siloed data is that major disconnects can occur that limit the firm as a whole. The sales and marketing teams are an asset management firm’s largest consumers of internal and third-party information sources. Their data analysis primarily focuses on customer segmenting by size, use of products, and product behavior.

So, while one department is gleaning insights from market data, Sales is leveraging internal CRM data. Both departments are busy analyzing data but are missing the targeted insights from consolidating all their information sources into a synchronized data repository.

While this potential is not realized for many reasons, the bottom line is that the more targeted information you can get from your data, the better your chance of achieving your firm’s goals. Information should be used proactively to shape the firm’s sales strategy. According to BlackRock, the best use of data by the organization is to achieve complete customer satisfaction by meeting the customer’s needs.

Understanding how things change, which elements are moving, and which elements are staying the same can help determine whether to expect the same or different outcomes compared with similar trends in the past.

Modern data analysis and forecasting tools that leverage artificial intelligence (AI) capabilities can be applied to predictive and prescriptive analytics to improve customer service, deliver personalized customer experiences, create targeted marketing campaigns, identify customer buying trends, and gain insights into fund strengths and weaknesses.


Predictive: What’s going to happen if I do nothing?

Prescriptive: What do I need to do to change the outcome?


Trend analysis

For this type of analysis, a firm needs a synchronized data platform capable of performing business intelligence and AI-driven analysis with integration across all its systems. Such a data platform will help Sales and Marketing and other areas in the organization, including risk management, portfolio management, performance management, regulatory compliance, market and trend research, and customer satisfaction.

An AI-driven data platform should represent a genuine investment in technology to achieve your specific business objectives. It is not haphazardly throwing AI at a problem but deliberately putting AI solutions to work to solve specific business problems.

For example, firms can lower costs by increasing productivity—using AI to automate routine tasks and freeing employees to utilize their expertise for more profitable pursuits.


What’s holding firms back ?

Data is consistently highlighted as a critical concern for asset and investment management firms. In a recent survey of CFOs, 40% reported a “low” or “medium” level of sophistication across a range of data priorities. And while 85% reported a significant acceleration in digital transformation in 2022, many firms continue to be reluctant to invest in a comprehensive data strategy.

According to a 2023 article in Deloitte’s Performance Magazine, “Investment Management (IM) firms should reconsider their current data strategy…As part of a strong data strategy and governance, IM firms can leverage this meaningful data as an asset for insights that drive sustainability and increase revenue.”



And yet, there is reluctance for asset management firms to invest in a comprehensive data strategy. The reasons vary, but they fall mainly into five groups:


They have the mistaken impression that such a solution would be an expensive undertaking


They are unclear about the benefits a well-planned data strategy will deliver


They realize the value but don’t know where and how to start


They realize the value and know how they want to proceed but cannot get executive support to invest in the solution (“We’ve invested enough in our data!”)


Assigning priority and resources to traditional and incumbent efforts that are well understood but might no longer deliver the kind of results and future you are looking for

Consequences of reluctance


This indecision is felt across the organization. Without visibility of the information available, each department is either wrestling with incomplete data and duplicating the efforts of other departments to obtain the same data, but never seeing the holistic benefits a true data platform strategy can deliver.


The consequences can be substantial:

  • Incomplete and inaccurate data results in a loss of trust in the data
  • There is no clear strategy for what the data can do
  • There is no clarity on who owns the data
  • Lost opportunities (You don’t know what you don’t know)
  • Growing customer dissatisfaction and the inability to anticipate churn of existing accounts
  • Loss of assets under management
  • Higher costs with less revenue
  • In the end, firms that fail to invest in a coherent, comprehensive data strategy, for whatever reason, are on track to lose more sales to their competitors.



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