Streamlining processes through automation: Asset managers aim to reduce redundancies
In the asset management industry, regulatory document production and compliance are seen as major efficiency drains, with 37% of industry leaders identifying them as areas where the most internal resources are wasted [1][2][5]. According to Liam Healy, CEO at FE fundinfo, this is due to reliance on legacy systems, inconsistent data flows, and duplicated systems [1].
The report by FE fundinfo's 2025 Asset Management Report further highlights that reliance on legacy systems is the biggest barrier to improving fund data and reporting, with 46% of respondents citing it as a major challenge [1][2]. Duplicated entry points and fragmented systems continue to slow accurate reporting and decision-making in the asset management industry [1].
Forty-three percent of asset managers struggle with the volume and frequency of data updates [1]. High upfront costs and long payback periods for digital transformation investments also pose a challenge, necessitating careful prioritization and resource allocation [5]. Resistance to change and skill gaps within organizations further slow adoption of advanced digital tools [3].
However, the benefits of modernization are clear. Automation streamlines repetitive tasks, reduces manual errors, and enables faster regulatory compliance, significantly boosting operational efficiency [1][4]. Digitized, integrated platforms facilitate real-time, consistent data access, enabling better decision-making, predictive analytics, and confident risk management [1][3][4].
Improved client experience is another key benefit, with digitization supporting personalized services, real-time reporting, and AI-powered client support, enhancing engagement and satisfaction [3][4]. Cost savings and optimized resource allocation are also significant advantages, as automation reduces duplicated effort and frees resources from regulatory and market-driven changes management [1][4].
Technologies such as AI, blockchain, and tokenization offer transformative potential for transparency, liquidity, and new investment models [3]. Sixty-four percent of UK asset managers report challenges with data fragmentation in product distribution [1]. The siloed processes and inconsistent data flows are creating structural stress points across firms' operations [1].
In summary, overcoming fragmented legacy systems, integrating siloed data, building digital skills, and managing transformation costs are the central challenges. The clear payoffs lie in operational efficiency, data harnessing, client focus, and innovation-driven growth [1][2][3][4][5]. Sixty-one percent of asset management leaders still devote considerable resources to dealing with regulatory or market-driven changes [1].
Liam Healy emphasizes that a data-driven approach is the foundation for confident decision-making, stronger compliance, and long-term growth [1]. He suggests that successful modernization requires breaking down these barriers and building agile, scalable systems [1]. Automation, data, and digital tools present an enormous potential for change in the asset management community [1]. Sixty-four percent of asset management leaders are investing in automation or digitization, according to the FE fundinfo's 2025 Asset Management Report [1].
References: [1] FE fundinfo's 2025 Asset Management Report [2] Financial News, "Asset managers face tech challenge in data consolidation", 2021 [3] Finextra, "Asset management leaders invest in automation and digitization", 2021 [4] The Economist, "The rise of the data-driven asset manager", 2020 [5] McKinsey & Company, "Digital transformation in asset management", 2020
- In the pursuit of operational efficiency and regulatory compliance, asset management firms are investing in digital transformation, recognizing that automation can reduce manual errors and streamline repetitive tasks, thereby promoting compliance within their businesses.
- To address the barriers posed by reliance on legacy systems and inconsistent data flows, asset managers are focusing on finance technologies such as AI and blockchain in their asset management strategies, as these tools offer the potential for improved data management, decision-making, and client experiences.
