Despite recent changes in the U.S. and shifting regulatory climate, environmental, social, and governance (ESG) factors remain essential considerations for investment firms worldwide. Projections indicate that ESG-focused investments could reach $50 trillion by 2025, representing over a third of the anticipated $140.5 trillion in total global assets under management.
The challenge is no longer whether ESG matters, but whether firms have the infrastructure to handle it. For many asset managers, legacy systems are a poor match for today's ESG data demands. Modernizing these systems isn't just about compliance, it's about staying relevant in a fast-changing, data-driven market.
The Continuing Importance of ESG
Today's investors, especially the next generation, push for greater accountability, transparency, and sustainability. But asset managers are changing their approach. Rather than rely on abstract ESG scores, they're focusing on ESG data that connects directly to earnings, risk, and long-term business value.
According to a 2024 analysis by the Principles for Responsible Investment (PRI), companies with high ESG ratings tend to outperform their peers due to stronger fundamentals, not inflated valuations. ESG is becoming less of a label and more of an input, another layer of insight that sharpens investment decisions.
This shift demands richer datasets, deeper integration, and infrastructure that supports both transparency and actionability.
What’s Holding Asset Managers Back
Most firms still rely on outdated, fragmented data systems. These systems were not designed to ingest, normalize, and analyze the scale and complexity of ESG data flowing in today. Key obstacles include:
- Siloed Architecture: ESG data often sits separately from financial data, making cross-analysis complex and error-prone.
- Inconsistent Formats: Many ESG disclosures are semi-structured or manually formatted, complicating ingestion and slowing insights.
- Limited Scalability: Legacy platforms buckle under pressure as ESG data grows in volume and velocity.
- High Barriers to Modernization: Transitioning to modern infrastructure requires capital, retraining, change management, and vendor coordination.
As DataArt emphasizes, asset managers who don't modernize their systems risk losing relevance in an increasingly data-driven landscape. ESG data feeds are also relatively new and often designed for human consumption: reports in PDFs, PowerPoints, or third-party dashboards. Extracting structured, machine-readable insights remains a persistent challenge.
Where to Begin: Practical Steps Toward Modernization
Asset managers looking to close the ESG infrastructure gap can begin with three key strategies:
- Embrace Advanced Data Integration Tools: Think of powerful tools that can seamlessly blend ESG data with your existing financial information. This integration facilitates comprehensive analyses and informed investment decisions. Microsoft emphasizes the development of such tools to inform comprehensive analyses and outcomes.
- Apply Artificial Intelligence (AI) and Machine Learning (ML): Use AI and ML to process complex ESG data at scale and especially process unstructured datasets into structured machine-readable form. The CFA Institute notes that top-performing asset managers already deploy AI to surface trends, track performance, and identify high-potential investments.
- Establish Strong Data Governance: Establishing clear protocols for data quality, consistency, and security ensures the reliability of ESG information. Deloitte points out that solid ESG governance enhances long-term portfolio resilience and aligns with increasing compliance expectations.
Don’t Ignore the Risks: ESG Isn’t Perfect
Greenwashing and misleading sustainability claims remain a top concern. There is also a lack of a single global ESG reporting standard. These issues breed skepticism and, in some markets, political backlash. However, ignoring ESG entirely is not a viable strategy. Instead, firms are investing in better tools, standards, and data to counteract ambiguity.
Frameworks like the Global Reporting Initiative (GRI) and the Sustainability Accounting Standards Board (SASB) are paving the way for more consistent disclosures. Meanwhile, regulatory bodies in the EU and Asia are increasing pressure on asset managers and their portfolio companies to standardize and verify their sustainability claims.
Case Study: Storebrand's Data-Driven ESG Integration
Storebrand, a leading Nordic asset manager that has made impressive strides in incorporating ESG factors into its operations. With assets exceeding $118 billion, their commitment to sustainability shines through their advanced IT infrastructure, which promotes seamless ESG data integration and analytics.
Cloud-Based Integration and Analytics
Storebrand consolidates ESG data from multiple providers, processes it in real-time, and uses machine learning to enhance investment analysis.
Data Governance Excellence
Their governance framework ensures ESG data integrity through quality controls, audit trails, and secure access protocols.
Seamless ESG Workflows
Application Programming Interfaces (APIs) and collaborative platforms facilitate automated ESG data ingestion, empowering analysts with the most current insights on demand.
Real-Time ESG Risk Monitoring
Instant ESG performance metrics help Storebrand stay agile, aligning investment decisions with sustainability goals in real time. In summary, Storebrand's integration of ESG factors is deeply rooted in a technologically advanced IT infrastructure. By harnessing cutting-edge data management and analytics tools, the firm effectively aligns its investment strategies with sustainability goals, demonstrating that robust IT systems are pivotal in achieving comprehensive ESG integration.
Benefits Beyond Compliance
By investing in ESG-capable infrastructure, firms unlock:
- Early risk detection – from environmental liabilities to reputational exposure
- Streamlined reporting – with data ready for regulators, clients, and internal dashboards
- Product innovation – enabling the creation of ESG-aligned investment offerings
- Stronger relationships with clients who demand transparency and purpose
Modern ESG infrastructure isn't just a way to meet regulatory demands – it's a growth lever.
From Obligation to Opportunity
The firms that treat ESG data as a strategic asset rather than a reporting burden will define the next generation of asset management. That starts with infrastructure built for scale, complexity, and agility.
At DataArt, we help firms re-architect their systems to meet the demands of modern ESG. From AI-driven data pipelines to secure, cloud-native platforms, our solutions turn ESG complexity into competitive clarity.
Let's build the future of investment – together.
Ready to modernize your ESG infrastructure? Talk to a DataArt expert.
