Introduction
In today’s investment landscape, non-financial data, including environmental, social, and governance (ESG) information is no longer just a nice-to-have. It has become a critical part of how multi-asset funds manage risk, allocate capital, and create long-term value. As institutional investors increasingly prioritise sustainability and regulatory compliance, the performance and transparency of non-financial indicators are shaping everything from portfolio construction to investor trust.
Yet, even with this momentum, asset managers face significant hurdles. The non-financial data landscape is still riddled with issues: fragmentation, inconsistency, and a lack of verification standards; that echo the inefficiencies seen in financial data systems two decades ago. Without a clear strategy to address these, integration of non-financial factors risks becoming superficial or even misleading.
The data problem: historical and current challenges
Looking back 20 years : Two decades ago, financial institutions struggled with data fragmentation, lack of standardization, and low-quality inputs. Risk and investment data sat in silos, reporting frameworks were varied and hard to compare, and manual processes left room for error. Outdated tech didn’t help either legacy systems couldn’t support fast, scalable analysis or real-time decisions.
What’s changed and what hasn’t: Fast-forward to today’s non-financial data environment, and we’re seeing a familiar pattern. Despite better technology, new challenges have emerged:
- Standardization is still elusive: Global frameworks like GRI, SASB, ISSB or SFDR have made progress, but lack of uniformity makes it difficult to compare non-financial performance across sectors and regions.
- Data quality remains a concern: Inputs such as climate models, social impact scores, and supply chain data aren’t always structured within conventional financial systems. According to the CFA Institute, 63% of investment professionals cite data quality as their top concern.
- Conflicting methodologies: Multiple rating providers and proprietary scoring models mean the same organisation can be evaluated differently. A 2022 MIT study found a correlation of just 0.54 between non-financial ratings from major providers.
- Growing regulatory demands: With SFDR, TCFD, the SEC’s climate disclosures and more, funds are under pressure to constantly adapt their non-financial data processes. This raises both operational costs and compliance risks.
Why multi-asset funds need to pay attention
Multi-asset funds span asset classes and regions, so the integration of non-financial data is even more complex. These funds need to collect, validate, and apply a wide range of information: some qualitative, some quantitative into their investment decision-making.
Take infrastructure and corporate bonds as an example. In infrastructure, physical climate risks are key. In fixed income, governance or social controversies can directly impact creditworthiness. To manage this, funds need a system that can process and connect granular non-financial data across very different domains.
Case study: integrating non-financial data in a global asset management firm
A global asset management firm with over €75 billion in assets under management launched an internal initiative to improve its non-financial data strategy across multi-asset portfolios. The firm operates a variety of funds, including equities, fixed income, and real assets—and faced mounting pressure from clients and regulators to improve its reporting transparency and sustainability performance.
To address this, the firm implemented a centralised data infrastructure that could aggregate and harmonise data from investee companies, ESG data providers, and proprietary sustainability assessments. It also adopted scenario analysis tools aligned with TCFD and invested in automated workflows to support SFDR and EU Taxonomy compliance.
Key outcomes over 18 months:
- Increased non-financial data coverage across its portfolio from 52% to 91%
- Reduced data reconciliation time for quarterly reports by 60%
- Integrated climate and governance indicators into its credit and equity risk models
The success was driven by cross-functional collaboration between sustainability, data science, and risk teams, as well as a focus on building internal capabilities rather than relying solely on external ratings.
What works: practical strategies
- Clarify governance roles Treat non-financial data as you would financial data assign ownership, embed controls, and ensure oversight from investment, risk, and compliance teams.
- Align with leading frameworks Stick to well-recognised standards so your reporting is transparent, comparable, and audit ready.
- Make it actionable Feed non-financial data into your financial models. For example, price climate risk into discounted cash flows or integrate social KPIs into stress tests. This helps connect non-financial performance with expected returns.
Conclusion: data maturity equals strategic advantage
Non-financial data is no longer about box-ticking. It’s about understanding the true financial and strategic implications of sustainability, ethics, and operational resilience. For multi-asset funds, this requires moving beyond fragmented, ad hoc data efforts to a comprehensive, technology-driven strategy.
Firms that treat non-financial data as a strategic asset not just a reporting requirement will not only meet regulatory expectations, but outperform in a market where sustainability and accountability are becoming central to capital allocation.
Ultimately, the funds that win in this new environment will be those that turn non-financial complexity into investment clarity and measurable results.
