Private credit is no longer niche. With global assets under management surpassing $1.7 trillion, and expected to double by the end of the decade, it has become the fastest-growing corner of the alternatives market. In the U.S., momentum is fueled by anticipated Federal Reserve rate cuts and a landmark Executive Order opening 401(k) retirement plans to alternative assets. That move could unlock $9 trillion defined-contribution market, dramatically expanding the investor base for private credit.
ESG Data in Credit
Retail capital could dramatically accelerate private credit’s growth, but with scale comes scrutiny. Experts warn that alternative assets carry higher fees, lower liquidity, and increased fiduciary responsibilities. Plan sponsors will need rigorous due diligence and transparent reporting to meet Employee Retirement Income Security Act (ERISA) obligations and manage litigation risk. For private credit managers, this makes credible ESG data infrastructure a necessity, not an option.
Additionally, limited partners (LPs) are no longer satisfied with check-the-box ESG data collection. They want evidence of integration into investment decisions, risk management, and value creation. In today’s fast-expanding credit market, supercharged by federal policy and structural regulatory shifts, robust ESG systems are a fundraising differentiator. For credit managers, this means building ESG data strategies that are flexible, transparent, and aligned with how deals are done.
Best Practices to Obtain ESG Data
ESG tools built for equity do not always work in credit. ESG questionnaires, while effective to assess portfolio company activity in private equity, often yield incomplete results when used in credit strategies. Today’s popular peer-benchmarked models can be misleading in structured credit, where the distance from the underlying assets makes direct engagement nearly impossible. In Collateralized Loan Obligations or securitizations, a single deal can represent hundreds of opaque borrowers, creating multiple layers of complexity.
Yet, proactive engagement in direct lending with borrowers, deal teams, and sponsors has resulted in improved ESG data quality. Managers who embed ESG early in the deal process and foster strong relationships often produce the most complete datasets.
Engagement in credit is not one-size-fits-all. It can involve sponsors, syndicate leads, or intermediaries depending on who holds the influence. Relying solely on passive data scraping or third-party scores risks missing the nuances investors care about.
ESG success in credit is not just about tools; it is about execution, transparency, and follow-through. The future belongs to firms that treat ESG as core data infrastructure, not a reporting afterthought. For credit managers, that means investing in solutions capable of orchestrating disparate inputs (across vendors, models, and borrower touchpoints) into a single, governed workflow.
For LPs, this translates into credible, decision-useful ESG data they can rely on when allocating capital. For managers, it means embedding ESG insights directly into risk management, pricing, and portfolio oversight, turning ESG from a fragmented liability into a scalable fundraising differentiator and strategic edge.
Specialized ESG partners, like ACA, can play a critical role in helping firms operationalize ESG strategies, supporting data collection, validation, and integration across complex portfolios.
The Role of ESG Orchestration Platforms
ESG data workflows must be tailored to suit the nuances of different investment strategies. In structured credit where engagement is limited, firms need blended models, including scraping, estimation, and peer modeling. Transparency into these data types is key; investors need to know what is directly sourced, estimated, and modeled. Without this clarity, ESG data can become a liability rather than an asset.
This challenge is compounded by the growing clutter of ESG data management platform vendors, each optimized to a single function, leaving credit investors to stitch together fragmented point solutions. Managers need an orchestration layer that harmonizes data models, integrates multiple sources, and delivers a coherent, decision-ready output.
Purpose-Built ESG Data for Credit
ACA Ethos is designed to play this orchestration role, enabling managers to integrate and govern ESG data across systems, asset classes, and strategies. It blends AI-driven scraping, estimation models, and survey tech into a single hub, reducing vendor clutter and elevating ESG workflows from disconnected inputs into a usable ecosystem. With custom dashboards and analyst overlays, ACA Ethos transforms ESG data into something decision-ready, not just reportable.
Reach out to your ACA consultant, or contact us here to learn how ACA Ethos can transform your ESG data.