ERM has partnered with Auquan to deploy artificial intelligence agents across sustainability workflows for financial institutions, as demand grows for faster and more scalable ESG risk analysis.
Under the collaboration, ERM will use Auquan’s Sustainability Agent to enhance the speed, scale and depth of sustainability insights delivered to clients navigating increasingly complex regulatory and investment requirements. The move comes as regulations such as SFDR Article 8 place greater scrutiny on corporate sustainability claims and intensify demand for comprehensive reputational risk assessments.
By combining ERM’s sustainability expertise and long-standing relationships across institutional finance with Auquan’s agentic AI technology, the firms aim to support faster identification and assessment of reputational risks during due diligence. Auquan’s platform scans global news, regulatory disclosures and stakeholder reports to flag controversies, litigation and adverse media linked to target companies and counterparties.
Andrew Radcliff, global service leader for mergers and acquisitions at ERM, said the collaboration reflects the consultancy’s efforts to scale its advisory capabilities as regulatory complexity increases. He said embedding AI solutions would enable ERM to deliver more timely, data-driven insights to help clients mitigate risk and strengthen investment decision-making.
Auquan chief executive Chandini Jain said ESG risk assessment remains one of the most data-intensive and time-consuming processes in finance. She added that the partnership would allow firms to meet sustainability and investment mandates more efficiently, freeing up time for higher-value strategic work.
ERM has advised private markets investors across buyouts, growth equity and infrastructure transactions for decades and has supported thousands of deals globally. The firm said the integration of AI into its sustainability workflows builds on this experience, combining technical depth with enhanced analytical capabilities to meet evolving client needs.
