Minutes of the Securities Lending Committee meeting – September 2026

The Securities Lending Committee opened its September 2026 meeting by addressing strategies to attract and retain early-career professionals in securities finance, including leadership programmes and cross-firm knowledge-sharing initiatives. The Tax & Regulations sub-committee reported heightened operational difficulties due to varying tax regimes and record date requirements, warning that T+1 settlement could exacerbate these issues if firms do not adapt their processes. Members noted that while many firms aim for T+1 readiness by October 2027, disparities in preparedness remain, with persistent challenges in recalls, collateral sourcing, and settlement timing. The Committee also explored growth opportunities in emerging markets and digital asset initiatives, including tokenisation programmes, while stressing the need for scalable operating models to support future market changes.

The group examined the expanding role of central counterparties, collateral efficiency mechanisms, and smart collateral structures, alongside regulatory developments that may impact lenders, borrowers, and investment funds in the coming years. Members highlighted the growing importance of digital collateral and infrastructure projects, though practical use cases remain a critical obstacle to broader adoption. Industry working groups are actively addressing repo, collateral mobility, payments, legal frameworks, and digital securities issuance to address these gaps.

A legal case involving the potential re-characterisation of a securities financing transaction as a secured loan was discussed, with members noting its potential implications for repos, securities lending, and contractual certainty across the industry. The Committee also assessed the pace of artificial intelligence adoption, describing current use as efficiency-driven, focusing on administrative tasks, data aggregation, and enhanced transparency in funding and collateral management.

Members observed that AI integration is evolving from individual productivity tools into strategic infrastructure, with potential impacts on trading activity, client selection, and collateral mobility. However, concerns were raised about governance, resilience, vendor oversight, and data security risks, particularly if AI systems accessed sensitive operational data, underscoring the need for robust oversight frameworks.