S&P Global invests in SSImple

Investment targets improvements in SSI data quality, governance and automation across post-trade workflows.

S&P Global has made a strategic investment in SSImple, a platform focused on the management and automation of standing settlement instructions (SSIs).  

The collaboration aims to address long-standing challenges around SSI management by combining SSImple’s capabilities with S&P Global’s market reach and data infrastructure. 

Speaking in a social media announcement about the investment, Bill Meenaghan, chief executive and founder of SSImple said: “This marks an important milestone in our collaboration and reflects a shared commitment to addressing one of the capital markets industry’s longstanding operational challenges: improving the quality, governance, and automation of Standing Settlement Instructions (SSIs).

“As the industry prepares for T+1 settlement and accelerates its adoption of automation, trusted SSI data has never been more important.”

Read more: Europe’s T+1 countdown: Insights from the US

The collaboration will bring together SSImple’s SSI management capabilities with S&P Global’s market reach and data capabilities, with the firms aiming to help financial institutions reduce operational risk and improve post-trade efficiency. 

Meenaghan added: “As the industry prepares for T+1 settlement and accelerates its adoption of automation, trusted SSI data has never been more important. By bringing together SSImple’s expertise in SSI management with S&P Global’s client reach and market capabilities, we aim to help firms reduce operational risk, improve efficiency, and strengthen post-trade resilience.” 

The investment comes as market participants continue to prioritise improvements in post-trade infrastructure, with accurate SSI data becoming increasingly important as firms adapt to shorter settlement cycles and greater automation. 

The investment follows an earlier collaboration between the two firms. In May 2025, S&P Global Market Intelligence and SSImple partnered to improve the automation and validation of SSIs. 

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