ValidMind, an AI and model risk management platform for financial services, has announced it has raised $8.1m in a seed funding. The funding round was led by Point72 Ventures, with participation from Third Prime, New York Life Ventures, AI Fund, Notion Capital, FJ Labs, Angel Invest, and Gaingels.

This funding will advance ValidMind’s go-to-market plans and establish it as a partner to its customers in financial services. With this round, ValidMind’s total funds raised are $11.1m.

Funding arrives as more financial institutions embrace AI-powered solutions 

43% of executives believe AI will be critical to financial businesses by 2025. However, as AI/ML, particularly large language models (LLM), adoption increases in financial services, adequately managing its unique risks has become crucial for model risk management (MRM) teams, especially amid consumer concerns surrounding AI’s trustworthiness and safety. For instance, the Consumer Financial Protection Bureau reports banks that use chatbots run the risk of providing inaccurate information to customers (which isn’t compliant with federal consumer financial protection laws) and diminishing consumer trust.

In addition to increased pressure from regulators to comply with existing banking regulations, MRM teams are facing new regulatory challenges, such as EU’s AI Act and the recently announced AI Bill of Rights by the US administration, factors demonstrate that today’s financial institutions need an end-to-end solution that can promote trust and compliance at every step of the MRM lifecycle, which ValidMind provides.

Jonas Jacobi, CEO and Co-founder of ValidMind, said: “The MRM teams at financial institutions are struggling to keep up amid increased pressure from the business to deploy more AI solutions faster and from regulators to ensure compliance, relying on an already time-consuming process due to a lack of fit-for-purpose built tools and increased model complexity. This funding strengthens our commitment to help customers increase the speed and efficiency of their MRM processes, reduce time-to-market for new AI solutions, and ensure compliance with global AI and model risk regulations.”

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