Model ML secures HSBC investment for AI expansion

By Milan Rojan

Financial services AI platform Model ML has secured an investment from HSBC Asset Management through its flagship Venture Capital strategy to support the company’s expansion of its agentic operating system.

London-based Model ML has developed an AI platform designed specifically for financial services, supporting banks, asset managers and advisory firms with workflows including research, due diligence, financial analysis and client document creation.

Chaz Englander, CEO and Co-founder of Model ML, said: “We’re delighted to welcome HSBC Asset Management as an investor. Their backing reflects growing confidence in vertical AI for financial services.”

The company has said its platform has been designed to maintain governance, accuracy and consistency while automating complex financial tasks. Its model-agnostic architecture has enabled firms to route individual tasks to different AI models based on their requirements.

Model ML has grown rapidly since launching less than two years ago and has raised more than $100m to date. The latest investment has come as financial institutions have increasingly moved beyond individual AI models towards systems capable of integrating multiple models into enterprise workflows.

Patrick Sixsmith, Head of Venture Capital at HSBC Asset Management, said: “AI and next-generation software are driving a new wave of innovation across the economy.”

He has added that the investment has reflected the firm’s focus on companies operating at the forefront of AI and software development.

HSBC Asset Management’s Venture Capital strategy has operated as a curated venture capital fund-of-funds programme within its $81 billion Alternatives platform. The strategy has also made selective co-investments in venture-backed companies.

The investment has strengthened Model ML’s position in the growing vertical AI market, where financial institutions have increasingly evaluated specialised platforms designed to combine automation, governance and multiple AI models across regulated workflows.