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Spade Raises $40M Series B to Tackle Transaction Data Challenges in Banking

2026-03-26 - 08:50

Spade, a US-based data and AI platform focused on transaction data for financial institutions, has raised US$40 million in Series B funding. The round was led by Oak HC/FT, with participation from Andreessen Horowitz, Flourish, Gradient, NAventures, National Bank of Canada’s corporate venture arm, and Y Combinator. The company said it will use the funds to expand its platform capabilities, grow its team, and meet demand from banks and fintechs using transaction data for AI applications. Founded in 2021, Spade aims to address longstanding challenges in transaction data quality. Financial institutions process large volumes of transactions across card networks, ACH, and wire transfers, but the underlying data is often difficult to interpret. Unstructured transaction strings can lead to disputes, limited customer insights, and inefficiencies in areas such as rewards attribution. Spade’s platform matches raw transaction data with verified businesses in its database to provide clearer information on merchant identity and activity. The company reports coverage of 99.9% of merchants in the US and Canada, with accuracy above 99%. Its API infrastructure operates with P99 latency below 40 milliseconds, supporting real-time use cases such as authorisation decisioning and analytics. Oban MacTavish “This funding allows us to become the default data and intelligence layer for financial services,” said Oban MacTavish, Co-founder and Chief Executive of Spade. “As AI adoption accelerates, banks can only move toward automated workflows if systems are built on structured and verified transaction data.” Spade’s platform uses a proprietary matching engine and AI tools to update and refine transaction data, including merchant categories and location details. The company said this approach improves over time as more transactions are processed. Featured image credit: Edited by Fintech News Switzerland, based on image by wirestock via Freepik

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