Spade, the data and AI platform for modern financial services, announced Spade Predictions, a product suite for banks and fintechs built on a transaction foundation model Spade trained on payments behavior and the verified merchant behind every transaction.

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Spade built its transaction foundation model to serve the whole industry. More than half a dozen of the world’s largest financial institutions and payment networks have trained foundation models on their own transaction data in the past eighteen months. Each required tens of millions of customers, a dedicated research team, and years of governed transaction history, and served only the institution that built it. With Predictions, Spade offers the same capability to institutions of every size, from the largest banks to regional institutions and fintechs.

Card networks still allow just 25 characters for a merchant name, a limit set decades before digital-first banking. Spade’s model has two core components. One learns what a business is, from Spade’s own verified record of it rather than from the payment message. The other learns what a person’s spending says about them, reading their history with the real business attached to every transaction. Combined, they can be leveraged to solve problems across an institution, from which product a customer is ready for, to which merchant they are likely to shop at next, all the way to detecting fraudulent behavior. Spade never receives personally identifiable information, and a model tuned for one institution runs on that institution’s own customer identifiers.

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