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While a monolithic architecture was a good starting point for this fintech company, Curve had reached the stage where it was holding them back from truly innovating with all the potential data they had available to better serve customers. The legacy architecture was also creating issues with scalability and server space.
Curve adopted a microservices-based approach with event-driven data transactions powered by Confluent’s data streaming platform.
The notion of carrying around a wallet full of credit cards seems old-fashioned now. Consumers expect to be able to pay for anything with a flick of a device. Curve takes the concept of easy payment even further, with a mission to simplify the way people spend, send, budget, and save money.
With the Curve card, consumers securely link all their credit and debit cards to one single card or payment app. While the transaction happens on the Curve card, it’s immediately passed on to whichever linked card the consumer chooses at the point of sale. Cardholders can even set up rules for certain payment types: one for groceries and another for dining, for example.
With this, a whole suite of fintech capability lands in the hands of consumers. A single mobile dashboard grants a comprehensive view of a user’s spending, and they gain full control over managing their accounts—including the ability to go back in time and change payment types.
But efficiency and simplicity for consumers on the front end almost always translates to an extremely complex back end, and Curve is no exception. As a startup, Curve was built on a monolithic architecture, but in order to expand, scale, and compete in a fast-moving market, and continually bring customers the next great feature, the engineering team switched to real-time, event-driven data transactions powered by Confluent.
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