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At the Singapore Data in Motion Tour stop, keynote speaker and Confluent co-founder Jun Rao helped break down the history of Kafka and explain how Confluent got started on its mission to modernize data flows.
“Kafka was designed to work for a more transactional type of data, and not meant for large scale,” Rao said. Companies using Kafka started to realize there was tremendous growth with the amount of digitized information being generated as well as the amount of places they needed to leverage that information, all while moving at a fast pace. While Kafka helps to streamline digital architectures in real time, avoid complex point-to-point integrations, and break data silos, businesses still need a solution for the cost and complexity that comes with self-managing Kafka.
Kredivo Holdings, previously known as FinAccel, took the stage to describe its success with data streaming. I sat down for a fireside chat with Adityo August, the Senior Lead Data Engineering and Analytics at Kredivo, to hear their data streaming story.
Kredivo Holdings is a financial technology company that leverages deep data analytics across users’ digital footprint to automate credit risk scoring and access to credit in Southeast Asia. Their flagship product, Kredivo “Buy Now Pay Later” enables e-commerce buyers to apply and qualify for instant credit and pay it back over time.
During their chat, August said that their “business grew bigger and faster” than they anticipated and “Kafka quickly became tedious to maintain.” They initially came to Confluent to solve a single issue, and it ended up not only solving all of their issues, but in turn skyrocketing their business and making it easier to maintain and self-manage. Since turning to Confluent, August said that Kredivo Holdings was able to cut down on their monetary resources by 40%. It also sped up the company’s processes, allowing them to do more work in a shorter period of time.
Confluent makes it easy to build an entirely new category of modern, event-driven applications, gain a universal data pipeline, and unlock powerful new use cases with full scalability, security, and performance.
Learn more about data streaming for financial services
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