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Financial Services

4 posts
Fraud Prevention with Apache Kafka in Real Time in Financial Services and Banking
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  • 4 minute read

Fraud Prevention in Under 60 Seconds with Apache Kafka: How A Bank in Thailand is Leading the Charge

In the fast-paced world of finance, the ability to prevent fraud in real-time is not just a competitive advantage – it is a necessity. For one of the largest banks in Thailand Krungsri (Bank of Ayudhya), with its vast assets, loans, and deposits, the challenge of fraud prevention has taken center stage. This blog post explores how the bank is leveraging data streaming with Apache Kafka to detect and block fraudulent transactions in under 60 seconds to ensure the safety and trust of its customers.
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Multi-Cloud Replication in Real-Time with Apache Kafka and Cluster Linking
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  • 5 minute read

Multi-Cloud Replication in Real-Time with Apache Kafka and Cluster Linking

Multiple Apache Kafka clusters are the norm; not an exception anymore. Hybrid integration and multi-cloud replication for migration or disaster recovery are common use cases. This blog post explores a real-world success story from financial services around the transition of a large traditional bank from on-premise data centers into the public cloud for multi-cloud data sharing between AWS and Azure.
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The State of Data Streaming for Financial Services in 2023
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  • 9 minute read

The State of Data Streaming for Financial Services

This blog post explores the state of data streaming for financial services. The evolution of capital markets, retail banking and payments requires easy information sharing and open architecture. Data streaming allows integrating and correlating data in real-time at any scale. The foci are trending enterprise architectures for data streaming and customer stories. A complete slide deck and on-demand video recording are included.
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Decentralized Data Mesh with Data Streaming in Financial Services and Banking
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Decentralized Data Mesh with Data Streaming in Financial Services

Digital transformation requires agility and fast time to market as critical factors for success in any enterprise. The decentralization with a data mesh separates applications and business units into independent domains. Data sharing in real-time with data streaming helps to provide information in the proper context to the correct application at the right time. This blog post explores a case study from the financial services sector where a data mesh was built across countries for loosely coupled data sharing but standardized enterprise-wide data governance.
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