The banking sector is experiencing profound digital transformation, driven by demands for real-time processing, hyper-personalized customer experiences, advanced analytics, and stringent regulatory compliance [1][2]. Event-Driven Architectures (EDA) powered by Apache Kafka have become foundational for building scalable, resilient systems capable of managing massive data volumes with minimal latency [3][4]. This paper investigates Kafka's pivotal role in enabling EDA within banking, facilitating big data analytics for applications such as real-time fraud detection, risk management, and customer 360-degree views [5][6]. Furthermore, it explores Kafka's support for agentic AI—autonomous agents that perceive environments, reason over data, and execute actions in multi-agent ecosystems, leveraging real-time event streams for coordination [7][8]. Key advantages include loose coupling of services, fault-tolerant processing, and integration with stream processors like Apache Flink [9]. Real-world deployments at institutions including Rabobank, Nationwide Building Society, ING Bank, Capital One, and Alpian Bank demonstrate tangible benefits, such as reduced fraud losses and enhanced operational agility [10][11]. Challenges like exactly-once semantics, schema evolution, security in regulated environments, and governance for AI agents are examined, alongside best practices and emerging protocols such as Model Context Protocol (MCP) and Agent-to-Agent (A2A) [12][13]. The synergy of EDA, data streaming, and agentic AI underscores Kafka's position as an essential technology for future-proof banking platforms.

Event-Driven Architecture (EDA) Apache Kafka Data Streaming Real-Time Processing Big Data Analytics Agentic AI Fraud Detection Risk Management Microservices Publish-Subscribe Event Sourcing CQRS Kafka Streams Kafka Connect Schema Registry Exactly-Once Semantics Multi-Agent Systems Retrieval-Augmented Generation (RAG) Model Context Protocol (MCP) Agent-to-Agent (A2A) Financial Services Transformation Cloud-Native Banking Fault Tolerance Scalability Low Latency [3][4][7][20].