August 23, 2025Open Access

Kafka Event Sourcing for Real-Time Risk Analysis

SKSagar Kesarpu HDHari Prasad DasariKing Abdullah University of Science and Technology

Key Points

The proposed architecture enhances real-time risk analysis through improved scalability and resilience, ensuring instant state reconstruction.
Utilizing immutable event streams in high-throughput scenarios, the system supports auditability and fault tolerance capabilities essential for risk management.
By integrating event sourcing with Apache Kafka, the approach demonstrates significant advantages in financial fraud detection and cybersecurity applications.
The model's distinct focus on risk evaluation points to promising directions for adapting strategies in hyperconnected operational contexts.

Abstract

In the age of hyperconnected systems and increasing regulatory scrutiny, real-time risk analysis has become a cornerstone of modern enterprise operations. This paper introduces a novel architecture combining Apache Kafka and event sourcing to facilitate dynamic, resilient, and scalable risk analytics. By leveraging Kafka's distributed log capabilities with immutable event streams, the system enables instant state reconstruction, auditability, and fault tolerance. We propose a domain-specific event model optimized for risk evaluation and demonstrate its efficacy in high-throughput environments, such as financial fraud detection and cybersecurity.

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