Transforming T+1 Trade Settlement for Modern Markets With Confluent

This post applies Confluent's data streaming platform, specifically Kafka, to the financial services domain for T+1 trade settlement. It details how Kafka can ingest, store, and distribute trade data in real-time, overcoming batch processing limitations. Key technical aspects include using Confluent connectors for data ingestion from various financial systems (e.g., Oracle CDC, AMPS), leveraging the Kora engine for elasticity and reliability in handling market volatility, and employing stream processing (e.g., windowed sorting, KTables, point-in-time joins) to enrich and deliver data to siloed processes. It also mentions Role-Based Access Control (RBAC) for security and data governance. The post illustrates how these components enable faster settlement, reduce risk, and meet regulatory requirements.