Event-Native Financial Onboarding Platforms: A Kafka-Centric Reference Architecture for Sub-Minute Identity and Compliance Processing
Tata Consultancy Services, Columbus OH, USA.
Research Article
World Journal of Advanced Research and Reviews, 2024, 21(02), 2182-2192
Publication history:
Received on 27 December 2023; revised on 18 February 2024; accepted on 26 February 2024
Abstract:
Traditional financial onboarding systems employ batch-oriented orchestration engines (BPM, Step Functions) that introduce latency bottlenecks ranging from 2-6 hours for regulatory compliance workflows. These architectures fundamentally constrain throughput through centralized state coordination and sequential processing dependencies. This research presents an event-native onboarding architecture leveraging Apache Kafka as the distributed system of record, eliminating batch orchestration entirely through stream-coordinated state machines. The proposed framework models customer identity verification, KYC, AML screening, and document validation as immutable event streams with exactly-once processing guarantees, enabling sub-minute compliance convergence at financial-grade reliability of 99.997%. Empirical evaluation demonstrates Time-to-First-Identity (TTFI) reduction from 127 minutes (batch baseline) to 48 seconds (streaming architecture), representing 158x latency improvement. Benchmark workloads processing 1M daily onboarding events achieve horizontal scalability through Kafka consumer group parallelism without coordination overhead. The architecture ensures regulatory reproducibility via event replay mechanisms, enabling retrospective compliance validation under evolving regulatory frameworks. Novel contributions include streaming-state onboarding model eliminating workflow engines, Kafka-based compliance orchestration with partition-affinity strategies, exactly-once financial event guarantees through transactional producers, and industry-standard performance benchmarks (TTFI, End-to-End Latency, Event Reprocessing Cost, Regulatory Drift Detection). Implementation on AWS infrastructure (ECS Fargate, Lambda, DynamoDB, S3) validates production viability with operational cost reductions of 67% compared to batch architectures.
Keywords:
Event-driven architecture; Apache Kafka; Financial onboarding; Stream processing; Exactly-once semantics; Compliance automation; Identity verification
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0