Event-Driven Architectures in Financial Services

Authors: Pavan Kumar Mantha

DOI: https://doi.org/10.37082/IJIRMPS.v7.i3.232941

Short DOI: https://doi.org/hbph2b

Country: United States

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Abstract: Financial services operate in an extremely fast-paced and highly regulated environment that increasingly requires real-time decision-making. Traditionally, data engineering in banks and other financial institutions has been highly controlled by batch-based data engineering systems, where data is periodically extracted, transformed and loaded (ETL) into centralized data warehouses. Although such a paradigm offered consistency and auditability, it is becoming more and more inadequate in detecting frauds, real-time risk detection, making immediate payments, and engaging customers in a personal relationship. This paper provides a detailed architectural discussion of event-based and streaming-first data architecture in the financial services, and in particular meta driven engineering as the key scalability mechanism. Instead of presenting scalability as a process rather than a process of adding another pipeline or more infrastructure, the paper claims that sustainable scale is reached by moving metadata out of passive documentation into control intelligence that can be executed. Metadata emerges as the controlling stratum that dictates ingestion, validation and governance policies and service-level objectives, and operational observability. The paper combines existing academic sources prior to 2019, industrial architectural trends, and regulatory anticipations to suggest a reference architecture where event streams assume the role of operational system of record (operational data), and metadata assumes the role of control plane (coordinates pipe activity). The paper discusses in detail automated ingestion, validation, governance, and monitoring mechanisms. The paper ends with the identification of architectural trade-offs and research directions of the future, such as self-healing pipelines and policy results in automation. Those results place financial data engineering based on metadata-driven, event-centric architectures as the fundamental transition to overcome the limitations of batch-driven financial data engineering to adaptable and intelligence-driven financial data systems.

Keywords: Event-driven architecture, streaming analytics, metadata-driven engineering, financial services, data governance, scalability, real-time systems.

Paper Id: 232941

Published On: 2019-06-08

Published In: Volume 7, Issue 3, May-June 2019

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