Cognitive Data Pipelines: Leveraging AI for Self-Optimizing and Resilient Data Supply Chains in Financial Regulatory and Analytics Environments
Year: 2025
Type: article
Abstract: The financial industry runs on data-and lots of it.We're talking about ever-growing amounts of information flowing at incredible speeds and in all sorts of formats.This data is crucial for everything from meeting strict regulations to powering advanced analytics.But here's the catch: traditional ways of moving and managing this data often can't keep up with the demands for agility, scalability, resilience, and cost-efficiency.This paper introduces a new idea: Cognitive Data Pipelines (CDPs).Imagine data pipelines that can essentially think for themselves, using Artificial Intelligence (AI) and Machine Learning (ML) to become selfoptimizing, self-healing, and highly adaptive.We'll explore the real challenges financial institutions face today in managing their data, lay out the architecture and main components of CDPs, and show you exactly how AI can inject intelligence into these pipelines.The paper goes on to analyze the significant benefits you can expect, including better operational efficiency, stronger adherence to regulations, reduced risk, and a clear Return on Investment (ROI).Finally, we'll discuss practical considerations for implementing CDPs in the financial sector and what the future might hold for them.
Language: English
Field: Decision Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4413170378