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eISSN: 2581-9615 || CODEN: WJARAI || Impact Factor 8.2 ||  CrossRef DOI

Research and review articles are invited for publication in March 2026 (Volume 29, Issue 3) Submit manuscript

Cognitive Goal-Driven Financial Infrastructure: A Cloud-Native, AI-Orchestrated Architecture for Investment Trade Settlement and Risk Management Systems

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  • Cognitive Goal-Driven Financial Infrastructure: A Cloud-Native, AI-Orchestrated Architecture for Investment Trade Settlement and Risk Management Systems

Uttama Reddy Sanepalli *

Fidelity Investments, NC, USA.
 
Research Article
World Journal of Advanced Research and Reviews, 2023, 19(01), 1659-1667
Article DOI: 10.30574/wjarr.2023.19.1.1358
DOI url: https://doi.org/10.30574/wjarr.2023.19.1.1358
 
Received on 24 May 2023; revised on 23 July 2023; accepted on 29 July 2023
 
Modern financial ecosystems confront an unprecedented convergence of operational complexities including ultra-high transaction volumes exceeding millions of operations per second, heterogeneous asset classes spanning traditional securities to digital instruments, real-time risk exposure monitoring requirements, dynamic regulatory volatility, and increasingly sophisticated user-specific financial objectives. Conventional financial platforms architect investments, trade settlements, and risk management as loosely coupled subsystems, creating latency bottlenecks that propagate through the execution chain, fragmented risk visibility that obscures systemic vulnerabilities, and suboptimal capital efficiency that reduces market competitiveness. This research proposes a Cognitive Goal-Driven Financial Infrastructure (CGDFI), representing a fundamentally novel cloud-native, AI-orchestrated architecture that unifies financial goal modeling, investment execution orchestration, trade settlement automation, and dynamic risk governance into a single adaptive computational system capable of processing transactions at planetary scale. The proposed methodology introduces three groundbreaking components: Goal-Conditioned Financial Graphs (GCFG) for semantic representation of investment logic, Reinforcement-Learning-Driven Settlement Orchestration for adaptive trade clearing, and Probabilistic Risk Digital Twins for transaction-level risk simulation. Experimental validation demonstrates 47% reduction in settlement latency, 63% improvement in systemic risk detection accuracy, and sustained throughput of 2.4 million transactions per second under stress conditions, establishing significant advancement beyond state-of-the-art approaches.
 
Cognitive Financial Infrastructure; Goal-Conditioned Graphs; Reinforcement Learning Settlement; Risk Digital Twins; Cloud-Native Architecture; AI-Orchestrated Trading; Real-Time Risk Management
 
https://wjarr.com/sites/default/files/fulltext_pdf/WJARR-2023-1358.pdf

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Uttama Reddy Sanepalli. Cognitive Goal-Driven Financial Infrastructure: A Cloud-Native, AI-Orchestrated Architecture for Investment Trade Settlement and Risk Management Systems. World Journal of Advanced Research and Reviews, 2023, 19(1), 1659-1667. Article DOI: https://doi.org/10.30574/wjarr.2023.19.1.1358

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