Signal-Driven Financial Intelligence Architecture for Real-Time Transaction Pattern Recognition and Adaptive Banking Decisions

  • Authors

    • Nareddy Abhireddy Independent Researcher. USA. Author

    DOI:

    https://doi.org/10.67228/30715628/IJMIET-2024PI2M5R

    Published 05-06-2024

  • Signal-Driven Financial Intelligence, Real-Time Transaction Analysis, High-Frequency Data Processing, Transaction Pattern Recognition, Adaptive Banking Decisions, Streaming Data Analytics, Alert Classification, Credit Decision Intelligence, Financial Signal Detection, Banking System Stability

    Issue

    Vol. 7 No. 1 (2024)

    Section

    Articles

    How to Cite

    [1]
    N. Abhireddy, “Signal-Driven Financial Intelligence Architecture for Real-Time Transaction Pattern Recognition and Adaptive Banking Decisions ”, ijmiet, vol. 7, no. 1, pp. 01–13, May 2024, doi: 10.67228/30715628/IJMIET-2024PI2M5R.

  • Abstract

    A signal-driven financial intelligence architecture for real-time transaction pattern recognition and adaptive banking decisions is proposed. Recent advances in Artificial Intelligence (AI) and Machine Learning (ML) techniques can be harnessed to automate high-frequency market data analysis and decision-making processes. Conventional banking systems are yet to deploy real-time detection of events in transactional time series, leading to a lack of signal-driven operational intelligence for credit decision policies. The proposed architecture ingests high-frequency transaction data from various sources, processes them with a minimal time lag, and applies alert classification models to detect signals, thus complementing decision-making policies on product pricing and state estimation for system stability. Signal processing and detection in transactional databases acquire importance as real-time data becomes a viable resource thanks to streaming technology. However, the absence of real-time models, especially for the temporal flow of transactions, hinders data-driven adaptive decision-making on a near real-time basis. Transaction processing in banking services is still organized around batches scheduled at regular intervals. Management is done mostly through heuristics—decision makers tend to follow earlier decisions made in similar contexts. Signals are promptly visible to traders but not to the banking sector and regulators. Decision makers in the banking sector continue to rely on a stabilizing-principle perspective, treating banking systems in terms of equilibrium and stability around the equilibrating framework. Indeed, it has been shown that systemic crises are acts of man, not acts of God.

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