Toward a Behavioural Intelligence Framework for Financial Stability: A National Model for Mitigating Systemic Risk in the United States Economy


Authors : Robert Adeniyi Aderinmola

Volume/Issue : Volume 10 - 2025, Issue 10 - October

Google Scholar : https://tinyurl.com/mrxftppt

Scribd : https://tinyurl.com/3kr7w6ze

DOI : https://doi.org/10.38124/ijisrt/25oct978

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Abstract : The stability of the United States' financial system increasingly depends on its ability to detect and respond to risks that emerge from behavioural, digital, and geopolitical domains. As financial shocks increasingly cross-national borders, there is a critical need for a comprehensive framework that integrates behavioural intelligence into national financial stability infrastructures. This article proposes a behavioural intelligence framework that unites sentiment analytics, cross-border surveillance, and predictive modelling into a coherent early-warning system for the United States economy. Sentiment analytics capture shifts in consumer confidence, investor psychology, and digital discourse, while cross-border surveillance detects contagion risks from global interdependence. Predictive modelling provides a forward-looking dimension, leveraging machine learning and advanced analytics to identify vulnerabilities before they escalate into systemic crises. Therefore, the proposed model demonstrates how behavioural intelligence can serve as a cornerstone for advancing the United States leadership in financial stability amid evolving systemic threats.

Keywords : Behavioural Intelligence; Economic Stability; Sentiment Analytics; Predictive Modelling.

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The stability of the United States' financial system increasingly depends on its ability to detect and respond to risks that emerge from behavioural, digital, and geopolitical domains. As financial shocks increasingly cross-national borders, there is a critical need for a comprehensive framework that integrates behavioural intelligence into national financial stability infrastructures. This article proposes a behavioural intelligence framework that unites sentiment analytics, cross-border surveillance, and predictive modelling into a coherent early-warning system for the United States economy. Sentiment analytics capture shifts in consumer confidence, investor psychology, and digital discourse, while cross-border surveillance detects contagion risks from global interdependence. Predictive modelling provides a forward-looking dimension, leveraging machine learning and advanced analytics to identify vulnerabilities before they escalate into systemic crises. Therefore, the proposed model demonstrates how behavioural intelligence can serve as a cornerstone for advancing the United States leadership in financial stability amid evolving systemic threats.

Keywords : Behavioural Intelligence; Economic Stability; Sentiment Analytics; Predictive Modelling.

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31 - December - 2025

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