Proactive Infrastructure Reliability: AI-Powered Predictive Maintenance for Financial Ecosystem Resilience

Pushpalika Chatterjee ()

Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023, 2024, vol. 7, issue 01, 291-303

Abstract: Financial institutions rely on complex, high-availability infrastructure such as payment gateways, ATM networks, trading servers, and blockchain nodes. Unexpected downtime can lead to severe financial losses, reputational damage, customer dissatisfaction, and regulatory penalties. Traditional reactive maintenance models are insufficient for today's high-speed financial environments where uptime and reliability are critical. This paper proposes a predictive maintenance framework using machine learning (ML), deep learning (DL), and time-series analysis to anticipate and prevent infrastructure failures. We develop and test an AI model combining anomaly detection, failure prediction, and root cause analysis, validated against a synthetic dataset modeled on real-world financial operations. Our findings demonstrate that predictive maintenance can significantly reduce downtime by over 40%, enhance system resilience, optimize maintenance costs, and support regulatory compliance in fintech operations. We also discuss practical deployment challenges, scalability issues, cybersecurity concerns, and potential future research directions to enhance reliability in financial ecosystems.

Keywords: Predictive Maintenance; Financial Infrastructure; Anomaly Detection; Downtime Prevention; Time-Series Forecasting; AI in Fintech; Root Cause Analysis; Cybersecurity Resilience (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:

Downloads: (external link)
https://newjaigs.com/index.php/JAIGS/article/view/358 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:das:njaigs:v:7:y:2024:i:01:p:291-303:id:358

Access Statistics for this article

Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023 is currently edited by Justyna Żywiołek

More articles in Journal of Artificial Intelligence General science (JAIGS) ISSN:3006-4023 from Open Knowledge
Bibliographic data for series maintained by Open Knowledge ().