Integrating GenAI with Existing Financial Systems on Google Cloud

This research paper aims to study the interaction of Generative AI with other existing financial programs in the Google Cloud Platform environment.How GenAI could revolutionize finance across areas such as customer service and risk management is discussed, alongside the difficulties of implementing these and other nextgeneration models onto frequently outdated infrastructure.This paper explores these issues, such as data partitioning, compatibility with existing systems, concerns of security, and requirements for interpretability within the financial industry constraints.Based on GCP's strong fundamentals, analytics, and security, the study explores the optimal way to integrate them into a project.Topics discussed are data migration, using APIs, run time containers, and managing multi-cloud platforms.It is work that aims to present a reliable how-to guide for the implementation of GenAI on GCP for financial institutions.To do that while staying compliant with the regulations and secure data, the financial industry needs to become wiser and more efficient.

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Publication Details

Journal
International Research Journal of Education and Technology (IRJET).
Published
2024-11-29
DOI
https://doi.org/10.70127/irjedt.vol.7.issue10.451
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.53
Controls
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article

Integrating GenAI with Existing Financial Systems on Google Cloud

Mounica Yenugula
1 citations
International Research Journal of Education and Technology (IRJET).
Big Data and Business Intelligence
0.53
article

Integrating GenAI with Existing Financial Systems on Google Cloud

Mounica Yenugula
article en
1 citations

Abstract

This research paper aims to study the interaction of Generative AI with other existing financial programs in the Google Cloud Platform environment.How GenAI could revolutionize finance across areas such as customer service and risk management is discussed, alongside the difficulties of implementing these and other nextgeneration models onto frequently outdated infrastructure.This paper explores these issues, such as data partitioning, compatibility with existing systems, concerns of security, and requirements for interpretability within the financial industry constraints.Based on GCP's strong fundamentals, analytics, and security, the study explores the optimal way to integrate them into a project.Topics discussed are data migration, using APIs, run time containers, and managing multi-cloud platforms.It is work that aims to present a reliable how-to guide for the implementation of GenAI on GCP for financial institutions.To do that while staying compliant with the regulations and secure data, the financial industry needs to become wiser and more efficient.

International Research Journal of Education and Technology (IRJET).Vol. 6(11)
University of the Cumberlands (US)
Openalex Percentile: Top 21%
Big Data and Business Intelligence
0.53
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