Accelerating Fintech optimization and cybersecurity: The role of segment routing and MPLS in service provider networks

This review paper explores the profound impact of advanced financial modeling techniques on strategic business planning and performance. The paper begins with an overview of the evolution of financial modeling, highlighting the importance of advanced techniques such as Monte Carlo simulations, real options analysis, and machine learning models. It delves into the role of technology, including artificial intelligence and big data analytics, in enhancing financial modeling capabilities. The discussion then shifts to how these advanced models support strategic business planning by providing deeper insights, improving risk management, and facilitating better decision-making. The paper also examines the challenges of implementing advanced financial modeling, including data quality issues and skill gaps, and offers practical business recommendations. Future trends in financial modeling, such as increased AI integration and the incorporation of ESG factors, are also explored. The review concludes by emphasizing the significant benefits of advanced financial modeling in driving strategic business decisions and improving overall business performance. Keywords: Advanced Financial Modeling, Strategic Business Planning, Monte Carlo Simulations, Machine Learning Models, Risk Management.

Authors

Publication Details

Journal
Engineering Science & Technology Journal
Published
2024-08-11
DOI
https://doi.org/10.51594/estj.v5i8.1393
Citations
8
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
4.23
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article

Accelerating Fintech optimization and cybersecurity: The role of segment routing and MPLS in service provider networks

Adebimpe Bolatito Ige, Olajide Soji Osundare
8 citations
Engineering Science & Technology Journal
Big Data and Business Intelligence
4.23
article

Accelerating Fintech optimization and cybersecurity: The role of segment routing and MPLS in service provider networks

Adebimpe Bolatito Ige, Olajide Soji Osundare
article en
8 citations

Abstract

This review paper explores the profound impact of advanced financial modeling techniques on strategic business planning and performance. The paper begins with an overview of the evolution of financial modeling, highlighting the importance of advanced techniques such as Monte Carlo simulations, real options analysis, and machine learning models. It delves into the role of technology, including artificial intelligence and big data analytics, in enhancing financial modeling capabilities. The discussion then shifts to how these advanced models support strategic business planning by providing deeper insights, improving risk management, and facilitating better decision-making. The paper also examines the challenges of implementing advanced financial modeling, including data quality issues and skill gaps, and offers practical business recommendations. Future trends in financial modeling, such as increased AI integration and the incorporation of ESG factors, are also explored. The review concludes by emphasizing the significant benefits of advanced financial modeling in driving strategic business decisions and improving overall business performance. Keywords: Advanced Financial Modeling, Strategic Business Planning, Monte Carlo Simulations, Machine Learning Models, Risk Management.

Engineering Science & Technology JournalVol. 5(8)
Openalex Percentile: Top 5%
Big Data and Business Intelligence
4.23
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Accelerating Fintech optimization and cybersecurity: The role of segment routing and MPLS in service provider networks — Adebimpe Bolatito Ige, Olajide Soji Osundare · Engineering Science & Technology Journal (2024) | TGRS Research Map | TGRS