Transforming Financial Services With Artificial Intelligence and Machine Learning DOI
Abdulhadi Ibrahim, Nashat Ali Almasria, Zaidoon Alhatabat

et al.

Advances in finance, accounting, and economics book series, Journal Year: 2024, Volume and Issue: unknown, P. 129 - 148

Published: Dec. 13, 2024

In modern dynamic business environments, the integration of machine learning (ML) and artificial intelligence (AI) into financial services investment decisions has significantly reshaped landscape. This comprehensive literature review explores AI tools, including predictive analytics, algorithmic trading, robo-advisors, enable data-driven insights real-time automation strategies fundamentals. Additionally, it was highlighted that these technologies enhance accuracy, speed, scalability decision-making in asset management, risk modeling, portfolio optimization considering uncertainty organization's environment. However, their application also presents challenges, such as data privacy concerns, biases, regulatory compliance issues. paper transformative impact ML analysis while addressing risks ethical considerations accompany use. Understanding tools' potential limitations is crucial for optimizing strategies.

Language: Английский

Where are the processes in IS research on digital transformation? A critical literature review and future research directions DOI Creative Commons
Martin Wiener, Susanne Strahringer, Julia Kotlarsky

et al.

The Journal of Strategic Information Systems, Journal Year: 2025, Volume and Issue: 34(2), P. 101900 - 101900

Published: April 8, 2025

Language: Английский

Citations

0
The impact of financial technology (FinTech) on improving financial performance: The case of commercial banks in Jordan DOI Open Access
Fadi Mohammed Alshannag,

Marah Mohammad Bani Hani,

Bilal Eneizan

et al.

International Journal of ADVANCED AND APPLIED SCIENCES, Journal Year: 2025, Volume and Issue: 12(3), P. 28 - 37

Published: March 1, 2025

This study explores the main financial technologies adopted by banks to improve their performance. The research sample includes 301 participants from commercial listed on Amman Stock Exchange (ASE). Financial performance is considered dependent variable, while technology (FinTech) independent variable. Multiple linear regression analysis will be used test hypotheses. findings indicate that FinTech contributes higher net income and total deposits. suggests should adopt inclusive approaches promote sustainable development.

Language: Английский

Citations

0
A knowledge-centric model for government-orchestrated digital transformation among the microbusiness sector DOI Creative Commons
Anuragini Shirish, Shirish C. Srivastava, Niki Panteli

et al.

The Journal of Strategic Information Systems, Journal Year: 2024, Volume and Issue: 34(1), P. 101870 - 101870

Published: Nov. 11, 2024

Language: Английский

Citations

2
Frugal innovation in the business environment: a literature review and future perspectives DOI Creative Commons
Carlos Escudero-Cipriani,

Julio García-del Junco,

Raquel Chafloque Céspedes

et al.

Frontiers in Artificial Intelligence, Journal Year: 2024, Volume and Issue: 7

Published: Dec. 6, 2024

This research aims to explore the growing field of frugal innovation within business environment, particularly its intersection with sustainability and artificial intelligence.

Language: Английский

Citations

2
Research on the impact of enterprise digital transformation based on digital twin technology on renewable energy investment decisions DOI Creative Commons
Mengxi Cao, Wonwook Song,

Yanyan Xu

et al.

Energy Informatics, Journal Year: 2024, Volume and Issue: 7(1)

Published: Dec. 30, 2024

In the context of global climate change and sustainable development, enterprise digital transformation has become key to improving efficiency competitiveness. Digital twin technology, as an emerging tool, enables real-time monitoring, prediction, optimization by creating dynamic virtual models real-world processes. This paper explores impact twin-based on renewable energy investment decisions. Through empirical analysis over 200 companies globally, study finds that using technology exhibit higher accuracy in These show improved forecasting consumption returns, gaining a competitive edge. On average, these experience 15% ROI increase for their investments enjoy 20% acceleration decision-making process. Furthermore, delves into how adoption differs across various company sizes industries, providing actionable insights guidance enterprises embarking journey.

Language: Английский

Citations

0
Transforming Financial Services With Artificial Intelligence and Machine Learning DOI
Abdulhadi Ibrahim, Nashat Ali Almasria, Zaidoon Alhatabat

et al.

Advances in finance, accounting, and economics book series, Journal Year: 2024, Volume and Issue: unknown, P. 129 - 148

Published: Dec. 13, 2024

In modern dynamic business environments, the integration of machine learning (ML) and artificial intelligence (AI) into financial services investment decisions has significantly reshaped landscape. This comprehensive literature review explores AI tools, including predictive analytics, algorithmic trading, robo-advisors, enable data-driven insights real-time automation strategies fundamentals. Additionally, it was highlighted that these technologies enhance accuracy, speed, scalability decision-making in asset management, risk modeling, portfolio optimization considering uncertainty organization's environment. However, their application also presents challenges, such as data privacy concerns, biases, regulatory compliance issues. paper transformative impact ML analysis while addressing risks ethical considerations accompany use. Understanding tools' potential limitations is crucial for optimizing strategies.

Language: Английский

Citations

0