Artificial intelligence applications in finance: a survey

Li, Xuemei; Sigov, Alexander; Ratkin, L.; Ivanov, L.A.; Li, Ling

doi:10.1080/23270012.2023.2244503

Cited by 15 publications

(2 citation statements)

References 89 publications

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“…The integration of Artificial Intelligence (AI) into the finance sector has been transformative, revolutionizing traditional practices and introducing a new era of efficiency, accuracy, and innovation. Li et al (2023) provide a comprehensive survey of AI applications in finance, highlighting its significant impact on financial forecasting, protection, analysis, and decision-making. This survey underscores the pivotal role of supervised learning and the rising popularity of deep learning technologies in reshaping financial services.…”

Section: Artificial Intelligence Applications Within Financementioning

confidence: 99%

“…The application of AI in finance represents a significant shift towards more efficient, accurate, and personalized financial services. The insights provided by Li et al (2023), Agarwal et al (2022), Tyagi et al (2022), and Jain (2023) highlight the transformative potential of AI in finance, as well as the challenges and considerations that accompany its adoption. As the finance sector continues to evolve, AI will undoubtedly play a central role in shaping its future.…”

Section: Artificial Intelligence Applications Within Financementioning

confidence: 99%

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The influence of AI on financial reporting quality: A critical review and analysis

Lawrence Damilare Oyeniyi,

Chinonye Esther Ugochukwu,

Noluthando Zamanjomane Mhlongo

2024

World J. Adv. Res. Rev.

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In an era where the confluence of Artificial Intelligence (AI) and financial reporting is reshaping the contours of financial analysis and accountability, this paper ventures into the heart of this transformation. With a purposeful gaze, it examines the burgeoning role of AI in enhancing the quality, accuracy, and timeliness of financial reporting. The study, anchored in a qualitative research methodology, meticulously explores the integration of AI technologies within the financial reporting landscape, aiming to illuminate the pathways through which AI can augment traditional reporting practices. Through the lens of this inquiry, the paper traverses the evolution of financial reporting, the foundational principles of AI, and the symbiotic relationship between AI applications and financial analytics, culminating in a nuanced understanding of AI's potential to revolutionize financial reporting. The main findings reveal that AI significantly enhances reporting accuracy, analytical depth, and efficiency, while also presenting challenges related to ethical considerations, regulatory compliance, and the potential for biases. These insights pave the way for a set of carefully articulated recommendations, advocating for the standardization of AI systems in financial reporting, the development of comprehensive regulatory frameworks, and the promotion of AI literacy among financial professionals. Conclusively, the paper posits that the strategic integration of AI into financial reporting is not merely an option but a necessity for the advancement of the field, urging stakeholders to embrace this technological evolution with a balanced approach that harmonizes innovation with ethical and regulatory imperatives. This scholarly endeavor not only contributes to the academic discourse on AI in financial reporting but also serves as a beacon for practitioners navigating the complexities of this digital transformation.

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Section: Artificial Intelligence Applications Within Financementioning

confidence: 99%

Section: Artificial Intelligence Applications Within Financementioning

confidence: 99%

The influence of AI on financial reporting quality: A critical review and analysis

Lawrence Damilare Oyeniyi,

Chinonye Esther Ugochukwu,

Noluthando Zamanjomane Mhlongo

2024

World J. Adv. Res. Rev.

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A systems perspective on the approach to industrial chain and supply chain ecology

Sun,

Yu,

Wang

2024

Syst Res Behav Sci

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To date, minimal literature is based on a systems perspective to examine the ecosystems of the industrial chain and supply chain. To fill the gap, this study has employed a systems perspective in analysing issues related to the industrial chain–supply chain ecology. The term ‘industrial chain–supply chain’ emerged recently to reflect the current global manufacturing industry structure and a prevalent global supply chain. This study clarifies the concepts of industrial chain ecosystem and supply chain ecosystem, highlighting their similarities and distinctions. Additionally, the study outlines the process of value creation within the industrial chain–supply chain ecosystem, involving innovation in research, technology, products, systems and management, leading to technological breakthroughs and enhancements. A three‐stage model for the industrial chain–supply chain ecosystem is proposed, comprising the blueprint creation stage, the core technology breakthrough stage and the iterative ecosystem upgrade stage.

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AI‐enabled information sharing mechanism and enterprise performance

Wang,

Zou

2024

Syst Res Behav Sci

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In recent years, with the continuous application and popularization of Artificial intelligence, the influence of artificial intelligence technology applied in information‐sharing mechanisms on enterprise performance has attracted more and more attention. With the background of the extended application of artificial intelligence in information sharing, based on the data of 348 manufacturing enterprises in the eastern coastal areas of China, the theoretical model of “information sharing mechanism ‐ accounting information quality ‐ enterprise performance” is constructed, and the relationship between the three is analyzed empirically. The results show that the stronger the information sharing mechanism and accounting information quality, the higher the enterprise performance; the information sharing promotes the accounting information quality; the quality of accounting information disclosure plays an intermediary role between information sharing and enterprise performance. Therefore, enterprises should pay attention to the use of artificial intelligence technology in information sharing to improve the quality of enterprise financial reports, improve enterprise performance, and provide theoretical references for the growth of manufacturing enterprises.

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Artificial intelligence applications in finance: a survey

Cited by 15 publications

References 89 publications

The influence of AI on financial reporting quality: A critical review and analysis

The influence of AI on financial reporting quality: A critical review and analysis

A systems perspective on the approach to industrial chain and supply chain ecology

AI‐enabled information sharing mechanism and enterprise performance

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