The ai revolution: opportunities and challenges for the finance sector
C Maple, L Szpruch, G Epiphaniou, K Staykova… - arXiv preprint arXiv …, 2023 - arxiv.org
This report examines Artificial Intelligence (AI) in the financial sector, outlining its potential to
revolutionise the industry and identify its challenges. It underscores the criticality of a well …
revolutionise the industry and identify its challenges. It underscores the criticality of a well …
Blockchain and Artificial Intelligence (AI) integration for revolutionizing security and transparency in finance
The convergence of Blockchain technology and Artificial Intelligence (AI) is exerting a
transformative influence, ushering in a new epoch of security and transparency within the …
transformative influence, ushering in a new epoch of security and transparency within the …
Whistleblowing dan Korupsi Pada Sektor Publik: A Systematic Review
AD Paraswansa, DC Utomo - Jurnal Akademi Akuntansi, 2024 - ejournal.umm.ac.id
Tujuan penelitian: Penelitian ini bertujuan mengidentifikasi faktor-faktor yang memengaruhi
whistleblowing dan menganalisis dampak dankonsekuensi yang timbul dari implementasi …
whistleblowing dan menganalisis dampak dankonsekuensi yang timbul dari implementasi …
Forecasting for regulatory credit loss derived from the COVID-19 pandemic: A machine learning approach
MR González, AP Ureña… - Research in International …, 2023 - Elsevier
The economic onslaught of the COVID-19 pandemic has compromised the risk management
of financial institutions. The consequences related to such an unprecedented situation are …
of financial institutions. The consequences related to such an unprecedented situation are …
Algorithmic decision-making in financial services: economic and normative outcomes in consumer credit
H Sargeant - AI and Ethics, 2023 - Springer
Consider how much data is created and used based on our online behaviours and choices.
Converging foundational technologies now enable analytics of the vast data required for …
Converging foundational technologies now enable analytics of the vast data required for …
A Hypothesis on Good Practices for AI-based Systems for Financial Time Series Forecasting: Towards Domain-Driven XAI Methods
BH Misheva, J Osterrieder - arXiv preprint arXiv:2311.07513, 2023 - arxiv.org
Machine learning and deep learning have become increasingly prevalent in financial
prediction and forecasting tasks, offering advantages such as enhanced customer …
prediction and forecasting tasks, offering advantages such as enhanced customer …
Navigating the technical analysis in stock markets: Insights from bibliometric and topic modeling approaches
In stock markets, technical analysis plays a vital role by offering valuable insights into price
trends, patterns, and anticipated market movements, aiding investors in making well …
trends, patterns, and anticipated market movements, aiding investors in making well …
One-way road: the impact of artificial intelligence on the development of knowledge in management
This article aims to discuss and provoke researchers in Applied Social Sciences about the
impact of artificial intelligence (AI) on producing and disseminating scientific content. This is …
impact of artificial intelligence (AI) on producing and disseminating scientific content. This is …
Leading-edge Artificial intelligence (AI)-powered financial forecasting for shaping the future of investment strategies
This research paper investigates the profound influence of Artificial Intelligence (AI) on
financial forecasting and its pivotal role in molding the trajectory of investment strategies. In …
financial forecasting and its pivotal role in molding the trajectory of investment strategies. In …
Enhancing Stock Price Prediction Accuracy Using ARIMA and Advanced Greylag Goose Optimizer Algorithm
M Abotaleb, WH Lim, P Mishra… - Journal of Artificial …, 2024 - journals.ekb.eg
This paper applies ARIMA and the Greylag Goose Optimizer (GGO) algorithm, among
others, for pre-trending the stock market prediction. This study aims to improve stock price …
others, for pre-trending the stock market prediction. This study aims to improve stock price …