Version 1
: Received: 27 June 2024 / Approved: 27 June 2024 / Online: 27 June 2024 (15:28:49 CEST)
How to cite:
JAGLI, D. S.; Khambaye, S.; Solanki, R. Machine Learning in Fintech: Opportunities, Challenges and Future Directions. Preprints2024, 2024061969. https://doi.org/10.20944/preprints202406.1969.v1
JAGLI, D. S.; Khambaye, S.; Solanki, R. Machine Learning in Fintech: Opportunities, Challenges and Future Directions. Preprints 2024, 2024061969. https://doi.org/10.20944/preprints202406.1969.v1
JAGLI, D. S.; Khambaye, S.; Solanki, R. Machine Learning in Fintech: Opportunities, Challenges and Future Directions. Preprints2024, 2024061969. https://doi.org/10.20944/preprints202406.1969.v1
APA Style
JAGLI, D. S., Khambaye, S., & Solanki, R. (2024). Machine Learning in Fintech: Opportunities, Challenges and Future Directions. Preprints. https://doi.org/10.20944/preprints202406.1969.v1
Chicago/Turabian Style
JAGLI, D. S., Sakshi Khambaye and Ramesh Solanki. 2024 "Machine Learning in Fintech: Opportunities, Challenges and Future Directions" Preprints. https://doi.org/10.20944/preprints202406.1969.v1
Abstract
Abstract: Online services have transformed into a boon for various industries and globalization as a whole. One of the ventures reliant upon the Web is finance. Pattern prediction and risk reduction in the stock market and other financial decisions are made possible by some technologies. These technologies promise to expand innovation, knowledge, and efficiency opportunities in the financial sector. Finance frequently uses machine learning technology to identify risks based on probabilistic statistics and historical data to support investment decisions. Additionally, it can be utilized for risk assessment and risk management planning. Internet technology, which enables real-time data analysis, streamlined transactions, and improved customer communication, has particularly benefited the financial sector. However, these advancements come with significant challenges, such as the need for robust online credit protection and security threats. This study looks at how advanced machine learning methods are used in the financial sector and focuses on how they have changed credit scoring, algorithmic trading, and predictive modeling.
Computer Science and Mathematics, Artificial Intelligence and Machine Learning
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
