2021/10/08 by Jaydip Sen, Sen, Jaydip, Rajdeep Sen +3 · 1 citation
Business, Management and Accounting · Computer Science · Decision Sciences · #Big Data and Business Intelligence #Blockchain Technology Applications and Security #FOS: Computer and information sciences #FOS: Economics and business #Machine Learning (cs.LG) #Statistical Finance (q-fin.ST) #Stock Market Forecasting Methods
paper · pdf · doi:10.48550/arxiv.2110.11999
openalex publication_date 2021/10/08 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
The paradigm of machine learning and artificial intelligence has pervaded our everyday life in such a way that it is no longer an area for esoteric academics and scientists putting their effort to solve a challenging research problem. The evolution is quite natural rather than accidental. With the exponential growth in processing speed and with the emergence of smarter algorithms for solving complex and challenging problems, organizations have found it possible to harness a humongous volume of data in realizing solutions that have far-reaching business values. This introductory chapter highlights some of the challenges and barriers that organizations in the financial services sector at the present encounter in adopting machine learning and artificial intelligence-based models and applications in their day-to-day operations.