Download PDFOpen PDF in browser

A Comprehensive Study on Integration of Big Data and AI in Financial Industry and its Effect on Present and Future Opportunities

EasyChair Preprint no. 11696

9 pagesDate: January 6, 2024

Abstract

This study evaluates the substantial influence of AI-technologies in the finance industry, with advancement expected
to accelerate in the next few years. It also forecasts the expansion of AI adoption across various business sectors and the integration
of AI-based operational networks with existing commercial systems to meet consumer demands. The financial industry will blend
AI-based transaction channels with established systems, enhancing the customer experience and efficiency. This integration will
streamline and advance transaction processes, making them more responsive to customer demands. The standard change in customer
dealings is expected to be a significant transformation in the financial sector. The transformative potential of Big Data and AI in the
financial sector goes beyond operational improvements; these technologies will create new opportunities for growth and
development, giving financial institutions a modest point in operational efficiency and innovative product and service offerings.
This study aims to investigate the overall impact of the convergence of Big Data and AI on the financial industry. It anticipates
increased revolution, diversification of commercial applications, and smooth AI integration into existing systems. These
technologies will shape the financial environment in the future, offering new opportunities for industry participants and consumers.

Keyphrases: AI, Big Data, comparative study, Financial Industry, OpenAI

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:11696,
  author = {Sina Ahmadi},
  title = {A Comprehensive Study on Integration of Big Data and AI in Financial Industry and its Effect on Present and Future Opportunities},
  howpublished = {EasyChair Preprint no. 11696},

  year = {EasyChair, 2024}}
Download PDFOpen PDF in browser