The Digitization Learning of Financial Markets.

EasyChair Preprint 15099

Abstract

This paper explores the integration of machine learning (ML) and data science techniques to enhance real-time fraud detection in financial markets. By utilizing large datasets, machine learning algorithms can identify patterns, anomalies, and outliers that are indicative of fraudulent behavior, enabling institutions to act quickly and mitigate risks. We examine key ML techniques such as supervised and unsupervised learning, and explore how advanced models, including deep learning and ensemble methods, provide greater accuracy in fraud detection. The role of data science in improving feature engineering, data preprocessing, and model interpretability is also highlighted.

Keyphrases: Digitalization, Financial, learning

@booklet{EasyChair:15099,
  author    = {Elizabeth Henry},
  title     = {The Digitization Learning of  Financial Markets.},
  howpublished = {EasyChair Preprint 15099},
  year      = {EasyChair, 2024}}