Transfer Learning and Transformer Architecture for Financial Sentiment Analysis

arXiv:2405.01586v1 Announce Type: new
Abstract: Financial sentiment analysis allows financial institutions like Banks and Insurance Companies to better manage the credit scoring of their customers in a better way. Financial domain uses specialized mechanisms which makes sentiment analysis difficult. In this paper, we propose a pre-trained language model which can help to solve this problem with fewer labelled data. We extend on the principles of Transfer learning and Transformation architecture principles and also take into consideration recent outbreak of pandemics …

abstract analysis architecture arxiv banks companies credit cs.cl customers domain financial financial institutions insurance language language model paper scoring sentiment sentiment analysis transfer transfer learning transformer transformer architecture type