A Survey: Credit Sentiment Score Prediction

A. N. M. Sajedul Alam; Junaid Bin Kibria; Arnob Kumar Dey; Zawad Alam; Shifat Zaman; Motahar Mahtab; Mohammed Julfikar Ali Mahbub; Annajiat Alim Rasel

arXiv · 2209.15293

A Survey: Credit Sentiment Score Prediction

A. N. M. Sajedul Alam·Junaid Bin Kibria·Arnob Kumar Dey·Zawad Alam·Shifat Zaman·Motahar Mahtab·Mohammed Julfikar Ali Mahbub·Annajiat Alim Rasel

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Abstract

Manual approvals are still used by banks and other NGOs to approve loans. It takes time and is prone to mistakes because it is controlled by a bank employee. Several fields of machine learning mining technologies have been utilized to enhance various areas of credit rating forecast. A major goal of this research is to look at current sentiment analysis techniques that are being used to generate creditworthiness.

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A. N. M. Sajedul Alam, Junaid Bin Kibria, Arnob Kumar Dey, Zawad Alam, Shifat Zaman, Motahar Mahtab, Mohammed Julfikar Ali Mahbub, Annajiat Alim Rasel. 2022-09-30. A Survey: Credit Sentiment Score Prediction. https://arxiv.org/abs/2209.15293

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