Loan Assistant using Text Processing and Natural Language Processing |
Author(s): |
| Poorva Paliwal , Acropolis Institute of Technology and Research; Priyal Sahu, Acropolis Institute of Technology and Research; Pratyush Pare, Acropolis Institute of Technology and Research; Juhi Shrivastava, Acropolis Institute of Technology and Research; Kavita Namdeo, Acropolis Institute of Technology and Research |
Keywords: |
| NLP: Natural Language Processing, NLTK: Natural Language Toolkit, NLU: Natural Language Understanding, NLG: Natural Language Generation, TF-IDF: Term frequency-inverse document frequency, ITF: Inverse Term Frequency, ML: Machine Learning |
Abstract |
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This paper aims to analyze and use some of the analytical techniques and tools which can be applied on human language. Nowadays, Natural language processing (NLP) has recently earned much attention for representing, analyzing and modifying text computationally. Its applications are widespread in various fields such as machine translation, detection of spam emails, information extraction, summarization, medical, and question answering etc. The paper analyzes finance related customer queries using text processing and NLP. The output acknowledges the customer about his loan sanctioning status. The goal is to decrease manual processing work in finance sectors and utilize new technologies in efficient way. The end result is to provide customer satisfaction with their experience in dealing with finance facilities. |
Other Details |
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Paper ID: IJSRDV8I20494 Published in: Volume : 8, Issue : 2 Publication Date: 01/05/2020 Page(s): 803-805 |
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