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International Journal for Research Trends and Innovation
International Peer Reviewed & Refereed Journals, Open Access Journal
ISSN Approved Journal No: 2456-3315 | Impact factor: 8.14 | ESTD Year: 2016
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Issue: April 2026
Volume 11 | Issue 4
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Impact Factor : 8.14
Issue per Year : 12
Volume Published : 11
Issue Published : 119
Article Submitted : 22653
Article Published : 8822
Total Authors : 23281
Total Reviewer : 825
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| Paper Title: | Bank Customer Complaint Classification Using Machine Learning and Deep Learning Models |
| Authors Name: | Sumedha Arya |
| Download E-Certificate: | Download |
| Author Reg. ID: |
IJRTI_209695
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| Published Paper Id: | IJRTI2602034 |
| Published In: | Volume 11 Issue 2, February-2026 |
| DOI: | |
| Abstract: | Customer complaints are prominent in evaluating service quality and customer satisfaction for banking sector. With the rapid growth of digitalization, banks receive a large volume of unstructured complaints, making them difficult to perform manual analysis due to inefficiency and time-consumption. This study proposes an automated framework for analyzing and classifying bank customer complaints using machine learning (ML) and deep learning (DL) techniques. A large-scale dataset consisting of 162,421 customer complaints was collected from Kaggle. After data preprocessing, several ML models, including Logistic Regression, Decision Tree, Multinomial Naïve Bayes, and Random Forest, were trained using TF-IDF features, along with a DL model as Long Short-Term Memory (LSTM). Experimental results shows that the LSTM model outperforms traditional ML models, achieving a highest classification accuracy of 96.61%. The findings indicate that credit reporting-related complaints are the most dominant, highlighting critical areas for service improvement. The proposed system provides an effective and scalable solution for automated complaint classification and can support banks in service improvement. |
| Keywords: | Bank Customer Complaints, Complaint Classification, Machine Learning, Deep Learning, Natural Language Processing |
| Cite Article: | "Bank Customer Complaint Classification Using Machine Learning and Deep Learning Models", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 2, page no.a269-a275, February-2026, Available :http://www.ijrti.org/papers/IJRTI2602034.pdf |
| Downloads: | 000155 |
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2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016 An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator |
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Published Paper ID: IJRTI2602034
Registration ID:209695
Published In: Volume 11 Issue 2, February-2026
DOI (Digital Object Identifier):
Page No: a269-a275 Country: New Delhi, Delhi, India Research Area: Other Publisher : IJ Publication Published Paper URL : https://www.ijrti.org/viewpaperforall?paper=IJRTI2602034 Published Paper PDF: https://www.ijrti.org/papers/IJRTI2602034 |
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ISSN: 2456-3315
Impact Factor: 8.14 and ISSN APPROVED,
Journal Starting Year (ESTD) : 2016
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