Enhancing Incident Management in Financial Services through Advanced Data Analytics

Authors

  • Arun Chandramouli USA Author

DOI:

https://doi.org/10.47363/JESMR/2022(3)227

Keywords:

Advanced Data Analytics, Incident Management, Financial Services, Data Cleaning, Customer Segmentation, Predictive Models, Prescriptive Analytics, Operational Efficiency, Machine Learning, Natural Language Processing, Anomaly Detection, Resolution Time Reduction, Customer Satisfaction, Proactive Management, Root Cause Analysis, Regulatory Compliance, Fraud Detection, Risk Forecasting, Sentiment Analysis, Visualization Techniques

Abstract

This study examines how advanced data analytics can transform incident management in the financial sector by addressing data quality issues, segmenting customer data, and using predictive analytics. It presents a comprehensive approach to improve incident data's accuracy and utility, boosting operational efficiency, customer satisfaction, and regulatory compliance. The paper includes real-time examples to showcase analytics implementation, aiming to enable financial institutions to anticipate and address challenges proactively through data-driven strategies.

Author Biography

  • Arun Chandramouli , USA

    USA

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Published

2022-07-21

Issue

Vol. 3 No. 3 (2022): Volume 3 Issue 3

Section

Articles