Practical Data Analytics for BFSI: Leveraging Data Science for Driving Decisions in Banking, Financial Services, and Insurance Operations


Practical Data Analytics for BFSI: Leveraging Data Science for Driving Decisions in Banking, Financial Services, and Insurance Operations (English Edition)
by: Mr. Bharat Sikka (Author), Dr. Priyender Yadav (Author), Dr. Prashant Verma (Author)
Publisher finelybook 出版社:‏ Orange Education Pvt Ltd (September 2, 2023)
Language 语言: English
Print Length 页数: 334 pages
ISBN-10: 9388590902
ISBN-13: 9789388590907

Book Description


DESCRIPTION
Are you looking to unlock the transformative potential of data analytics in the dynamic world of Banking, Financial Services, and Insurance (BFSI)? This book is your essential guide to mastering the intricate interplay of data science and analytics that underpins the BFSI landscape.
Designed for intermediate-level practitioners, as well as those aspiring to join the ranks of BFSI analytics professionals, this book is your compass in the data-driven realm of banking. Address the unique challenges and opportunities of the BFSI sector using Artificial Intelligence and Machine Learning models for a data driven analysis.
This book is a step by step guide to utilize tools like IBM SPSS and Microsoft Power BI. Hands-on examples that utilize Python and SQL programming languages make this an essential guide.
The book features numerous case studies that illuminate various use cases of Analytics in BFSI. Each chapter is enriched with practical insights and concludes with a valuable multiple-choice questionnaire, reinforcing understanding and engagement. This book will uncover how these solutions not only pave the way for increased profitability but also navigate risks with precision and elevate customer support to unparalleled heights.
TABLE OF CONTENTS
1. Introduction to BFSI and Data Driven Banking
2. Introduction to Analytics and Data Science
3. Major Areas of Analytics Utilization
4. Understanding Infrastructures behind BFSI for Analytics
5. Data Governance and AI/ML Model Governance in BFSI
6. Domains of BFSI and team planning
7. Customer Demographic Analysis and Customer Segmentation
8. Text Mining and Social Media Analytics
9. Lead Generation Through Analytical Reasoning and Machine Learning
10. Cross Sell and Up Sell of Products through Machine Learning
11. Pricing Optimization
12. Data Envelopment Analysis
13. ATM Cash Forecasting
14. Unstructured Data Analytics
15. Fraud Modelling
16. Detection of Money Laundering and Analysis
17. Credit Risk and Stressed Assets
18. High Performance Architectures: On-Premises and Cloud
19. Growing Trends in the Data-Driven Future of BFSI
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