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Revolutionizing BFSI with Data Analytics
Key Features
● Real-world examples and exercises will ground you in the practical application of analytics techniques specific to BFSI.
● Master Python for essential coding, SQL for data manipulation, and industry-leading tools like IBM SPSS and Power BI for sophisticated analyses.
● Understand how data-driven strategies generate profits, mitigate risks, and redefine customer support dynamics within the BFSI sphere.
Book 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.
What you will learn
● Delve into the world of Data Science, including Artificial Intelligence and Machine Learning, with a focus on their application within BFSI.
● Explore hands-on examples and step-by-step tutorials that provide practical solutions to real-world challenges faced by banking institutions.
● Develop skills in essential programming languages such as Python
Who is this book for?
This book is tailored for professionals already engaged in or seeking roles within Data Analytics in the BFSI industry. Additionally, it serves as a strategic resource for business leaders and upper management, guiding them in shaping data platforms and products within their organizations.
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
About the Author
Bharat Sikka is a Data Scientist based in Mumbai, India. He holds a MS in Data Science and Analytics from Royal Holloway, University of London and BTech in Information Technology from Symbiosis International University and has earned multiple certifications including MOOCs in varied fields.
Dr. Priyender Yadav has a vast experience of more than 19 years in both Academics and Analytics in Banking Industry. He has completed his Master of Statistics (M. STAT) and Ph.D. in Statistics from Institute of Social Sciences, Dr. B.R. Ambedkar University, Agra.
Dr. Prashant Verma is currently serving as Asst. Professor, Department of Statistics, University of Allahabad. He has completed his PG and Ph.D. in Statistics from Banaras Hindu University (BHU), Varanasi.
ASIN : B0CHB4685K
Publisher : Orange Education Pvt Ltd (September 2, 2023)
Publication date : September 2, 2023
Language : English
File size : 4435 KB
Text-to-Speech : Enabled
Screen Reader : Supported
Enhanced typesetting : Enabled
X-Ray : Not Enabled
Word Wise : Not Enabled
Print length : 451 pages
