TY  - BOOK
AU  - Sikka, Bharat 
AU  - Yadav, Priyender
AU  - Verma, Prashant
TI  - Practical data analytics for BFSI : : leveraging data science for driving decisions in banking, financial services, and insurance operations 
SN  - 9789388590907
U1  - 332.10285 
PY  - 2023///
CY  - New Delhi
PB  - Orange Education
KW  - Banking
KW  - Financial Services
KW  - Insurance
KW  - Analytics
KW  - Data science
N1  - 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
N2  - 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 explores the area of Data Science and Analytics, including Artificial Intelligence/Machine Learning, that runs behind the BFSI sector to provide its services. This book functionally explains the core concepts of how businesses adapt to Data-Driven solutions to generate profits, reduce risks, and provide better customer support, giving a brief idea to the top management in understanding such a field. On the other hand, this book technically aims to provide solutions to multiple banking pain points using programming languages like Python, R, IBM SPSS, etc.

The field of Data Science and Analytics has been in constant highlight for a decade now, and many major industries have stepped and benefited from the domain. BFSI leading the grips in the industry, generating a humungous amount of data. It is only necessary for BFSI to therefore benefit from the information available
ER  -