Practical Data Analytics for BFSI

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.

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.

WHAT WILL YOU 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 (fundamentals) and SQL (intermediate), crucial for effective data manipulation and analysis.
• Gain insights into how businesses adapt data-driven strategies to make informed decisions, leading to improved operational efficiency.
• Stay updated on emerging trends, technologies, and innovations shaping the future of data analytics in the BFSI industry.

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. 

The book also serves as a starting point for individuals interested in the BFSI sector. Prior experience with coding tools such as Python, SQL, Power BI is beneficial but not required as it covers all dimensions from the basics.

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

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. Over the years, he has worked on providing solutions to multiple business pain points in BFSI and Deep Optics. He has a thorough knowledge and understanding of various programming languages such as Python, R, MATLAB and Octave for Machine Learning, Deep Learning, Data Visualization and Analysis in Python, R and through Power BI, Tableau. He is also the author of Elements of Deep Learning for Computer Vision.

He currently works at Transunion as a Consultant, Data Science and Analytics. He has also served as a technical reviewer for books and articles on machine learning and deep learning. He is a traveling fanatic, a great cook and considers food exploration as his hobby. He loves writing and contributes to multiple journals and studies in Data Science.

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. He has also completed his Master of Business Administration (MBA) from Dr. B.R. Ambedkar University, Agra. He has been working in SBI since the last 9 years and currently is serving as a Chief Manager in the Analytics Department, SBI. 

He has published more than 15 articles in International and National journals, American Journal of Sociological Research, International Journal of Management and Information Technology, (IJMIT) , International Journal of Management Sciences and Technology, (IRJMST) etc.

Presently, he is working in Analytics and AI/ML model development, designing of Digital products through Machine Learning Models, leading a major role in implementation of end to end digital product in the areas of Operational efficiency, Cross Sell Business, Retail Credit, SME Business, Risk and Fraud and other areas of Banking.

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. He has worked for 5 Years as a Statistician at the Analytics Department, Global IT Center, State Bank of India, Navi Mumbai. He has also worked as Business Analyst at Tata Consultancy Services, Bangalore.

He has published more than 15 articles in international journals, including various springer journals like Biomedical Central Journals (BMC), Annals of Data Science, Genus, Etc. He has contributed 4 chapters in 2 edited books published by APP with CRC Press (Taylor & Francis Group).

He has received travel awards from the Indian Council of Medical Research (ICMR), New Delhi, and the Indian Council of Social-Science Research (ICSSR), New Delhi, for presenting articles at various international conferences. He has presented more than 15 articles at various National/International conferences. He has received a certificate of appreciation from the International Conference on Family Planning (ICFP-2015, Indonesia), Bill & Melinda Gates Institute for Population and Reproductive Health, Johns Hopkins Bloomberg School of Public Health for serving as an abstract reviewer. He has also served as an article reviewer for several journals. He has delivered invited lectures at various institutions and organisations.