000			02986nam a22002177a 4500
020			_a9789388590907
082			_a332.10285 _bSIK
100			_aSikka, Bharat
245			_aPractical data analytics for BFSI : _bleveraging data science for driving decisions in banking, financial services, and insurance operations / _cBharat Sikka, Priyender Yadav and Prashant Verma
260			_aNew Delhi : _bOrange Education, _c2023.
300			_axxiv, 310 pages : _billustrations ; _c24 cm.
505			_a1. 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
520			_aThis 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.
520			_aThis 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.
650			_aBanking _vFinancial Services _xInsurance
650			_aAnalytics
650			_aData science
700			_aYadav, Priyender
700			_aVerma, Prashant
942			_2ddc _cBK
999			_c23691 _d23691