Unit 1
Introduction to Data-Driven Financial Services – Evolution of banking, insurance, and finance in the digital era. Meaning and importance of data-driven decision-making in financial services. Difference between traditional finance and data-driven finance. Role of data and AI in financial institutions. Types of data used in banking and insurance. Data-driven transformation in Indian and global financial institutions.
Unit 2
Customer Analytics in Banking and Insurance – Role of customer data in financial services. Customer segmentation and profiling using data. Understanding customer behavior and financial needs. Data-driven personalization of banking and insurance products. Predicting customer churn and retention. Benefits and limitations of customer analytics.
Unit 3
Data-Driven Risk Management and Fraud Detection – Types of financial risks in banking and insurance. Role of data analytics in credit risk assessment and its benefits. Data-driven underwriting in insurance. Fraud detection in banking, insurance, and digital payments. Benefits and challenges of analytics-based risk management. Case studies of data-driven risk and fraud management.
Unit 4
Data-Driven Financial Decision-Making – Role of data in financial planning and forecasting. Data-supported lending and investment decisions. Performance measurement in banking and insurance. AI-enabled decision support systems in finance. Comparison of data-driven vs traditional financial decisions.
Unit 5
Data-Driven Financial Products and Service Innovation – Role of data analytics in designing banking and insurance products. Data-driven pricing of financial products and insurance premiums. Personalization of banking and insurance services using data insights. Cross-selling and upselling strategies supported by data analytics. Data-enabled digital channels and service delivery in banking and insurance.