Banking, Financial Services and Insurance(BFSI) Analytics
BFSI Industry is the leader in utilizing power of analytics and creating opportunity. Not surprising, >30% of current analytic opportunities are from this sector. This program builds a rock solid and fool proof understanding of analytics of 5C’s (Compliance, Competition, Complexity, Customization and Circumvention) in BFSI industry and positions you to make most out of the opportunity & prepares oneself to be business ready for the upcoming stream of disruptive innovation in this industry.
- Practical usage of Decision Science in respective domain.
- Prepare individuals to contribute in their organization’s journey towards data driven innovation.
- Learn about domain relevant tools and techniques.
- With financial industry being the largest consumer of analytics, the program designed to open up unlimited possibilities in an individual’s career.
- Encapsulating analytics of 5C’s (Compliance, Competition, Complexity, Customization and Circumvention) in BFSI for a solid learning.
- Eminent academicians and practitioners as course advisors and faculties.
- Program accredited and certified by Analytics Society of India.
- Case study based approach.
- Course pedagogy comprises of assignment()s and hands on project.
- Non-disruptive weekend program.
- Spans across 60 hours of 100% in classroom knowledge sharing.
- V Connect – Acts as a platform to connect with industry experts and get mentored.
- Route α – Your club to connect and progress.
- Overview of Analytics.
- Overview of analytics in BFSI.
Fundamentals of Statistical analysis
- Types of data, Central Tendencies, Central limit theorem, Probability distribution, Histogram, Hypothesis Testing, Sampling, Confidence Interval, Correlation.
- Processes of data quality check, missing data treatment/data imputation, data transformation.
Customer analytics in BFSI
- Segmentation & Acquisition, Cross Selling of Liability and Asset products.
- Dynamic Pricing & Reward analytics in Banking & Insurance.
- Customer Attrition prediction, Customer / Agent retention analytics, Sales Incentives.
Risk, Fraud and Compliance analytics
- Risk modeling, Credit scoring model, Application scoring model.
- Fraud Analytics (Banking transactions & Insurance claims – Traditional and Algorithmic).
- Delinquency prediction, Basel Norms.
- Survival analytics in insurance – Life Tables, KapMeier estimates, Predictive hazard modeling.
- Customer attrition, Loan foreclosure.
Analytics in Securities and Investments
- Asset allocation optimization, Stock/Forex forecasting.
- Discounted Cash flow, Profitability Ratio, Value at risk(VaR).
- Algorithmic trading.
- Derivatives – Brownian motion, Pricing options and Black–Scholes formula.
Analytical techniques for practical usage
- Practical application of following analytical techniques using financial case studies for above topics using R:
– Linear & Logistic regression
– Decision Trees
– Time Series
– Machine Learning – Random Forest
– Custom Algorithms
– Classification & Clustering (KNN, K-Means)