Part 1 - Applied Analytics Basics of Risk, Marketing, Collections analytics
  • Overview of Part 1 - applied analytics vertical wise
  • Birds Eye View of Analytics Verticals, their goals and inter linkage
  • Common Industry Terms - Understad terms like Loan types, billing cycle, due date
  • Marketing Analytics Overview - Objective and levers
  • Marketing Analytics Objective 1 - Increase / Maintain (reduce attrition) base
  • Marketing Analytics Objective 2 - Increase Revenue per customer (cross sell )
  • Marketing Analytics - campaign and it's effectiveness measurement
  • Campaign Analytics Advanced stuff - Uplift Moeling
  • Risk Analytics Overview - Objective and levers
  • RA obj 1: 1. aplication approval process and 2. application fraud prevention
  • RA Obj 2: Authorization & Transaction Fraud prevention
  • RA Obj 3: Credit Limit Management - CLI (Credit Limit Increase) & CLD (decrease
  • Collections Analytics Overview
  • CA 1: Best Practices of Collections Strategy for Early / Middle Late stage
  • CA 2: Collections Operations - how to contact & training needs of agents
  • Customer Services and Operations Analytics (detect internal fraud)
  • Example of analytics applications for business
Part 2 - Case Studies from Various Industries
  • Section Overview
  • Welcome Note
  • Sucess story from Healthcare Industry : win-win for the customer and firm
  • Telecom Industry - reduce churn, grow business using analytics
  • Automobile Industry - spectacular success of Ford Figo
  • Transport business - amazing usage of analytics for the purpose
  • Electronics Industry - best buy concept of store within store
  • Entertainment Industry - Casino, NetFlix and Apple ITune
  • Retail Chain - Analytics usage by Walmart and Tesco
  • Usage of Analytics in Sports - Moneyball
  • Using Analytics for efficient cement supply
  • Use of analytics by online merchants
  • Use of Analytics by Google - google search and google map
  • Analytics in contact center - improve pronunciation and collection
Closing Note and E-Book
  • Analytics Techniques at a glance - where to apply what?
  • Bonus Topic - Analytics / Data Science / Machine Learning Interview questions
  • Closing Note
  • E-Book (PDF of the presentation - part 1)
  • E-Book (PDF of the presentation - part 2)