Big Data and Credit Management

Module Objective:

This module discusses big data and its functionality characteristics. A review of big data, analytics, and statistics is provided. Applications of big data, including to an Order-to-Cash process, is offered. A scientific approach to credit management is introduced. IFRS 9 and the estimation of a trade receivable’s expected loss are shared.

What to Expect:

• Big data and its aspects
  
• Big data vs Analytics vs Statistics
  
• Essential skills of big data analytics
  
• Learn from the casino's scientific profit model
  
• The quantifiable approach to credit management
  
• IFRS 9 and the Expected Loss Model
  
• Prediction of a trade receivable’s chance of default
  
• Delay payment vs default payment
  
• When should an overdue payment be classified as a bad debt?
  
• How to estimate an Expected Loss?