Hyper Personalized Microloans

Hyper Personalized Microloans

Prior Situation / Scenario:

  • Loans available to only 54% of the total prepaid base with highly restrictive rules
  • Generic, limited value proposition
  • High/flat fees for customers
  • Only loans based on prepaid balance

Client Challenges:

  • Improve data pack adoption and frequency
  • Reduce bad debt
  • Difficult to assign segmented/contextual offers for each subscriber profile
  • Improve customer experience

Strata Solution/ Key Enablers:

  • We deployed a Risk scoring model combined with a real-time triggers to approach subscribers based on prior usage and payment behavior to determine loan amount.
  • Segmented payback to reduce fees depending on outstanding debt

Outcome:

  • Increased the loans amount while keeping the risk controlled
  • Expand the targetable group for the service.
  • Simplified and shortened prepaid loans and accelerated loan payback rates.
  • Customer Satisfaction improved due to the service accessibility and contextual moment of Loan offering.

Results:

Within the first 12 months of the micro-loan deployment, target group increase by 27% and the total credit amount given increased by 39% while keeping the bad debt stable.