Balancing the load (narrow)
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This document discusses fine tuning policies over time at Zidisha, a micro-finance platform, including maximum loan size, invitation limit, and loan loss fee. Regression analysis found that changes took effect with a consistent 2 week lag. While typical borrower lag was 2 weeks across countries, different countries did not always have consistent behavioral responses. More experimentation and data is needed to fully validate and improve policies for each individual country.
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Balancing the load (narrow)
- 1. Balancing the Load: Optimizing Micro-Finance Supply & Demand
- 2. — Maximum loan size Fine Tuning: Zidisha’s Policies Over Time
- 3. — Maximum loan size — Invitation limit Fine Tuning: Zidisha’s Policies Over Time
- 4. — Invitation limit — Maximum loan size Fine Tuning: Zidisha’s Policies Over Time — Loan loss fee
- 5. Fine Tuning: Zidisha’s Policies Over Time — Invitation limit — Loan loss fee — Website optimization — Maximum loan size
- 6. — Maximum loan size PolicychangesFirstloansperweek — Invitation limit — Loan loss fee — Website optimization
- 7. Waiting for a Reaction: Lagged Regression — Loan loss fee — Website optimization R2 = 0.75 Lag: 2 weeks
- 8. — Loan loss fee — Website optimization — Fee upfront — Loans funded rate R2 = 0.87 Consistent 2 week lag
- 9. Takeaways for — Typical borrower lag is 2 weeks — Different countries do not have consistent behavior — More experimentation is required in each country — Improved record keeping needed — More data needed to validate Kenya results
- 10. About Me • Alex Glenday • Grew up in Nairobi, Kenya • PhD in Physics – Harvard University • Post-Doc – Harvard-Smithsonian Center for Astrophysics • More details at: www.balancingtheload.net
- 11. Ghana: Same Lag, But No Fee Effect R2 = 0.77
- 12. Indonesia: Slower Website Effect R2 = 0.76
- 13. Website & Upfront Consistent
Editor's Notes
- Zidisha is an online micro-finance non-profit using crowd sourced financing similar to Kickstarter. It needs to balance the rate that new borrowers sign up to match the supply of money coming in to finance loans. Too many new borrowers and many loans requests will only be partially supported (like Kickstarter there is a time limit to attract lenders to your loan) as the money is spread thinly over the loan requests, helping fewer people than if it was concentrated in a reduced number of loans. Too few borrowers will leave money on table that could have helped someone. Zidisha would like to know the size of the effect that various parameters it has control over will have on the rate that new borrowers take out loans.
- Make up – down policies green / red