Project Everest

Post Not Ready

[Idea/Concept Not Complete]: SoCon Fiji - Loan Structures - July 2018

Lean phase: MVP prototyping/ solution

 

Assumption: We are testing the assumption that loan structure directly correlates to the default rate of loanees and that consequently certain loan structures will be more effective than others at reducing risk.

 

Time period: This experiment (loan period) should be conducted over 3 months to allow time for repayment and enough time to see if the loanee will default.

 

Success metric

 

  • Default rate

  • Factors affecting default rate

 

Green light: If we identify that certain structures are more effective than another at reducing risk we will continue to test on the successful structures.

 

Success point: If less than 80% of people default on the loans at n>30.

 

Orange light: Variations and iterations of this experiments will include changing loan repayment periods, interest rates, and collection & monitoring methods.

 

Failure point: If more than 80% of people default on the loan at n>30.

 

Red light: If we identify that loan structure does not correlate to default rate then experiments should be conducting regarding repayment periods and collection & monitoring methods to reduce risk.

 

Experiment/ method

 

  1. Identify customer segment

  2. Use data from empathising to identify the best assumed loan structure

  3. Provide loans to more than 30 people

  4. Monitor and collect repayments

  5. Provide survey once final repayment is collected for loanees to complete

  6. Analyse data for results

 

Proposed loan structures

 

  1. Token loan

This loan involves providing the finances for a specific good to ensure it is being spent on an investment and not on consumption; the asset purchased will generate income that will contribute to the repayments. We have tested this loan with Fuel’s Buka Stoves; SoCon provided a ‘token’ for the stove, which they then repay over 3 weeks at an interest rate of 8%. We have also been in contact with hardware stores in Sigatoka looking at the viability of providing loans to their customers for products we deem a good investment e.g farming equipment.

 

  1. Kickback loan

The premise of this loan is that the uncertainty premium can be removed once the risk has been mitigated. Therefore, once the loan has been paid the interest rate can be reduced. We are testing this with farmers by offering them a loan at 13% and if it is paid on time then this will be reduced to 8%. This incentivises loan recipients to repay their loan on time reducing the risk of a default on a loan.  

 

  1. Collective loan

This loan is contingent on the community-focus and village dynamics in Fiji. The proposed structure of this loan is that multiple people are granted a loan and if one defaults then the others will carry the weight of the loan between them. This could be tested with farmers who operate collectively in their villages. For example a group of farmers from Naroro would like a loan for a tractor that they will share between them.

 

  1. Progressive loan

This loan structure involves initially loaning small amounts and if loans repaid on time, continuously increasing this amount. This process will build a credit score for individuals with limited financial history. Reducing the need for financial statements and other sources of data will allow us to increase access to financial assistance without inducing risk.

 

  1. Fixed period loan

Through empathising we have identified that many farmers are concerned about being able to pay back a loan due to the variability of their income. When we gave out loans to the Buka Stove customers many of them paid more than the required amount in some periods in order to settle their debt. Therefore this loan structure would give the loan recipient a final payment date, a recommended structure and minimum for each repayment, but ultimately it is at their discretion as to how much they repay each week. For farmers, this would allow them to repay larger amounts when their yield is successful and repay the minimum when they experience a poor crop yield.

edited on 5th September 2018, 23:09 by Justin Hakeem

Isaac Crawford Jul 26, 2018

Have you guys got access to any national level data that you can validate your face to face testing with? This would help draw stronger conclusions on the population, rather than the concentrated sample size that would be targeted in villages around Sigatoka. Data in terms of what loan structures work with banks or other Microfinance companies in Fiji?

Reply 0

Ineke Mann Aug 5, 2018

Currently the only national level data we have is from RBF and FBS but this is not specific to loan structures. There could be privacy concerns with accessing this kind of data but it should definitely be something to look into in the future because it would be so valuable.

Reply 0

Wade Tink Jul 26, 2018

Status label added: Idea/Concept Not Complete

Reply 0

Wade Tink Jul 26, 2018

Hi Ineke, can you please review the experimentation template and place this into that format. Looking forward to seeing the updated.

Users tagged:

Reply 0