Proposed Experiment
Under Review

[Proposed Experiment] SoCon I, Fiji Jan 2019 Testing Buka 4.0 Payment Plans (2/2)

Lean Phase: Solution

Assumption: SoCon team will receive the deposit and the first two payment plan repayments. This assumption is currently being used in conjunction with the financial model and survey results to determine the payment plan structure.

[Purpose: By observing and analysing the default rates and demographic data we will be able to construct better risk mitigation system and better determine the payment plan components.]

Time Box: 3 1/2 months.

Success Metric:

The percentage of borrowers who make the deposit and first two payments.

This will be tested with 15 sales of the Buka stove 4.0.

Green Light -  

1. If defaulting after first two payments - understand why
2. If they’re not defaulting at all - progress on payment plan structure.

Success point - Success if 70% of borrowers don’t default until after the first 2 payments.

Orange Light - Look at sales pitch, the way we are explaining SoCon and payments, etc.

Failure Point - Failure if over 40% default before first 2 payments.

Red Light- Understand why borrowers are defaulting so soon, and adjust financial model accordingly.

Experiment build:

  1. Converse with fuel team to collect buyer information including name, contact details (phone/email/address), and date of handover. Record information in simple table. Assume 3½ month payment plan structure has already been explained to buyers, with mobile money utilised as the method of transfer.
  2. Design the spreadsheet to input the data regarding payments. The spreadsheet is to include:
    1. Rows of buyers (name, contact details etc).
    2. Columns of date of handover, repayments 0 to 4 (deposit = repayment 0) Cells are ‘paid’ or ‘not paid’ and if required reason for default.
  3. Check to see if the deposit repayments are received at Day 0 and input the corresponding data into the spreadsheet (assume all buyers shall pay deposit).
  4. Progress through the three and a half month repayment period checking payment status and inputting the corresponding data into the spreadsheet with dates of repayments.  If the repayments not received at any point, contact the buyer and inquire reason for default. Input the reasons to the spreadsheet.
  5. Analyse the data to determine percentage of buyers paying the deposit and first two repayments, and obtain the success metric. (>70% = green light, <40% = red light, in between = orange light).
  6. If the success metric is reached, progress with the payment plan. If the failure point is reached, investigate why and see what changes need to be made, e.g: adaptation the of payment plan
  7. Summarise the results and draw conclusions, create a results document and upload to Crowdicity.

Jess Riley 3 months ago

Status label added: Under Review

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Jess Riley 3 months ago

Status label added: Proposed Experiment

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Fiona Aaron 3 months ago

Have you guys looked at doing any risk mitigation via surveying, income statements or anything like that by profiling the customers before giving the loan? Surely this would have some sort of positive impact on the default rates?

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Henry Edwards 3 months ago

That's a great question - at the moment our risk mitigation includes a requirement of a photocopy of a national ID, sending messages before repayments are due, calling defaulting customers and the implementation of a guarantor system. Of course before giving the loan we will also ask some basic financial questions such as how much they make and how often they are paid. Currently we do not require the use of an income statement or other financial documents - primarily because of the assumption that most of our customer segment does no posses such documentation. Do you have any other suggestions for risk mitigation?

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