"Before the loans I had very little capital. I was unable to grow my business or even feed and clothe my family. But now, I am able to look after my family and build us a new home with running water and electricity." Jane Chiumia runs a timber business using sustainable wood.
Lendwithcare lenders have been helping to finance the small businesses of people like Jane from Malawi for the last eight years. Through Lendwithcare, over $30 million has been lent to 110,000 low-income entrepreneurs in 10 countries.
And in early 2015, in collaboration with the University of Portsmouth, Lendwithcare started collecting data on a range of social and economic indicators on the entrepreneurs the programme supports in Pakistan and Zimbabwe and compared these against a selection of non-borrowers.
What did we accomplish?
The first set of results are in and the changes we have seen are extremely positive so far. Between 2015 and 2018, in Pakistan we saw:
- 74% of respondents reporting an increase in business profits
- 77% reporting better standards of living (in terms of being able to cover household expenses, improved diet and healthcare)
- 55% of entrepreneurs improved their ‘poverty score’ in just two years (this refers to their Poverty Probability Index (PPI) score)
- The biggest changes in poverty score occurred for women and those who are illiterate (63% of women improved their poverty score and 62% of those who are illiterate improved their poverty score)
How did we get there?
- By identifying strong local partners whose goals align with ours. All Lendwithcare’s microfinance partners have a clearly identified and well-integrated poverty alleviation mission.
- By enabling our partners to leverage interest-free capital through the Lendwithcare platform to on-lend to pre-identified borrowers.
- By providing training and support to our partners in addition to capital to help build capacity and strengthen their social performance management.
What did we learn?
When conducting a longitudinal study amongst a transitory population, dropout rates can be very high, particularly amongst control groups. Regular quality control checks are important to ensure data is being collected accurately and to identify any areas of misunderstanding before too much data has been collected. We also found that the control group in Zimbabwe did not share the same characteristics as the borrower group once all the data had been collected and this has caused problems for us in terms of having a reliable control group.
Where do we go next?
Starting the third round of interviews in 2019 and will start introduce the study in one more country this year– Ecuador. We also plan to complement the findings with focus group discussions.
Want to learn more?
Check out evaluations from Pakistan and Zimbabwe. Read the blog post on Zimbabwe’s results.