This study aims to contribute to the academic and business knowledge of how to enhance digital credit in Pakistan's unsecured lending sector, which is vital to the development of the country's financial ecosystem. A Randomized Control Trial (RCT) is conducted with a view to answering two questions: (1) What is the optimal amount to lend to a customer? (2) How long should the loan tenor be? The objectives of the RCT were to track product take-up and product repayment as both are crucial for the success of a lending institution as well as the credit history of the individual customer. The study employs a linear probability model (LPM), estimated by an ordinary Least Squares (OLS) regression, to analyse take-up, and instrumental variables to analyse repayment sensitivity. The data used was obtained from a technology platform that partners with a Pakistani microfinance bank and was automatically collected via their USSD platform. The sample consisted of roughly 28,000 individuals. Causal evidence of the impact of changes in loan amount and loan repayment tenor was found on both take-up and repayment. Loan take-up was most impacted by the loan amount offered with the highest take-up for the loan of the largest amount and having the longest tenor. Repayment rates were better for the longer tenor loans and this was particularly apparent at the larger loan amount level. Some additional characteristics were also causally relevant in loan take-up but not in repayment, such as whether a customer read through the terms and conditions. Although the starting sample was large (28,000 individuals), the limited take-up of the product significantly reduced the actual sample, as is common in other studies of this kind. Future studies might seek for an even larger starting sample, alter price as one of the variables for an RCT, or add qualitative surveys to better understand loan usage and reasons for repayment and non-repayment.
| Identifer | oai:union.ndltd.org:netd.ac.za/oai:union.ndltd.org:uct/oai:localhost:11427/35777 |
| Date | 16 February 2022 |
| Creators | Johnston, Clarissa |
| Contributors | Alhassan, Abdul Latif |
| Publisher | Faculty of Commerce, Graduate School of Business (GSB) |
| Source Sets | South African National ETD Portal |
| Language | English |
| Detected Language | English |
| Type | Master Thesis, Masters, MBA |
| Format | application/pdf |
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