Essays on Strategies for Increasing Repayment Rates of Digital Microloans

Access to credit can act as a highly effective tool for poverty reduction and economic growth. The ability to borrow increases the propensity of low-income people to start and maintain businesses, educate their children and withstand financial shocks. These factors, in turn, can help them to move out of poverty and lead to more sustainable economic development. However, traditional financial institutions have inherent limitations that have impeded their ability to serve the poor. Digital lenders are able to leverage the widespread adoption of mobile phones and mobile money to extend credit quickly and conveniently to more people, especially in developing countries. However, due to a lack of credit bureaus and available financial histories of borrowers, digital lenders frequently need to amass vast amounts of data in order to screen borrowers and experiment to find the appropriate loan amount by gradually increasing credit limits based on past repayment. This can lead to high user default rates and over-indebtedness. The lack of collateral during loan applications also means that digital lenders have limited mechanisms for enforcing repayment of loans. Both of these challenges threaten to limit further adoption of digital credit. Through three experimental studies conducted with an airtime lender, I explore theoretical and empirical mechanisms for reducing default rates of digital loans. In the first study, I demonstrate that limited mobile phone data contain enough signals for creating effective credit assessment methods that minimize privacy risks to borrowers. In the second study, I find that increasing credit limits negatively impacts repayments and future borrowing, and offer recommendations for increasing credit limits while minimizing the drawbacks. In the final study, I draw on theories from psychology and consumer behavior to develop vivid repayment reminders. This study found that vivid reminders had limited effectiveness for increasing loan repayment and reducing loan duration. Taken together, these three studies propose new avenues for digital lenders to reduce default rates. The hope of this dissertation is that these proposed methods would lead to a reduction in interest rates, that would ultimately benefit the borrowers

Responsible access to credit for sole-traders and micro-organizations under unstable market conditions with psychometrics

In a context of market volatility, the growing complexity of financial products, and a shift towards self-employment, there is an increasing demand for inclusive financial services for sole traders and micro-organizations. To address this need, we conducted a study using real-time data from a Fintech lender in the Czech Republic to assess the effectiveness of a new financial literacy based psychometric credit scoring model (PSM) in improving access to finance for micro, small and medium sized enterprises (MSME) sector, particularly sole traders, and micro-organizations, during volatile market conditions. This study affirms that PSMs play a significant role in responsibly including this underserved sector. Specifically, we observed a 30% higher approval rate and a 23% lower default rate when utilizing the PSM versus the traditional credit scoring model (TCSM). Moreover, during the period of substantial market volatility and instability, such as the state-of-emergency during the COVID-19 pandemic, the PSM exhibited a 13% higher approval rate at a 20% lower default rate than the TCSM. This evidence supports the proposition that PSMs offer a viable option for promoting financial inclusion and targeted financial education among MSMEs in the face of instable financial markets

The Myth of Financial Inclusion through FinTech: Focusing on the Digital Credit Industry in Kenya

Digital credit, a type of mobile loan service, has achieved remarkable success in Kenya. The advocates of digital credit argue that its unique characteristics are expected to give new opportunities to those who have been excluded from formal loan services due to their vulnerable socio-economic status. However, it has been questioned whether digital credit has had a positive impact on Kenyan households in terms of expanding financial inclusion. This thesis draws on insights from two different types of digital credit services, mobile banking loans (MBL) and Fin-Tech loans (FTL), which yield different results. Both digital credit services are indiscriminately provided to rural residents. Yet, the access to MBL is more influenced by the socio-economic characteristics of the borrowers than that of FTL. Female and low-income groups are less likely to use MBL, in contrast, the use of FTL is less affected by the variables of sex and the level of income, meaning that people who are female or of low-income could access FTL just as male and high-income classes could. However, it should be noted that easy access to loans is not always a good sign. FTL services could make the borrowers use excessive borrowing, leading to late-repayment or even default. In reality, it has been reported that a large number of digital credit borrowers in Kenya have been struggling with various problems, especially with high levels of default. Therefore, this thesis uses mixed methods combining OLS regression analysis and semi-structured interviews with digital credit borrowers in Nairobi’s slum areas, exploring the main drivers of high default rates on digital credit. According to the quantitative results, the use of digital credit itself influences default more than other factors such as consumers’ income level. It demonstrates that the use of digital credit itself has a greater effect on the likelihood of default than borrowers’ characteristics. Also, the study qualitatively identifies the characteristics of digital credit, such as high interest rates, short repayment periods, and the inducement of over-borrowing, which have made it harder for borrowers to repay the loans. In addition to high default rates, this thesis sought to identify the consumer protection issues currently facing Kenyan borrowers. Through key informant interviews (KIIs) with officials of MBLs and semi-structured interviews with consumers of digital credit, I conclude that the Kenyan digital credit environment is rife with consumer protection risks. Customers have been harmed by the problems of digital credit products; the characteristics of digital credit, such as high interest rates, aggressive business practices that encourage consumers to borrow continuously, and the existence of unlicensed lenders, may increase risks. There are instances of improper debt collection by digital credit lenders following default. In addition, the interviews reveal that there are problems with transparency because of violations of data privacy and deceptive marketing. To address these concerns regarding consumer protection, the Central Bank of Kenya Amendment Bill 2021 was introduced in December 2021. This is significant as it is the first serious attempt to regulate the digital credit market. However, based on the findings of this study, it appears that the new bill has limitations when it comes to addressing various consumer protection risks which I identify through the interviews. Moreover, certain provisions of the bill may endanger both borrowers and lenders. In conclusion, this thesis empirically explores the impact of digital credit on Kenyan households from multiple perspectives by listening to various stakeholders, digital credit borrowers and lenders, and by constructing a picture of the entire digital credit business using a mixed methods approach, and thus contributes to filling the knowledge gap. The results disprove the myth of digital credit's benefits and demonstrate the need for improved regulation and additional research