Digital Finance Enigmas: Inclusion, Privacy, and Return

Abstract

Digital finance employs digital technologies and data to provide and enhance financial services for individuals and businesses. It can enhance financial inclusion, efficiency, and security, but also pose challenges like data privacy, cybersecurity, consumer protection, and financial stability. This dissertation examines three topics in digital finance: the impact of cashless payment on credit access for the underprivileged, the data privacy paradox in consumer data-sharing choices, and the aggregate return on equity investments in ventures. Chapter 1 investigates how cashless payment affects credit access for the underprivileged using Alipay, a BigTech finance platform that serves over 1 billion users. Leveraging a natural experiment and a representative user sample, I find that cashless payment adoption increases credit access by 56.3% and a 1% rise in payment flow increases credit line by 0.41%. These effects are stronger for less educated and older users. Counterfactual analysis shows that cashless payment data increase credit lines by 57.7%, consumer surplus by 0.5% of median income, and lender profit by 41.3% of consumer surplus. Chapter 2, co-authored with Long Chen, Yadong Huang, and Wei Xiong, investigates consumer data-sharing choices in real-life settings. We combine survey and behavioral data to reveal the data privacy paradox, as respondents with stronger privacy concerns are found to authorize more data sharing. The paradox is not explained by unreliable survey responses or behavioral biases, but rather by privacy-concerned respondents having a higher demand for digital services, which counteracts their privacy concerns. This highlights a key tension within the data economy, as both privacy concerns and digital demands grow with the expansion of digital services. Chapter 3, co-authored with Ravi Jagannathan and Jiaheng Yu, measures the aggregate return on equity investments for various funding rounds of venture companies, valuing the founders’ investments at their first-round pre-money valuations. We examine 17,242 ventures that had their initial funding rounds between 1980 and 2006 and follow them until their exit or 2018. We use a return measure that does not require valuation information for interim funding rounds, which are often missing or biased. This approach offers a unique perspective on understanding the performance of venture capital investments.