Impact of marketplace lending on consumers’ future borrowing capacities and borrowing outcomes

FinTech Loans, Self-Employment, and Financial Performance

“…In doing so, we demonstrate the role that FinTech loans play in conditioning self-employment activity, and show the differential role that it plays depending on the borrowers' initial employment status. Second, we add to the literature on FinTech loans and future financial performance (Chava et al, 2021;Di Maggio & Yao, 2021). We specifically show a positive effect of FinTech loans on future financial performance of self-employed individuals, this is different than that documented for general borrowers in previous studies.…”

“…We further show that this enhancement is stronger for more constrained self-employed individuals, selfemployed individuals in the lowest monthly income and credit access deciles. We contribute to the recent literature on credit access and self-employment (Corradin & Popov, 2015;Herkenhoff, Phillips, & Cohen-Cole, 2021) and FinTech loans and future performance (Chava, Ganduri, Paradkar, & Zhang, 2021;Di Maggio & Yao, 2021) by analyzing the impact of FinTech loans on self-employment decisions and future performance of serial FinTech borrowers, those most relying on FinTech loan outcome (Butler, Cornaggia, & Gurun, 2017).…”

How does a data strategy enable customer value? The case of FinTechs and traditional banks under the open finance framework

“…This study contributes to the literature on information asymmetry in banking, which currently is mainly concerned with financial inclusion and intermediation (Grassi et al 2022;Baek et al 2020;Demir et al 2020;Feyen et al 2021;Mhlanga 2020) or with the potential signals for success (Farag and Johan 2021; in ICO, Chen 2019, Chen and Chen 2020, Šapkauskienė and Višinskaitė 2020; in peer-to-peer funding and crowdfunding, Chava et al 2021;Lin et al 2013;Yeh and Chen 2020).…”

The financial health of a company and the risk of its default: Back to the future

“…In fact, [Rajan et al, 2015] find that "a statistical model fitted on past data underestimates defaults in a predictable manner." To stem these problems, an attempt was made to take into account the time-series evolution of the predictor variables, using macroeconomic data ( [Chava andJarrow, 2004, Das et al, 2007], and subsequent works). The results at the level of portfolio risk management improved, but the response of the individual borrower to macroeconomic trends (i.e., idiosyncratic risk) continues to be neglected.…”

“…The model is based on the use of "tailored" fundamental analysis techniques 7 . These are techniques customized on a judgmental basis ( [Clement andTse, 2005, Fracassi et al, 2016]) as a function of multiple competitive and strategic factors/information, and allows analysts ( [Crane andCrotty, 2020, Gredil et al, 2022]) and relationship bankers ( [Bharath et al, 2011, Brown et al, 2021, Chava et al, 2021, Han and Zhou, 2014) to more accurately evaluate and price risk. Thus, just as in the popular film Back to the Future, we imagine returning to the beginning of the 1960s, before the development of "mass" scoring systems, to divert the history of the financial intermediation market by implementing "tailored" scoring systems modeled on the rising fundamental analysis techniques.…”