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Fintech and banking: What do we know

Journal of Financial Intermediation 2020 41, 100833
This paper is a review of the literature on fintech and its interaction with banking. Included in fintech are innovations in payment systems (including cryptocurrencies), credit markets (including P2P lending), and insurance, with Blockchain-assisted smart contracts playing a role. The paper provides a definition of fintech, examines some statistics and stylized facts, and then reviews the theoretical and empirical literature. The review is organized around four main research questions. The paper summarizes our knowledge on these questions and concludes with questions for future research

On the Rise of FinTechs: Credit Scoring Using Digital Footprints

Review of Financial Studies 2020 33(7), 2845-2897
We analyze the information content of a digital footprint—that is, information that users leave online simply by accessing or registering on a Web site—for predicting consumer default. We show that even simple, easily accessible variables from a digital footprint match the information content of credit bureau scores. A digital footprint complements rather than substitutes for credit bureau information and affects access to credit and reduces default rates. We discuss the implications for financial intermediaries’ business models, access to credit for the unbanked, and the behavior of consumers, firms, and regulators in the digital sphere

Long-Run Growth of Financial Data Technology

American Economic Review 2020 110(8), 2485-2523 open access
“Big data” financial technology raises concerns about market inefficiency. A common concern is that the technology might induce traders to extract others’ information, rather than to produce information themselves. We allow agents to choose how much they learn about future asset values or about others’ demands, and we explore how improvements in data processing shape these information choices, trading strategies and market outcomes. Our main insight is that unbiased technological change can explain a market-wide shift in data collection and trading strategies. However, in the long run, as data processing technology becomes increasingly advanced, both types of data continue to be processed. Two competing forces keep the data economy in balance: data resolve investment risk, but future data create risk. The efficiency results that follow from these competing forces upend two pieces of common wisdom: our results offer a new take on what makes prices informative and whether trades typically deemed liquidity-providing actually make markets more resilient