We show that FinTech lending affects credit markets and real economic activity using a unique data set of a Peer-to-Business platform for which we have the universe of loan applications. We find that FinTech serves high quality and creditworthy small businesses who already have access to bank...

We examine the effects of FinTech lending on firm policies using proprietary data on loan applications and loans granted from a peer-to-business platform. We find that FinTech serves high-quality and creditworthy small businesses who already have access to bank credit. Firms access FinTech to...

Following the 2008 financial crisis, regulation mandates the clearing of the CDS market through Central Clearing Counter-parties (CCPs). Large CCPs are now designated as 'Global Systemically Important Institutions' (GSIIs), whose unlikely-but-plausible failure threatens global financial market...

Recent regulation mandating the clearing of credit default swaps (CDS) by a Central Clearing Counterparties (CCP), has rendered the latter a systemically important institution, whose failure poses a serious threat to global financial stability. This work investigates the potential failure of a...

Using 2013 and 2016 data, we compare the performance of unsecured consumer loans made by U.S. bank holding companies to that of the fintech lender, LendingClub. We focus on the volume of nonperforming unsecured consumer loans and apply a novel technique developed by Hughes and Moon (2017) that...

Mobile money, a technology-driven innovation in financial services, has profoundly penetrated the financial landscape in Sub-Saharan Africa, including banks. Yet, besides anecdotal evidence, little is known about whether mobile money adoption enhances or worsens bank performance. Combining...

Lending to Small and Medium Enterprises (SME) is facilitated by the availability of advanced Machine Learning (ML) methods, embedded in financial technologies, which can accurately predict financial performance from the many data sources available. However, despite their high predictive...

FinTech online lending to consumers has grown rapidly in the post-crisis era. As argued by its advocates, one key advantage of FinTech lending is that lenders can predict loan outcomes more accurately by employing complex analytical tools, such as machine learning (ML) methods. This study...

FinTech online lending to consumers has grown rapidly in the post-crisis era. As argued by its advocates, one key advantage of FinTech lending is that lenders can predict loan outcomes more accurately by employing complex analytical tools, such as machine learning (ML) methods. This study...

We study the role of privacy-insensitive data on device attributes in identifying loan default, under the context of ongoing tension between privacy protection and credit efficiency. Using a unique applicant-level data from a leading Fintech credit institution in China and merging two basic...