NBERWORKINGPAPERSERIES DOESFINTECHSUBSTITUTEFORBANKS?EVIDENCEFROMTHEPAYCHECK PROTECTIONPROGRAM IsilErel JackLiebersohn WorkingPaper27659 nber/papers/w27659 NATIONALBUREAUOFECONOMICRESEARCH 1050MassachusettsAvenue Cambridge,MA02138 August2020 WewouldliketothankRenStulz,TejaswiVelayudhan,DanielGreen,GregHoward,Victor Lyonnet for very helpful comments. Thanks to May Zhu for excellent research assistance. All errorsareour own.Theviewsexpressedhereinarethoseoftheauthorsanddonotnecessarily reflecttheviewsof theNationalBureauofEconomicResearch. NBERworkingpapersarecirculatedfordiscussionandcommentpurposes.Theyhavenotbeen peerreviewedorbeensubjecttothereviewbytheNBERBoardofDirectorsthataccompanies official NBERpublications. 2020byIsilErelandJackLiebersohn.Allrightsreserved.Shortsectionsoftext,nottoexceed two paragraphs,maybequotedwithoutexplicitpermissionprovidedthatfullcredit,including notice, isgiventothesourceDoesFinTechSubstituteforBanks?EvidencefromthePaycheckProtectionProgram IsilErelandJackLiebersohn NBERWorkingPaperNo.27659 August2020 JELNo.G00,G01,G2,G21,G23,G28,H12,H2,H3 ABSTRACT Newtechnologypromisestoexpandthesupplyoffinancialservicestoborrowerspoorlyserved by thebankingsystem.Doesitsucceed?WestudytheresponseofFinTechtofinancialservices demand created by the introduction of the Paycheck Protection Program (PPP). We find that FinTechisdisproportionately usedinZIPcodeswithfewerbankbranches,lowerincomes,anda largerminorityshareofthepopulation, aswellasinindustrieswithlittleexantesmallbusiness lending.ItsroleinPPPprovisionisalsogreater incountieswheretheeconomiceffectsofthe COVID19pandemicweremoresevere.Tounderstand whetherthesedifferencesarisebecause certaingroupsareswitchingfromtraditionalbankstoFinTech oriftheyarebeingnewlyserved byFinTech,westudywhetherFinTechenabledPPPloanswere morewidespreadinareaswith fewertraditionalloans.Usingthepredictedresponsivenessoftraditional bankstotheprogramas aninstrument,weshowthatborrowersweremorelikelytogetaFinTechenabled PPPloanif theywerelocatedinZIPcodeswherelocalbankswereunlikelytooriginatePPPloans. IsilErel FisherCollegeofBusiness OhioStateUniversity 2100NeilAvenue Columbus,OH43210 andNBER erelfisher.osu.edu JackLiebersohn UniversityofCaliforniaIrvine cjlieberuci.edu1 Introduction The COVID-19 pandemic has created a crisis like no other, with a projected global economic contraction of 4.9 percent in 2020. 1 It has induced tremendous stress on nancial institutions, with an unprecedented demand for their services. Li, Strahan and Zhang (2020) show that, during the last three weeks of March 2020, commercial banks faced the largest increase in demand for credit ever observed. Among rms that needed emergency liquidity, small businesses have been hit the worst: According to a recent State of Small Business Report, nearly one third of small businesses have shut down; and many that still survive have faced important challenges with liquidity and revenue. 2 Our paper studies the role of FinTech in an important government program aimed at providing immediate relief to small businesses during this crisis. As a response to the COVID-19 shock, the U.S. government created the Pay- check Protection Program (PPP), which oers guaranteed and potentially-forgivable small-businesses loans to provide a direct incentive for small businesses to keep their workers on the payroll. 3 Although the program is administered by the Small Busi- ness Administration (SBA), approved nancial institutions receive applications and distribute the funds, but do not bear credit risk from the loans. Traditional nancial institutions (i.e., depository institutions), however, have been shown to be inecient in their allocation of nancial services across customers from dierent locations and demographics (Philippon, 2015), and, in the particular case of allocating PPP loans, have been heavily criticized by the popular media for favoring their relationship bor- 1 World Economic Outlook Update, International Monetary Fund, June 2020. 2 May 2020 State of Small Business Report by Facebook and Small Business Roundtable. 3 PPP is an important part of the Coronavirus Aid, Relief, and Economic Security (CARES) Act: See sba.gov/funding-programs/loans/coronavirus-relief-options/paycheck-protection- program. See also Hamilton and Veuger (2020) for the importance of direct emergency loans in such unprecedented times. 2rowers at the expense of smaller rms that were hit hardest by the pandemic. 4 We also know that alternative sources of nancial intermediation have been devel- oping quickly. The role of Financial Technology (FinTech) has increased in dierent types of credit and other nancial services, by not only unregulated nonbanks but also by regulated banks. 5 Our primary question is whether specialized FinTech lenders respond dierently than traditional banks to the demand for PPP. This question speaks directly to the impact of including FinTech lenders when using banks as intermediaries to provide government services. Furthermore, FinTechs are a growing share of the nancial industry, so this study helps us understand how access to nancial services changes as a result of their expansion. We have three main ndings. First, we show that during Phase 1 of the program, when traditional banks were most constrained, FinTech lenders provided more PPP loans to areas with a worse economic shock while traditional banks provided less. Second, we show that borrowers with less local access to the traditional banking system | as proxied by the number of bank branches, for example | were more likely to get FinTech-enabled PPP loans. Finally, we use a Bartik-style instrument to show that at least part of the dierence in borrower composition was because applicants substituted to FinTech when traditional banks were not available. In areas where our instrument predicts lower traditional bank PPP lending, FinTechs originate more PPP loans per business. However, we estimate less than one-for-one substitution between banks and FinTech lenders, suggesting that FinTechs do expand access to the PPP program but do not fully close the gap in nancial services across regions. 4 E.g., Banks Gave Richest Clients Concierge Treatment for Pandemic Aid, NYT, April 2020. 5 See, e.g., Buchak, Matvos, Piskorski and Seru (2018), Chernenko, Erel and Prilmeier (2019), Stulz (2019), Liebersohn (2020), and Gopal and Schnabl (2020). 3Our ndings support the view in the popular press that traditional banks base their PPP originations on past relationships and are geographically constrained by the location of their physical branches, unlike FinTech which is mainly online and where prior relationships are less relevant. Comparing ZIP codes located in the same county, we nd that a larger fraction of traditional bank PPP loans were originated to applicants in areas with more bank branches. Relative to FinTechs, traditional banks also provided a higher fraction of PPP loans to rms in industries with stronger ties to the banking system, as proxied for by ex ante demand for SBA loans relative to new PPP demand. Next we study whether small businesses substitute to FinTechs when banks orig- inate few PPP loans. If small businesses do not substitute between traditional banks and FinTechs, this may indicate that FinTechs supply nancial services to a com- pletely distinct market relative to the traditional banking system. To test whether substitution happens, we rst create a bank-level measure of PPP responsiveness at the national level by calculating how many PPP loans each traditional bank origi- nates per branch. Using the ex ante location of each banks branches, we predict how much PPP origination we would expect based on the banks that happen to be lo- cated in each ZIP code, in an approach that is akin to a shift-share (Bartik) design. Note that using national lending patterns to predict local bank responsiveness yields variation in traditional banks PPP lending that is independent of the magnitude of the COVID-19 shock. We nd that there are fewer FinTech PPP loans per business in ZIP codes where local banks are more responsive. This nding implies that borrowers respond to a lack of bank PPP provision by somewhat (but not fully) substituting to these other types of nancial institutions. It is important to note that we nd evidence on substitution despite the fact that it is harder to get authorized for extending government subsidies 4for unregulated FinTech lenders; and, therefore, some FinTech lenders in our sample were granted authorization only during the last week of the Phase 1 of the PPP. The incentives in play for PPP loan origination are dierent from standard credit. Although technically termed loans, PPP funds are forgiveable in many circum- stances and the lender does not bear any credit risk. Therefore, the dierences in the response of FinTech and traditional banks in the PPP context may not map directly to the dierences in standard credit provision. Our results speak to the dierences between FinTechs and traditional banks use of relationships to allocate credit and their use of new technology, but not to dierences in credit evaluation and risk man- agement. Nevertheless, the PPP program sheds light on how dierences in technology and reliance on relationships between FinTech and traditional banks aect nancial intermediation. The rest of the paper is organized as follows. Section 2 reviews the literature on FinTech lending. Section 3 describes the PPP, discusses the data collection process and presents summary statistics. In Section 4, we present our main results on geog- raphy of online and nonbank lending. Section 5 addresses whether ZIP codes with less bank branches had more PPP loans by FinTech lenders, controlling for local de- mographics. In Section 6, we calculate predicted responsiveness of banks to the PPP and then test whether borrowers were more likely to get a FinTech-enabled loan if they are located in ZIP codes where local banks were unlikely to originate PPP loans. Section 7 concludes. 2 Literature Review Our paper contributes to the nascent literature on the role of FinTech in providing nancial services to rms or individuals. One paper that has studied dierences 5between FinTech and traditional banks in credit provision, Chernenko et al. (2019), shows that FinTech provides relatively more credit to unprotable businesses and that this is because they are subject to dierent regulation. In eect they nd that the FinTech and traditional credit markets are highly segmented. We nd that the FinTech-enabled PPP loans partially substituted for traditional loans. Several other papers have studied the role of FinTech lending to rms. Davydiuk, Marchuk and Rosen (2020) study commercial lending by Business Development Com- panies (BDCs). Hanson, Shleifer, Stein and Vishny (2015), Cortes, Demyanyk, Li, Loutskina and Strahan (2020), and Gopal and Schnabl (2020) show how various non- bank lenders have been lling the gap when large commercial banks faced regulatory constraints and, therefore, had to pull back from lending to small rms. 6 Although many purely online FinTech lenders started as peer-to-peer lenders ex- tending only personal loans, they have also moved to direct small-business lending. As Stulz (2019) discusses, two well-known FinTech rms, LendingClub and Kabbage, make traditional small-business loans through a banking subsidiary or a funding bank partner. Buchak et al. (2018) show that there has been a dramatic growth in online FinTech lenders of mortgage loans post-nancial crisis. FinTech banks have also been competing aggressively on the funding side of the nancial institutions balance sheet. Abrams (2019) points to the rapid growth in deposit contracts oered by online banks in the past decade: online banks now comprise four of the 30 largest banks by de- posits, pay higher deposit rates, and have about the same amount of market power over their depositors as midsize banks do. Given the way the PPP program is struc- 6 There are also papers using Dealscan data on larger loans to study loans extended by or sold to nonbanks. For example, Carey, Post, and Sharpe (1998) focus on loans arranged by nance companies. Berlin, Nini and Yu (2018), Lim, Minton and Weisbach (2014), Nadauld and Weisbach (2012), Ivashina and Sun (2011), Massoud, Nandy, Saunders and Song (2011), and Jiang, Li and Shao (2010), Biswas, Ozkan and Yin (2018), Irani, Iyer, Meisenzahl and Peydro (2020) study participation by nonbanks in loans arranged and syndicated by banks. 6tured, having an existing relationship with a bank, even through a simple commercial deposit account should matter. Insucient access to bank credit is one important reason for borrowers to bank with FinTech lenders (Cole, Cumming and Taylor (2019) Butler, Cornaggia and Gu- run (2016). Therefore, they are likely to serve the under-served and ll in gaps in lending, where traditional bank lending has contracted due to increased regula- tory constraints during and after the nancial crisis. They also oer convenience and faster processing through better technology (Buchak et al. (2018) and Fuster, Plosser, Schnabl and Vickery (2019). 7 Carlin, Olafsson and Pagel (2020) nd sig- nicant reductions in high-interest, unsecured debt and bank fees when individuals can get access to information about their bank balances and transactions more often. Therefore, they conclude that FinTech has signicantly improved consumers well- being. However, FinTech rms have limitations on what they can oer to customers. For example, Balyuk, Berger and Hackney (2020) show that FinTech lenders can sub- stitute for hard-information-based lending by large out-of-market banks, but are less able to compensate for the loss of relationship-based lending from small, in-market banks. Lastly, we also contribute to the literature on government interventions espe- cially, directed lending programs. Such programs can run in a form of a direct subsidy (e.g., Banerjee and Duo (2014) using data from India) or an indirect subsidy as in a loan guarantee (e.g., Claire, Sraer and Thesmar (2010) using data from France). PPP is also a directed lending program, where the Small Business Administration oered guaranteed and potentially forgivable loans to small businesses. But borrowers apply 7 There is also a growing literature on peer-to-peer personal loans that use FinTech, testing various predictions on lax screening/bottom shing or cream screaming, comparing these loans with bank loans (see, e.g., Morse (2015) for a review; de Roure, Pelizzon and Thakor (2018), Di Maggio and Yao (2018), Tang (2019), and Vallee and Zeng (2019) for more recent papers). 7for and receive loans through the system of nancial institutions. Therefore, the role of these institutions in this process is essential. Some contemporaneous papers have also studied the PPP program. Cororaton and Rosen (2020) study public rms that got funding through the PPP and received signicant med