JFE-息技術(shù)與貸款人競爭-Information technology and lender competition

JournalofFinancialEconomics163(2025)103957

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Informationtechnologyandlendercompetition

☆

XavierVives

a

,

*

,ZhiqiangYe

b

aIESEBusinessSchool,Av.dePearson,21,Barcelona,08034,Spain

bSchoolofEconomics,ZhejiangUniversity,866YuhangtangRd,Hangzhou,310058,China

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updates

ARTICLEINFO

ABSTRACT

Westudyhowinformationtechnology(IT)affectslendercompetition,entrepreneurs’investment,andwelfareinaspatialmodel.TheeffectsofanITimprovementdependonwhetheritweakenstheinfluenceoflender–borrowerdistanceonmonitoringcosts.Ifitdoes,ithasahump-shapedeffectonentrepreneurs’investmentandsocialwelfare.Ifnot,competitionintensitydoesnotvary,improvinglenderprofits,entrepreneurs’investment,andsocialwelfare.Whenentrepreneurs’moralhazardproblemissevere,IT-inducedcompetitionismorelikelytoreduceinvestmentandwelfare.Wealsofindthatlenders’pricediscriminationisnotwelfare-optimal.OurresultsareconsistentwithreceivedempiricalworkonlendingtoSMEs.

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JELclassification:

G21G23I31

Keywords:

Credit

MonitoringFinTech

PricediscriminationMoralhazard

Regulation

1.Introduction

Thebankingindustryisundergoingadigitalrevolution.Agrow-ingnumberoffinancialtechnology(FinTech)companiesandBigTechplatformsareengagingintraditionalbankingbusinessesusingtheirin-novativeinformationandautomationtechnologies.

1

Incumbentbanksarealsomovingfromrelianceonphysicalbranchestoadoptinginfor-mationtechnology(IT)andBigDatainresponsetotheavailabilityoftechnologyandtochangesinconsumerexpectationsofservice,whicharetwomaindriversofdigitaldisruption(

FSB

,

2019

).Suchatransformationspursthebankingsector’sincreasinginvestmentinIT,allowingfinancialintermediariestoofferpersonalizedservicesand

topricediscriminate.TheCOVID-19pandemichasacceleratedthisdigitalizationprocessandfosteredremoteloanoperationsandthedevelopmentanddiffusionofITinthecreditmarket(

Carlettietal.

,

2020

).

Howdothedevelopmentanddiffusionofinformationtechnologyaffectlendingcompetition?WhatarethewelfareimplicationsofITprogress?Inparticular,doesthetypeofITmatterforcompetitionandwelfare?Isthereawelfarelossfrompricediscrimination?Toanswerthosequestions,webuildamodelofspatialcompetitioninwhichlenderscompetetoprovideentrepreneurswithloans.Lendersinourmodelrefertoinstitutionsthatcanprovideloansinthecreditmar-ket,includingcommercialbanks,shadowbanks,fintechs,orBigTech

☆PhilippSchnablwastheeditorforthisarticle.Wethanktheeditorandtwoanonymousrefereesfortheirhelpfulcomments.WearealsogratefultoparticipantsattheCEBRA2021AnnualMeeting,EARIE2021AnnualConference,EFA2021AnnualMeeting,ESEMVirtual2021,FinanceForum2022,FIRS2021Conference,MADBAR2020Workshop,Bocconi-CEPR2023Fintechconference,andtheAnnualConferenceoftheCentralBankofBrazil2024(andespeciallytoourdiscussantsToniAhnert,DavidMartinez-Miera,CeciliaParlatore,DavidRiveroandLinShen)andatseminarssponsoredbytheBankofCanada,BanquedeFrance,SaMMFJohnsHopkinsandSwissFinanceInstituteatEPFL–inparticular,toTobiasBerg,HansDegryse,AndreasFuster,ZhiguoHe,JulienHugonnier,RobertMarquez,GregorMatvos,SofiaPriazhkina,UdayRajan,AmitSeru,LauraVeldkamp,ChaojunWang,Pierre-OlivierWeill,DavidXiaoyuXuandLiyanYang.GiorgiaTrupiaprovidedexcellentresearchassistance.XavierVivesacknowledgesthefinancialsupportofGrantRef.PID2021-123113NB-I00fundedbyMCIN/AEI/10.13039/501100011033and‘‘ERDFAwayofmakingEurope’’bytheEuropeanUnion.

*Correspondingauthor.

E-mailaddresses:

xvives@

(X.Vives),

zhiqiangye@

(Z.Ye).

1ProminentexamplescanbeseeninChina,whereAlibabaandTencent–thetwolargestBigTechcompanies–areactiveinawiderangeoffinancialservicesthatincludepayments,wealthmanagement,andlending.IntheUnitedStates,almostone-thirdofsmallandmediumfirmsthatsoughtfinancingappliedwithaFinTechfirmoronlinelender,upfrom19%in2016(USFederalReserve’sSmallBusinessCreditSurvey2019).TheannualgrowthrateofthevolumeofFinTechbusinesslendingintheUnitedStateswasgreaterthan40%from2016to2020

(Bergetal.

,

2022

).Seealso

Vives

(2019

).

/10.1016/j.jfineco.2024.103957

Received22July2022;Receivedinrevisedform7October2024;Accepted11October2024Availableonline25October2024

0304-405X/?2024TheAuthors.PublishedbyElsevierB.V.ThisisanopenaccessarticleundertheCCBY-NC-NDlicense(

/licenses/by-

nc-nd/4.0/

).

X.VivesandZ.YeJournalofFinancialEconomics163(2025)103957

2

platforms.Ourmodelwillhelptoilluminatethefollowingempiricalresults:

?BusinesslendingbybankswithbetterITadoptionislessaffectedbythedistancebetweenbanksandtheirborrowers(

Ahnertetal.

,

2024

).

?Borrowerswithbetteraccesstobankfinancingrequestloansatlowerinterestratesonafintech’splatform(

Butleretal.

,

2017

).Abankwillchargeitsborrowershigherloanratesiftheborrowersgetgeographicallyclosertothebankor/andfartherawayfromcompetingbanks

(Herpferetal.

,

2022

).

?Increasedbank/branchindustryspecialization(e.g.,inexport/SME)lendingcurtailsbankcompetition(

Paravisinietal.

,

2023

;

Duquerroyetal.

,

2022

).Broadbandinternetimplementationin-tensifiesbankcompetitionandreducesbanks’loanprices

(D’Andreaetal.

,

2021

).

?BankswithsuperiorITadoptionhavehigherloangrowth

(Dadoukisetal.

,

2021

and

Branzolietal.

,

2024

).Entrepreneur-shipisstrongerinUScountiesthataremoreexposedtoIT-

intensivebanks

(Ahnertetal.

,

2024

).

?Therelationshipbetweenbankcompetitionandbankcreditsup-plyishump-shaped

(DiPattiandDell’Ariccia

,

2004

).

Thelendingmarketismodeledasalinearcityàla

Hotelling

(

1929

)wheretwolenderslocatedatthetwoextremesofthecitycompeteforentrepreneurswhoaredistributedalongthesegment.Entrepreneurscanundertakescalableriskyinvestmentprojects,whichmaysucceedorfail,andhavenoinitialcapital.Hence,theyrequirefundingfromlenders.LendershavenodirectaccesstoinvestmentprojectsandcompeteinaBertrandfashionbysimultaneouslypostingtheirdiscrim-inatoryloanrateschedules.WetakeitasgiventhatITisadvancedenoughforlenderstopriceflexibly.Anentrepreneurcanshirkandde-riveaprivatebenefit,whichisex-anterandomandunobservable,afterobtainingloansfromthelender;ifsheshirks,herinvestmentprojectwillfailforsure.Acriticallenderfunctionismonitoringentrepreneurstoreducetheirprivatebenefitsofshirking(see,e.g.,

Holmstromand

Tirole

,

1997

).Monitoringismorecostlyforalenderifthereisalargerdistancebetweenthelenderandthemonitoredentrepreneur.Thisdistancecanbephysical

2

orinthecharacteristicsspacefromthelender’sexpertiseincertainsectorsorindustries.

3

Afteranentrepreneurhaschosenalenderforfunding,herprivatebenefitofshirkingbecomesobservabletothelender,whichwillthenadjustcreditavailability–modeledasthemaximumsizeoftheloanavailabletotheentrepreneur–basedontheobservedprivatebenefit.Forsimplicity,weassumethatlenderscanprovideloansatagivenmarginalfundingcostanddonotmodelhowlenderscompetetodeveloprelationshipswithinvestorsordepositors.

4

2Thereisevidencethatfirm–lenderphysicaldistancemattersforlending.See

DegryseandOngena

(2005

),

PetersenandRajan

(2002

)and

Brevoortand

Wolken

(2009

).

3

Blickleetal.

(2023

)findthatabank‘‘specializes’’byconcentratingitslendingdisproportionatelyononeindustrywhereithasbetterknowl-edge.

Paravisinietal.

(2023

)documentthatexporterstoagivencountryaremorelikelytobefinancedbyabankwithbetterexpertise.

Duquerroyetal.

(2022

)findthatinlocalmarkets,thereexistspecializedbankbranchesthatconcentratetheirSMElendingoncertainindustries.

4Weadmitthatthisisalimitation.

Drechsleretal.

(2021

)emphasizetheimportanceofthedepositfranchiseforbankstoincreasetheirmarketpoweroverretaildeposits,allowingthemtoborrowatratesthatarelowandinsensitivetomarketinterestrates.

MatutesandVives

(1996

)and

Cordella

andYeyati

(2002

)studybankcompetitionfordepositswithinasimilarspatialcompetitionframework,butintheirmodels,bankscandirectlyinvestinriskyassets.

Themodelhastwoimportantingredients:First,lendermonitoringmattersforwelfaresinceitenablesentrepreneurswithmoralhazardproblemstoobtaincreditandinvest.Second,lenderscannotcredi-blycommittomonitoringeffortexantesincetheycanadjustcreditavailabilitylater(afterobservingentrepreneurs’privatebenefits).

Wedistinguishtwotypesofinformationtechnology:(a)infor-mationcollection/processingtechnology(IT-basicforshort)and(b)distancefriction-reducingtechnology(IT-distanceforshort).Improve-mentsinthetwotypesofITgeneratedifferentoutcomes.Specifically,animprovementinIT-basiclowersevenlythecostsofmonitoringen-trepreneursindifferentlocations.Suchanimprovementinthelendingsectordoesnotaffectlenders’relativecostadvantageindifferentloca-tions–forexample,byimprovingtheabilitytocollectmorevaluabledataandprocessthemwithbettercomputerhardwareorinforma-tionmanagementsoftware(e.g.,desktopapplications).Incontrast,improvingIT-distancereducesthenegativeeffectoflender–borrowerdistanceonmonitoringcosts.Suchanimprovementlowersmoresignif-icantlythecostsofmonitoringentrepreneurslocatedfartheraway.Forexample,betterinternetconnectivityandcommunicationtechnology(e.g.,videoconferencing)reducethephysicaldistancefriction.

5

Theimprovementinremotelearningdevices,searchengines,andartificialintelligence(AI)makesiteasiertoextendexpertise,therebyreduc-ingtheexpertisedistancefriction.BigDataandmachinelearningtechniquesmayimprovebothIT-basicandIT-distance.

6

Undertheset-updescribed,westudyhowinformationtechnol-ogyaffectslendercompetitionandobtainresultsconsistentwiththeavailableempiricalevidence.Theequilibriumconsequencesofim-provementsinthetwotypesoftechnology(IT-basicv.s.IT-distance)arecompared.WefindthatbyadoptingmoreadvancedIT,whateveritstype,alendercanchargehigherloanratesandprovidemoreloans.Thisissobecausealender’sITprogressincreasesitscompetitiveadvantageoveritsrival.

Whenbothlendersmaketechnologicalprogress,thatprogresswillnotincreasetheoverallcompetitiveadvantageofeitherlender.Inthiscase,differenttypesofITprogresscanyielddifferentresults.IfITprogressreducesthecostsofmonitoringanentrepreneurwith-outalteringlenders’relativecostadvantage(i.e.,IT-basicimproves),lenders’competitionintensitywillnotbeaffected.Inthiscase,theloanratesthatlendersoffertoentrepreneursdonotvary;lendersbecomemoreprofitableandprovidemoreloansbecausemonitoringisnowcheaper(i.e.,monitoringefficiencyishigher).However,ifITprogressinvolvesaweakeningintheinfluenceoflender–borrowerdistanceonmonitoringcosts(i.e.,IT-distanceimproves),lenders’competitionintensitywillincreasebecausetheirdifferentiationbecomessmaller.Then,theloanratesofferedtoentrepreneursdeclineforbothlenders.Suchadifferentiation-reducingeffectdecreaseslenders’profitsdespitethefactthatITprogressmakesmonitoringcheaper.

TheeffectofIT-distanceprogressonlenders’creditsupplyis‘‘hump-shaped’’.IT-distanceprogressgeneratesthreeeffectsonloansupply:First,itimproveslenders’monitoringefficiency,tendingtoincreasetheircreditsupply.Second,lenders’differentiationandloanratesde-crease,increasingentrepreneurs’skininthegameandalleviatingmoralhazard;thiseffectalsotendstoincreasecreditsupply.Finally,lenders’skininthegamedecreases,reducingtheirmonitoringincentivesandwillingnesstosupplycredit.Thefirsttwoeffectsdominateandincreaselenders’creditsupplyandentrepreneurs’investmentwhenIT-distanceisnotsufficientlyadvanced(i.e.,whenlenderdifferentiationishigh),whilethelasteffect–thedecreaseinlenders’monitoringincentives

5

Jiangetal.

(2023

)findsthat3Gmobilenetworkssignificantlyreducedistancefrictionforbanks,geographicallyexpandingtheirlending.

6Therearemanycompanies(e.g.,Zestfinance,Scienapticsystems,Datarobot,Underwrite.ai)thathelpthefinancialindustryimproveinformationprocessingviaBigDataandmachinelearningtechniques,thustransformingsoftdataintoharddata.Seealso

Bootetal.

(2021

).

X.VivesandZ.YeJournalofFinancialEconomics163(2025)103957

3

–dominatesandreduceslenders’creditsupplyandentrepreneurs’investmentwhenIT-distanceissufficientlyadvanced.Moreover,asentrepreneurs’moralhazardproblembecomesmoresevere,thelasteffectwillbemorelikelytodominatethefirsttwo.Thereasonisthatamoreseveremoralhazardproblemincreasestheneedformonitoring,hencemakingtheprovisionofmonitoringincentives(determinedbylenders’skininthegame)moreimportanttocreditsupply.Incontrast,IT-basicprogressunambiguouslyincreaseslenders’creditsupplysinceithasnodifferentiationeffect.

Ourmodelcanshedlightonthecompetitionbetweenatraditionalbank–whichhasbetteraccesstofirmdataandhenceanadvantageinIT-basic–andafintechlenderwithbetterIT-distanceandlackoffirmdata.WithitsbetterIT-basic,thebankcanensureapositivemarketsharebecauseithashighermonitoringefficiencythanthefintechwhenservingfirmssufficientlyclosetothebank.Theimplicationisthatalthoughfintechs,withtheiradvantageinIT-distance,canbringcom-petitivepressuretobanks,thelatterwillnotbecompletelyreplaced.Moreover,ifthebankhasacheaperfundingsource(e.g.,deposits)thanthefintech,thenthebankwillofferlowerloanratesandvolumesthanthefintechwhenservingentrepreneursofsimilarcharacteristics.

Next,weanalyzethewelfareeffectsofinformationtechnologyprogress.Wefindthatmoreintensecompetitiondoesnotalwaysfavorsocialwelfare.Whenlendercompetitionisnotintense,increasingcom-petitionintensityimproveswelfarebecauseitincreasesentrepreneurs’skininthegamefromexcessivelylowlevelsandsubstantiallyalleviatestheirmoralhazardproblem.Yet‘‘toomuch’’competitionreducessocialwelfarebecausehighcompetitionintensitydecreaseslenders’skininthegameandtheirmonitoringincentives,therebyreducinglenders’willingnesstoextendcreditsupply.Hence,animprovementinIT-distance–whichdecreaseslenderdifferentiation–mayormaynotbenefitsocialwelfareowingtotheconsequentincreasedlendercompe-tition.IT-distanceprogresswillbemorelikelytoreducesocialwelfarewhenentrepreneurs’moralhazardproblemismoreseverebecausetheneedformonitoringwillincreaseinthiscase,makinglenders’monitor-ingincentivesmorecrucial.Incontrast,improvinglenders’IT-basichasnodifferentiationeffectandhenceimproveswelfareunambiguously.

Fromthesocialpointofview,thewelfare-maximizingloanratedoesnotdependonlenders’IT.Thisraterepresentsthesociallyoptimalwaytosharetheprojectvaluebetweenanentrepreneurandherlender.Althoughalender’sITdeterminesthevalueofaprojectitfinances(i.e.,thesizeofthepie),thewelfare-maximizingwaytosharethepiemustbalancetheseverityoftheentrepreneur’smoralhazardandthelender’smonitoringincentive,whichisatrade-offindependentofthelender’sIT.Theimplicationisthatlenders’pricediscriminationwillgenerateinefficientequilibriumoutcomes:Alenderwillpriceaggressivelyatfar-awaylocations–wherethelender’sITadvantageislow–togainasmuchbusinessaspossiblewhileatlocationsclosetothelender’sareaofspecializationitwillpriceveryhightoexploititshighITadvantage.Suchastrategydoesnotbalancetheseverityofmoralhazardswellwiththelender’smonitoringincentiveateachlocation.Regulatorscanimprovewelfarebysettingaproperreferenceloanrateforlendersandlimitingtheirabilitytopricediscriminate.

Relatedliterature.Ourworkbuildsonthespatialcompetitionmod-elsof

Hotelling

(

1929

)and

ThisseandVives

(

1988

)butfocusesonlenders’competitiontofinanceentrepreneurs’projects.

Villas-Boasand

Schmidt-Mohr

(

1999

)buildaspatialmodelstudyinghowlendingcom-petitionaffectsthecollateralrequirementsofbankcontracts.Severalpapershaveemphasizedtheimportanceofmonitoringinlending.

7

Almazan

(

2002

)studieshowlendercapitalization,interestrates,and

7See,e.g.,

Diamond

(1984

)and

HolmstromandTirole

(1997

)forpioneeringwork.

regulatoryshocksaffectmonitoringefficiencyinaspatialcompeti-tionmodelwherelendershavenomarketpoweroverentrepreneurs.

Martinez-MieraandRepullo

(

2019

)examinetheeffectivenessofmon-etaryandmacroprudentialpoliciesinaddressingafinancialsystem’sriskswithinaframeworkwherelendermonitoringcanincreasetheprobabilitythatinvestinginanentrepreneuryieldsapositivereturn.

8

Differentfromtheaforementionedpapers,ourmodelfocusesonhowdifferenttypesofITprogress(IT-basicv.s.IT-distance)generatedif-ferenteffectsonlenders’monitoring,marketpower,entrepreneurs’investment,andwelfare.

Ourpaperalsobelongstotheliteraturestudyinginformationtech-nologyandlendingcompetition.

HauswaldandMarquez

(

2006

)extendtheadverseselectionmodelin

HauswaldandMarquez

(

2003

)andshowthattheequilibriumloanratesreceivedbyborrowersaredecreasinginthelender–borrowerdistanceandintheintensityoflendercom-petition(measuredbythenumberoflenders),similartoourmodelprediction.However,ourmodelbuildsonadifferentmechanism–entrepreneurs’moralhazardandlendermonitoring(asin

Holmstrom

andTirole

,

1997

)–andweanalyzetherelationshipbetweentheseverityofentrepreneurs’moralhazardandtheequilibriumeffectsofITprogress.Furthermore,ourresultsdifferfromthoseof

Hauswald

andMarquez

(

2006

),inwhichanimprovementinthelendingsector’sITwillsoftenlendercompetition,andsocialwelfareincreasesintheintensityoflendercompetitionifcompetitionisalreadyveryintense.Incontrast,wefindthatlendercompetitioniseitherintensifiedorunaffectedbythelendingsector’sITimprovements,dependingonthetypeofimprovedIT,andthatsocialwelfaredecreasesintheintensityoflendercompetitionifcompetitionisveryintense.

Inamodelwhereatraditionalbankandafintechlendercompetetoextendloans,

Heetal.

(

2023

)analyzetheeffectsof‘‘openbanking’’–aninformationsharingmechanismthatenablesborrowerstosharetheircustomerdatastoredinabankwithafintechthathasadvancedinformationprocessingtechnologybutlessaccesstocustomerdata.Theyfindthatopenbankingincreasesthefintech’sscreeningabilitybutthatitcansoftenlendingcompetitionandhurtborrowersifthefintechis‘‘over-empowered’’bythedatasharingmechanism.Ourworkhasadifferentfocus:wedistinguishtwotypesofinformationtechnologyandcomparetheirdifferentequilibriumconsequences.Inaddition,weshowthatonelender’sITprogressandtheentirelendingsector’sITprogressgeneratequitedifferentequilibriumoutcomes.

Ourtheoreticalframeworkisrelevanttotheempiricalliteratureoninformationtechnologyadoptioninthelendingmarket,whichhasthrivedowingtotheriseofFinTechinrecentyears.

9

Tostartwith,thereisconsiderableevidenceshowingthatITmakesnon-traditionaldatausefulforassessingthequalityofborrowers.

10

Moreover,awidestreamofresearchdocumentsthelendingefficiencyincreasebrought

8

Bouvardetal.

(2022

)studylendingandmonitoringinamarketwhereabigtechandcompetitivebankscanprovideloansandmonitorentrepreneurs.Inadditiontoprovidingloans,thebigtechitselfisamonopolisticplatformchargingparticipationfeesfromentrepreneurs(i.e.,merchants).

9

Philippon

(2016

)claimsthattheexistingfinancialsystem’sinefficiencycanexplaintheemergenceofnewentrantsthatbringnoveltechnologytothesector.

GopalandSchnabl

(2022

)showthatmostoftheincreaseinfintechlendingtoSMEsafterthe2008financialcrisissubstitutedforabanklendingreduction.

10Thenon-traditionaldataincludesoftinformation

(Iyeretal.

,

2016

),friendshipsandsocialnetworks

(Linetal.

,

2013

),applicants’descriptiontext

(Dorfleitneretal.

,

2016

;

Gaoetal.

,

2023

;

Netzeretal.

,

2019

),contractterms

(Kawaietal.

,

2022

;

Hertzbergetal.

,

2018

),mobilephonecallrecords

(Bj?rkegrenandGrissen

,

2020

),digitalfootprints

(Agarwaletal.

,

2023

;

Berg

etal.

,

2020

),andcashlesspaymentinformation

(Ghoshetal.

,

2022

;

Ouyang

,

2023

).

4

X.VivesandZ.YeJournalofFinancialEconomics163(2025)103957

Fig.1.Theeconomy.

aboutbyinformationtechnology.

11

Severalpapersprovideevidenceconsistentwithourresults.

Branzolietal.

(

2024

)and

Dadoukisetal.

(

2021

)findthatbankswithhigherITadoptionhavelargerloangrowth;thisisconsistentwithourfindingthatanimprovementofalender’sITincreasesitslendingvolume.

D’Andreaetal.

(

2021

)findthatbroad-bandinternetimplementationintensifiesbankcompetitionandreducesbanks’loanprices,whichisconsistentwiththeeffectofIT-distanceprogressinourmodel.

Ahnertetal.

(

2024

)documentthatsmallbusinesslendingbybankswithhigherITadoptionislessaffectedbythedistancebetweenthebankheadquartersandtheirborrowers.Ourmodelalignswiththisfinding.

Ahnertetal.

(

2024

)alsofindthatjobcreationbyyoungenterprises,aproxyforentrepreneurship,isstrongerinUScountiesthataremoreexposedtoIT-intensivebanks;consistentwiththisfinding,ourmodelshowsthatIT-basicprogressinthelendingsectorspurscreditsupplyandentrepreneurialinvestment.However,IT-distanceprogressintensifieslendercompetition,soitseffectonlenders’creditsupplyishump-shaped,whichisconsistentwith

DiPattiand

Dell’Ariccia

(

2004

).

12

Therestofourpaperproceedsasfollows.Section

2

presentsthemodelsetup.Section

3

examinesthelendingmarketequilibrium,andSection

4

examinestheeffectsofinformationtechnology.Section

5

providesawelfareanalysisofinformationtechnologyprogress.WeconcludeinSection

6

withasummaryofourfindings.

Appendix

A

presentstheproofswhileotherappendicesdealwithmodelextensions.

2.Themodel

Theeconomyandplayers.Theeconomyisrepresentedbyalinear‘‘city’’,oflength1,thatisinhabitedbyentrepreneursandlenders.Ateachlocation,thereisonepennilessentrepreneur.Apointonthecityrepresentsthecharacteristicsoftheentrepreneur(typeofproject,technology,geographicalposition,industry,...)atthislocation,andtwoclosepointsmeanthattheentrepreneursinthoselocationsaresimilar.

Therearetwolenders,labeledbyi∈{1,2},locatedatthetwoextremesofthecity.Hence,alenderisclosertosomeentrepreneursthantoothers.Thismeans,forexample,thatlendersarespecializedindifferentsectorsoftheeconomy(see

Paravisinietal.

,

2023

forexport-relatedlending,

Duquerroyetal.

,

2022

forSMElendingand

Giometti

11Buchaketal.(2018)findthatlenderswithadvancedtechnologycan

offermoreconvenientservicestoborrowersandhencechargehigherloan

ratesintheU