Distance and Information Asymmetries in Lending Decisions

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Distance and Information Asymmetries in Lending
Decisions

• Sumit Agarwal
• Federal Reserve Bank of Chicago
• Robert Hauswald
• American University
• FDIC-CFR Fall Workshop
• Washington, DC, October 2006
• The views do not represent those of the Federal
  Reserve Bank of Chicago.

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Motivation

• Information drives financial intermediation but
• anecdotal and recent empirical evidence suggest
  that other factors might be important geographic
  distance
• changing geography banks lend over longer
  distances while also contesting local markets
  more vigorously
• Current work on distance in lending is
  inconclusive
• what is the economic role of borrower proximity?
• nature of discrimination in credit pricing and
  availability
• how does information production affect credit
  markets?
• There exists a large theoretical literature but
  little empirical evidence on bank-borrower
  interaction

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Results

• Loan rates and the likelihood of granting credit
• decrease (increase) in firm bank (competitor)
  distance
• consistent with both informational and spatial
  models
• However, once we include a proxy for the banks
  private information the effects become
  insignificant
• strong evidence distance is a proxy for private
  information
• Higher rate or credit score, or more distant
  applicant more likely to decline loan offer and
  to switch lender
• consistent with informational capture rent
  extraction
• evidence in favor of asymmetric-information
  models
• Does the banks type II error increases in
  distance?

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Related Literature

• Petersen and Rajan (2002) NSSBF survey
• local-information hypothesis the soft
  information crucial in this market borrower
  proximity matters for risk assessment
• find increase in bank-borrower distance
  technology presumably allows banks to overcome
  rising risks outside local core markets
• Degryse and Ongena (2005) Belgian loan data
• loan rates decrease (increase) in distance to
  bank (competitor)
• relationship variables insignificant
  transportation costs seem to play a large(r) role
  in Belgian loan transaction (economic geography?)
• Hauswald and Marquez (2006) quality of banks
  information decreases in distance between bank
  and loan applicant
• adverse selection constrains competition (captive
  markets) loan rates (competition) decrease
  (increases) in firm-bank distance
• same prediction as transportation-cost models no
  pricing-based test
• ) use declined loan offers to test the
  different model classes

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Unique Sample

• All 28,761 new loan applications by small
  businesses to a major US financial institution
  from 01/02 to 04/03
• sole proprietorships and small firms SME lending
  as defined by Basel I accord (total obligation lt
  1m and sales lt 10m)
• collect branch and applicants address, financial
  information, credit-bureau reports, credit
  decision, terms of loan offer
• internal credit score proxy for private
  information, contains subjective input by local
  branches through adjustments
• Using Yahoo!SmartView and Yahoo!Maps we identify
• banks closest competitors BellSouth, InfoUSA
  yellow pages
• driving distances in miles and minutes, aerial
  distances
• Leaves 25,744 observations with full data
  availability
• remove 257 obs with distances gt 255 m nonlocal
  lending

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Key Variables by Bank Decision
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The Banks Lending Decision

• Logistic discrete-choice model of the banks
  decision to offer or deny credit in terms of
• physical distances firm to bank and to nearest
  competitor
• information relationship intensity, public
  information, with or without proprietary-informati
  on proxy, interaction terms
• control variables loan terms, quarter (cycle),
  states, 2-digit SIC, UST yields and yield curve,
  house prices
• Linear regression model of the offered loans
  annual percentage rate (APR all-in cost) same
  variables
• Loan offers or booked loans ) sample-selection
  bias
• re-estimate model with the Heckman Correction to
  account for the banks prior decision to grant or
  refuse credit but
• inclusion of score sufficiently corrects for
  selectivity issues

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Availability and Pricing of Credit

• Competition under asymmetric information
  trade-off
• proximity to bank facilitates access to credit,
  but at the cost of locational price
  discrimination client pays for information?
• information clearly matters time in business and
  intensity of lending relationship reduce
  (increase) APR (credit availability)
• Distance is a proxy for private information and
  its quality consistent with the
  local-information hypothesis
• with credit score, distance becomes insignificant
  for APR but still matters (albeit less) for the
  decision to grant credit
• the smaller the distance, the less the score
  reduces the APR
• ) private information contained in the score
  leads to the (attempt of) informational capture
  of good credit risks matches theory

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Banks Decision to Offer CreditLogistic
Discrete-Choice Model
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APR Determinants OLS Regression
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Accepting or Declining Loan Offers

• Asymmetric information ) adverse selection )
  informational capture an applicant is more
  likely to decline an offer
• the closer the firm is to the bank, the higher
  the loan-rate rent extraction
• the higher the credit score better borrowers
  more likely to switch lenders
• HM (2006) local-information advantage implies
  lender switching
• Analyze an applicants decision to accept the
  offered loan
• 891 applicants declined loan offer (¼ 3 of
  approved applications)
• credit-bureau information around loan offer date
  indicates alternative sources of credit firm
  presumably switched lenders
• Estimate logistic discrete-choice model of
  applicants decision
• clean test of asymmetric-information vs.
  transportation cost models
• rejecting offers affects loan-portfolio quality
  who switches lenders?

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Declined Loan Offers

• The probability to decline a loan offer
• increases in score, loan rates (APR) and in
  firm-bank distance
• the greater the firm-bank distance the more it
  increases in score
• is decreases in firm-competitor distance
• Results consistent with the attempt of
  informational capture inducing applicants to
  switch lenders
• as distance erodes informational advantage of
  informed bank borrowers further away are more
  likely to get competing offers
• consistent with results in HM (2006) local
  information matters to deter competition for
  core-market applicants
• Better borrowers more likely to switch portfolio
  effect

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Borrowers Decision to Decline Offer
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The Local-Information Hypothesis

• If relevant (soft) borrower information is truly
  local
• the banks information advantage should diminish
  with firm-bank distance firm-competitor distance
  irrelevant
• empirical prediction errors in lending (type II
  error) should increase with distance ceteris
  paribus
• To test this hypothesis we specify a logistic
  model of credit delinquency in terms of our usual
  variables
• 322 loans 60 days overdue (out of 12,005 booked
  loans ¼ 2.7 default rate) within 18M of
  origination
• internal definition of defaulted loan requiring
  action over 90 of such loans eventually
  experience default

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Type II Error in Lending

• The further away the borrower, the more likely
  credit delinquency (i.e., default) becomes (De
  Young et. al. find similar results - SBA loans).
• private and public information variables reduce
  likelihood of loan becoming nonperforming value
  of information
• Unsurprisingly, the internal credit score is the
  most important variable for predicting credit
  delinquency
• shows how technology can overcome distance
  problems
• the further away, the less a high score reduces
  default probability information discounted in
  terms of distance
• Results provide strong evidence for
• the local nature of soft information on loan
  applicants
• screening specification in HM (2006) screening
  quality of (type II error in) lending falls
  (rises) with distance

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Type II Error in Lending Default
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The Nature of Soft Information and the Effect of
Competition

• Relationship content of credit assessments
  interact the score and lending-relationship
  variables
• relationship variables increase the scores
  marginal effect in all specifications
  improvement in risk assessment
• soft information is (i) local, (ii) gathered over
  time
• partial hardening of soft information through
  technology
• The incidence of industry structure number of
  branches or competitors, HHI for deposit shares
• more competition reduces both loan offers and
  rates
• again, trade-off between pricing and availability
  of credit

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Conclusion

• We investigate the dual hypotheses that
• private information is local and implies an
• informational advantage to deter competition
• Technology increases the reach of local
  information banks harden soft proprietary
  information
• to extend the geographic reach of their markets
  by overcoming threats of adverse selection due to
  distance
• Hence, distance still limits the size of local
  markets
• bank discounts own intelligence in function of
  distance that acts as a proxy for the quality of
  information

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