Bank culture and risky lending Linh Nguyen (University of St Andrews) Louis Nguyen (University of St Andrews) Ben Sila (University of Edinburgh) Conference on Professional and Ethical Standards in Banking May 2016
Motivation • Key economic features of the past decade: • Reckless bank behavior • Unprecedented wave of bailouts and failures around the world • “Bank culture ” – the source of all evils • Research question: does bank culture affects financial stability? • Via credit decisions • A core business function of banks • Require human discretion
What do we fi find? • Bank culture affects financial stability via bank lending behavior • Banks with compete-oriented culture are more likely to lend to sub-investment borrowers, require fewer covenants and ask for a higher loan spread. • They enjoy extraordinarily fast lending growth at the expense of more bad loans. As a result, they make greater contribution to systemic risk. • Compete-banks behave like a slow-exploding bomb • They make most contribution to systemic risk during boom time and only realize losses (bad loans) during bust time.
How do we measure corporate culture?
Corporate cult lture used in in previous lit literature 1. Management scholars conduct case studies on a few selected companies • Only captures some, but not all aspects of culture • Temporary • Generalization issue 2. Recent work in finance and economics use annual rankings of companies (“Best companies to work for”) or company surveys (“Glassdoor”) • Limited to a subset of very large firms • Firms pay to do surveys self-selection issues
Our approach to capture corporate cult lture • Textual analysis of company’s annual reports • First used introduced to the finance literature by Fiordelisi and Ricci (2014) • Assumption: Language mirrors values and culture • Classifies into four major dimensions • Compete: “compete hard, move fast, and play to win” • Create: “ create, innovate, and envision the future ” • Control: “ better, cheaper, and surer ” • Collaborate: “development , empowerment, commitment” Create and Compete External, outward-looking Control and Collaborate Internal, inward-looking
Bag of f words Culture type Bag of words Control capab*, collectiv*, commit*, competenc*, conflict*, consens*, control*, coordin*, cultur*, decentr*, employ*, empower*, engag*, expectat*, facilitator*, hir*, interpers*, involv*, life*, long-term*, loyal*, mentor*, monit*, mutual*, norm*, parent*, partic*, procedur*, productiv*, retain*, reten*, skill*, social*,tension*, value* Compete achiev*, acqui*, aggress*, agreem*, attack*, budget*, challeng*, charg*, client*, compet*, customer*, deliver*, direct*, driv*, excellen*, expand*, fast*, goal*, growth*, hard*, invest*, market*, mov*, outsourc*, performanc*, position*, pressur*, profit*, rapid*, reputation, result*, revenue*, satisf*, scan*, succes* signal*, speed*, strong, superior, target*, win* Collaborate boss*, burocr*, cautio*, cohes*, certain*, chief*, collab*, conservat*, cooperat*, detail*, document*, efficien*, error*, fail*, help*, human*, inform*, logic*, method*, outcom*, partner*, people*, predictab*, relation*, qualit*, regular*, solv*, share*, standard*, team*, teamwork*, train*, uniform*, work group* Create adapt*, begin*, chang*, creat*, discontin*, dream*, elabor*, entrepre*, envis*, experim*, fantas*, freedom*, futur*, idea*, init*, innovat*, intellec*, learn*, new*, origin*, pioneer*, predict*, radic*, risk*, start*, thought*, trend*, unafra*, ventur*, vision*
Dominating ti time-invariant corporate cult lture In 2002, JPMorgan has 1145 (=3.11%) Compete-related, 451 (=0.75%) Create- related, 811 (=1.11%) Control-related and 433 (=0.25%) Collaborate-related words. • These scores are meaningless • Subjected to company-specific or industry-specific variations in 2002 • Or simply, what does a Compete=3.11% mean? • We convert these scores into measures of “ dominating culture ” by comparing with peer firms • JPMorgan is said to have a compete-dominated culture if its Compete score =3.11% is in the top 25% score of all banks in 2002. • Although rare, a bank can have more than one or zero dominating culture.
Data and sample Data • All loans made by US lenders to US borrowers 1993-2007 from Dealscan • Hand-clean lenders and match to Calls Report Data for bank characteristics • Borrower data are collected from Compustat Final sample: • 30,000+ loan-level observations and 600+ bank-level observations
Empirical specification Pr( risky lending it ) = α 0 + α 1 compete-dominant i + α 2 create-dominant i + α 3 control-dominant i + α 4 collaborate-dominant i + controls + ε itk • Risky lending = Equals 1 if borrower is unrated or has a BB+ and below credit ratings • Controls: Bank, Borrower, Loan, Relationship lending, Same-culture indicator • Fixed-effects: Year, Industry, State, Loan Purpose, Loan Type
Risky le lending Dependent variable: Dummy equals 1 for unrated borrowers or those rated BB+ or worse (1) (2) (3) (4) (5) Compete-dominant 0.076*** 0.078*** (2.630) (2.638) Create-dominant -0.008 0.014 (-0.345) (0.626) Control-dominant -0.174** -0.171** (-2.131) (-2.040) Collaborate-dominant 0.017 0.048 (0.454) (1.217) [control variables omitted from tables] Year dummies Yes Yes Yes Yes Yes Borrower sic-2 dummies Yes Yes Yes Yes Yes Borrower state dummies Yes Yes Yes Yes Yes Observations 38,875 38,875 38,875 38,875 38,875 Pseudo- R 2 0.491 0.491 0.491 0.491 0.491
Risky le lending Dependent variable: Dummy equals 1 for unrated borrowers or those rated BB+ or worse (1) (2) (3) (4) (5) Compete-dominant 0.076*** 0.078*** (2.630) (2.638) Create-dominant -0.008 0.014 (-0.345) (0.626) Control-dominant -0.174** -0.171** (-2.131) (-2.040) Collaborate-dominant 0.017 0.048 (0.454) (1.217) [control variables omitted from tables] Year dummies Yes Yes Yes Yes Yes Borrower sic-2 dummies Yes Yes Yes Yes Yes Borrower state dummies Yes Yes Yes Yes Yes Observations 38,875 38,875 38,875 38,875 38,875 Pseudo- R 2 0.491 0.491 0.491 0.491 0.491
Robustness • Alternative cut-off points: results vary consistently with the notion of “dominating culture” • Excluding top 10 (“TBTF”) lenders • Sample restricted to rated-only borrowers • Remove years immediately after mergers • Alternative standard-error clustering • Additional location and loan controls
Endogenous le lender-borrower matching • Borrowers do not randomly choose lenders • We indeed find that borrower-lender has a corporate culture match, e.g., compete borrowers are more likely to obtain loans from compete banks • This is a part of rather an alternative interpretation. • That riskier borrowers approach riskier lenders suggest they are aware of the “reckless reputation” of the banks • There are other endogeneity concerns
Id Identifi fication: Russian Default Crisis • An exogenous shock that produces a short-term negative sentiment to the competitive culture of US banks and thus affects its lending behaviour. • Plausibly exogenous to omitted factors such as credit demands of US borrowers or borrower-lender matching. • Event: The Russian Government defaulted their sovereign debt obligations on 17 th August 1998, causing losses to exposed US banks, putting the entire US banking industry under distress. • Chava and Purnanandam (2011) show that borrowers whose lenders affected by the Russian crisis cut CAPEX and suffer valuation loss.
Id Identifi fication: Russian Default Crisis (1) (2) (3) (4) 3-month 4-month 5-month Placebo event 1 y prior to August 1 Compete-dominant * Post Russian default -0.085** -0.087** -0.086** 0.004 (-2.204) (-2.091) (-2.124) (0.097) Create-dominant * Post Russian default -0.016 -0.027 -0.030 -0.062 (-0.346) (-0.619) (-0.685) (-1.505) Control-dominant * Post Russian default -0.066 -0.091 -0.089 0.101 (-0.498) (-0.692) (-0.711) (0.635) Collaborate-dominant * Post Russian default 0.041 0.046 0.054 0.005 (0.699) (0.828) (1.050) (0.080) [control variables omitted from tables] Year dummies Yes Yes Yes Yes Borrower sic-2 dummies Yes Yes Yes Yes Borrower state dummies Yes Yes Yes Yes Observations 1,198 1,582 2,003 54,195 Pseudo- R 2 0.703 0.641 0.604 0.491
Loan terms Lo Dependent Variable = Covenants Dependent Variable = Ln(Spread) Full Sub- Investment Full sample Sub-investment Investment sample investment grade grade (1) (2) (3) (4) (5) (6) Compete-dominant -0.041** -0.055*** 0.021 0.045*** 0.029*** -0.002 (-2.513) (-2.777) (1.097) (3.991) (2.916) (-0.117) Create-dominant -0.096*** -0.106*** -0.001 0.047*** 0.053*** -0.020 (-6.215) (-5.514) (-0.085) (4.617) (5.430) (-1.617) Control-dominant 0.208*** 0.224*** 0.094* 0.011 0.104** -0.096* (3.319) (2.719) (1.782) (0.248) (2.369) (-1.695) Collaborate-dominant 0.060*** 0.066*** 0.009 0.012 -0.004 0.029 (3.032) (2.919) (0.328) (0.985) (-0.394) (1.574) [control variables omitted from tables] Year dummies Yes Yes Yes Yes Yes Yes Borrower sic-2 dummies Yes Yes Yes Yes Yes Yes Borrower state dummies Yes Yes Yes Yes Yes Yes Observations 30,877 23,080 7,797 30,877 23,080 7,797 Pseudo- R2 0.376 0.266 0.431 0.491 0.529 0.556
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