The recent internationalization trend among Japanese regional banks is a topic of interest for researchers in the context of regional bank growth strategy. This paper examines the factors that explain the lending behavior of regional banks in the international syndicated loan market during the period from 2009 to 2014. Through a comparative analysis and probit model using data from 10,717 transactions, it is found that regional banks prefer to participate in syndicated loans of lower amounts. The denomination of loans in Japanese yen is the most important factor in increasing the probability that regional banks will participate in these loans. The second most important consideration in explaining the lending behavior of regional banks relates to the characteristics of the borrowers. Regional banks prefer Asian borrowers that are in the financial services industry. Risk-taking and funding capacities can explain the characteristics of regional banks.

1. Participation of Japanese regional Banks in
International Syndicated Loans: Lending
behavior and explanatory factors
Masaki YAMAGUCHI
Yamagata University
Annual Tokyo Business Research Conference,
Waseda University, 15-16 December, 2014

2. Motivation
• Hot issue – international syndicated loans
• Gunma Bank – 10 billion yen buildup by the end of FY2013
• Hyakugo Bank – 55 billion yen buildup by the end of FY2015
• Chiba Bank – 20% increase of foreign currency loans by the end of FY2017
• Growth strategies of regional banks
• Loan demand cannot be expected to increase amid fierce competition in
shrinking regional economies
• Participation in syndicated loans could serve as a new source of profits for
regional banks

3. Research Questions
1. Characteristics of deals that regional banks
participated?
2. Factors which enhance regional banks’
participation ?

4. Questions
Motivation
Related literature
Analysis 1 Analysis２
Result１ Result２

5. Related literature
• Type 1： Decision of syndication
• Influencing factors on decision whether set up a syndicate or not
• binary-choice model, Syndicate = F (Information, Agency, Loan term)
• Dennis and Mullineaux (2000), Godlewski and Weil (2008)
• Type2: Size of a syndicate
• what factors affect the syndicate structure
• count data model, Size = F (Opaque, Loan Characteristics)
• Lee and Mullineaux (2004) , Sufi (2007)

6. Related literature
• Type 3 : Difference in lending behavior
• Difference between bank types
• Model; Spread = F (loan terms, bank types)
• Haselmann and Wachtel (2011), Harjoto, Mullineaux, and Yi (2006)
• Position of this study
• close to the first type
• different in research object ; regional banks

7. Data Source
• Thomson Reuter – DealScan: Loan Database
• Sample: 10,907 deals, Japanese banks participated
• Period: 2009 – Sep. 2014
• Location: All over the world
Japanese banks
Regional banks

8. League Table: 2009 – Sep. 2014
Bank Name
Number of
Deals
Bank Name
Number of
Deals
Bank Name
Number of
Deals
Chiba 80 Fukuoka 4 Kinki Osaka 1
Hachijuni 32 Oita 3 Hokkoku 1
Yamaguchi 26 Hyakujushi 3 Fukui 1
Chugoku 24 Ogaki Kyoritsu 3 Kyoto 1
Shizuoka 18 Tsukuba 3 Hokuto 1
Gunma 16 Akita 3 Shonai 1
Yokohama 12 Higashi-Nippon 2 Michinoku 1
Hiroshima 12 Toho 2 Nishi-Nippon 1
Minato 12 Joyo 2 Aomori 1
Iyo 5 Higo 2 Shiga 1
77 5 Daishi 1 Ashikaga 1
Hyakugo 4 Dasan 1 Keiyo 1

9. Borrower Country
Borrower
country
Number of
Deals
Borrower
country
Number of
Deals
USA 61 UK 5
Korea 17 Vietnam 4
China 12 Sweden 3
India 12 Chile 2
Panama 11 Malaysia 1
HK 10 UAE 1
Thailand 9 Cayman 1
Indonesia 9 Netherland 1
Singapore 8 Brazil 1
Australia 7 Belgium 1
Liberia 6 Canada 1
Mexico 5 Philippines 1
・US takes the top borrower nationality
・83 borrowers from Asian countries
Hypothesis 1: Asian nationality
enhances the possibility of regional
banks participation
Geographical proximity reduces
information asymmetry

10. Currency
Currency
Number of
Deals
Percentage
USD 108 57.1
JPY 61 32.3
CNY 5 2.6
HKD 4 2.1
US Equiv 4 2.1
AUD 3 1.6
Multi 2 1.1
CAD 1 0.5
Euro 1 0.5
・Large share of USD can be partly
explained by the borrower nationality
・Hypothesis 2: regional banks prefer to
syndicated loans denominated in JPY
Most regional banks have difficulty with
funding USD

11. Purpose
Purpose
Number of
Deals
Percentage
Corporate purposes 81 42.9
Working capital 43 22.8
Debt Repay 21 11.1
Ship finance 15 7.9
Capital expend 13 6.9
Project finance 6 3.2
CP backup 3 1.6
Takeover 3 1.6
Equip. Purch. 2 1.1
Aircraft 1 0.5
Security Purchase 1 0.5
・Top three loan purposes account for
76.8%
・Capital expenditures, project financing,
equipment purchases….
difficult to measure the success and
failure of long-term projects
・Hypothesis 3: Regional banks avoid
taking on such risks

12. Analysis 1 :Comparison
Participation Non-Participation
Means Sample Means Sample
Loan Size (millions) 355 189 679 10717 0.00
Maturity (years) 4.98 187 4.59 10471 0.04
Number of lenders 10.8 189 11.5 10703 0.00
Regional Bank Regional Bank
U test
Regional banks prefer smaller loans

13. Participation N on-Participation
N Ratio (%) N Ratio(%)
0 128 10617
1 61 101
0 81 2942
1 108 7776
0 146 10119
1 43 599
0 108 4789
1 81 5929
0 95 5204
1 94 5514
0 162 9686
1 27 1032
0 108 9578
1 81 1140
0 120 9735
1 69 983
RegionalB ank RegionalB ank
χ2
test
JPY 32.3 0.9 0.00
U SD 57.1 72.6 0.00
W orking C apital 22.8 5.6 0.00
C orp.Purpose 42.9 55.3 0.00
Rating 49.7 51.4 0.64
Financial 36.5 0.0 0.00
G uarantor 14.3 9.6 0.03
Asia 42.9 10.6 0.00

14. Analysis 2: Probit model
Expalined variable Explanatory variables
Regional banks’ participation ← - Loan Character
1 or 0 log(amount), maturity, rating
currency, guarantor
- Loan Purpose
working capital, corp. purpose
- Borrower Character
country, industry

15. M odel1 M odel2 M odel3 M odel4 M odel5
LAO M O U N T -0.123**
-0.123**
-0.124**
-0.084**
-0.082**
(0.026) (0.026) (0.026) (0.028) (0.029)
M ATU RITY -0.003 0.009 0.008 0.013 0.031**
(0.011) (0.011) (0.011) (0.011) (0.011)
RATE 0.155*
0.144 0.161*
0.300**
0.217**
(0.073) (0.074) (0.075) (0.081) (0.083)
JPY 1.924**
1.844**
1.864**
1.847**
1.835**
(0.115) (0.116) (0.117) (0.118) (0.12)
N U M B ER 0.013**
0.015**
0.015**
0.013**
0.014**
(0.003) (0.003) (0.003) (0.003) (0.003)
C O RP. -0.072
(0.068)
W O RKIN G 0.525**
0.503**
0.434**
0.407**
(0.097) (0.097) (0.099) (0.102)
G U ARAN TO R 0.197**
0.006
(0.096) (0.103)
ASIA 0.754**
0.663**
(0.081) (0.083)
FIN AN C IAL 0.624**
(0.083)
C O N ST -0.072 -0.222 -0.233 -1.230*
-1.423**
(0.482) (0.483) (0.483) (0.527) (0.552)
Sam ple 10643 10643 10643 10643 10643
Pseudo R 2 0.173 0.187 0.189 0.233 0.264

16. Summary of results
• Smaller loans, JPY preference ← funding problem for foreign currencies
• WORKING ← lower risk of project
• ASIA, RATE ← smaller information asymmetry
• Financial ← implicit guarantee
• IFRS Bank ← human resources for overseas transactions

17. Explanatory variable Marginal effect Explanatory variable Marginal effect
LAOMOUNT -0.001 NUMBER 0.000
MATURITY 0.001 WORKING 0.014
RATE 0.004 ASIA 0.027
JPY 0.262 FINANCIAL 0.024
・JPY produces the greatest effect on the probability of
participation
・ASIA and FINANCIAL have the next strongest marginal
effects