SME Loan Decision Making Process: A Declining Role of Human Capital

1. SME Loan Decision Making Process: A Declining Role of Human Capital NATIONAL CHENG KUNG UNIVERSITY – INSTITUTE OF CREATIVE INDUSTRY DESIGN Ottavia, Shao-Chi Chang Ph.D., Ding-Bang Luh Ph.D.

2. Agenda • Quick Review • Background & Motivation • Model & Hypotheses • Method used • Results & Discussion • Conclusion & Suggestions • Q & A APMC

3. Background & Motivation • Loan: the biggest contributor in bank income (Golin, 2001) • 51.81% of bank income (Indonesian bank statistics, 2008) • Business vs. Risk • Wrong decision affects bank’s financial performance & reputation (Coleshaw, 1989) • Human factor in decision making process (Coleshaw, 1989, Van Buren, 1999) About Loan

4. Research Objectives • Borrower’s attributes vs. loan approval • Human capital’s influence in decision • Are there priorities? The Expected Outcomes

5. Research Model & Hypotheses M1 M2 M3 M4 • Hypotheses • Positive relationships (H1 - H5): • Borrower’s attributes vs. loan approval • Human capital’s influence (H6): • Different judgments on attributes H6, H7 H1, H2, H3, H4, H5 X1 X2 X3 X4 X5 The Basic Model

6. Methodology • Survey: • Target: Bank loan officers • Location: Indonesia • Metric conjoint experiment • 5 attributes • 2 levels: high & low • Scenarios: 10 hypothetical companies • Approval rate (scale 1 – 7)

7. The results: 291 respondents • 291 responses: • 255 on-the-spot • 36 by email • 59 not returned Demography Human Capital 15 branches 3 credit HQ Descriptive Data Analysis

8. Borrower’s Attributes & Loan Approval High High High High High • Results: • When attributes are low, the utility value is negative • When attributes are high, the utility value is positive • Positive relationships between borrower’s attributes & loan approval • Hypotheses H1 – H5 are proven Low Low Low Low Low COL REL SIZE EXP SHARE Conjoint Analysis Result (1/3)

9. The Importance Values In their own words “The most important thing is business experience. It reflects the capacity of applicants; how well he/she can manage the company and cope with the nature of the business. The longer one survives; the better one’s capacity is to run the business.” S. D. Analyst - Jakarta branch 13 years in credit REL COL SIZE EXP SHARE Conjoint Analysis Result (2/3)

10. The Least of All – Firm size In their own words “Size actually is not what matter most; as long as the business can make profit that is enough to repay the loan, why not?” M. S. Marketing - Bali branch 10 years in credit REL COL SIZE EXP SHARE Conjoint Analysis Result (3/3)

11. The Influence of Human Capital • Human capital factors have affect on the judgment over share of investment (except banking experience) • H6 is partially proven. One-way ANOVA (1/2)

12. More on Human Capital • Share of investment: • The higher the education, loan officer’s value toward share of investment decreases • Same tendencies on lending experience & exposure to SME • Bank experience – not influential? In their own words “I was an administration staff for 6 years before I started working as a loan officer 3 years ago. I don’t think it helped meunderstand the concept about credit at all. I got the grasp after attending several credit trainings,on-the-job training for two months and doing the real job.” E. H. Marketing - Surabaya branch 3 years in credit One-way ANOVA (2/2)

13. Human Capital: not as influential? • The transition from manual to computerized system • Traditional/ expert system: relies heavily on the expertise, subjective judgment, and weighting on borrower’s attributes by loan officers (Saunders & Allen, 2002) • Computerized system: more uniformed decision, based on more clear & rigid regulations. Automatically generate risk ratings(Saunders & Allen, 2002). Less room for subjective judgment. • Human factor’s role decreases in SME decision-making process Discussions

14. Research Contribution • Borrower’s attributes have positive relationship to the likelihood of loan approval • Reevaluate the result • Bank’s criteria in credit analysis • Create supporting analytical tools • Human capital: decreasing role • SME department – novice/ lower levels • High level of human capital – relocated for optimal utilization research Banking industry For academic and banking industry

15. Research Limitations • Actual settings cannot be fully represented • Simplified cases (5 attributes) • Loan officers were “forced” to plainly accept & make decisions • Universal basic theory vs. country-specific context • Hawthorne effect • Awareness of being the subjects in research(Robbins & Judge, 2007) • Possibility of different decisions in real setting Constraints & Limitations

16. Future Research • Different loan categories • Size: commercial & corporate loans • Usage: working capital vs. consumption • Link with default rate & credit profit • Compare manual & computerized system • Best composition – effective & efficient • Types of banks: • Commercial vs. state-owned • Local vs. foreign • Non-bank financial institutions • Cross-cultural studies Suggestions

17. Q & A