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This paper discusses the theoretical framework and practical issues related to bank credit assessments, focusing on lending officers' evaluations of loan applications from small/medium-sized enterprises. It explores the factors considered in credit assessments and presents a repertory grid approach as a method for analyzing data. The study also reports on the pilot testing of methods and assesses their feasibility.
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RECONSIDERATION OF THE BANK CREDIT ASSESSMENTS:THEORETICAL AND PRACTICAL ISSUES Alexander Rad, Olof Wahlberg, Peter Öhman and Einar Häckner Paper presented at the ERES 2009 Conference, Stockholm June 24-27 2009
A Research program • Bank risk management – what is best practice? • A SME loan assessment study – ”the study” focusing on Lending Officers (”LO”s) assessments of loan applications from Small/Medium Sized Enterprises (”SME”s) • Research question for the study: How does a LO arrive at a summary conclusion on an individual SME loan application evaluation?
Purposes of the paper to ... briefly outline the theoretical frame of reference for theresearch program and for the study to identify information useful for bank credit assessments discuss methods for the study report on pilot testing of methods and assess their feasibility
Theoretical frame of reference Theories on banking and finance Accountability theory Cognitive theory Institutional theory and structuration theory Sense-making theory
Credit assessment criteria A. Industry risk B. Business concept C. Financial statements D. Anticipated financial standing (budgets, cash flows) E. Company documents (reliable, verified etc.) F. Management and board G. Client’s record H. Market conditions I. Collaterals J. The bank’s loss risk K. The bank’s earning opportunities
The Repertory Grid Approach Based on Personal Construct Theory (Kelly, 1955) We see “the world” as bipolar constructs e.g. “Easy to assess – Difficult to assess” Classes of phenomena in “the world” are called “elements” e.g. “Application cases”, “LOs”, “banks” or “clients” Constructs are used as Likert scales to score elements The output is a matrix (grid) with the scores for each elementon each construct The data captured can be analyzed e.g. by Principal Component (Factor) Analysis or Cluster Analysis
Constructs for pilot study 3 1. Easy (1) – difficult (7) to assess 2. Small (1) – large (7) influence by Basel agreements 3. Small (1) – large (7) impact on first time applicant (new client) 4. Requires future-orientated assessments to a small (1) – large (7) extent 5. Predominantly quantitative (1) – qualitative (7) information 6. Requires little (1) – much (7) time to assess 7. Little (1) – much (7) oral information 8. Predominantly objective (1) – subjective (7) assessments 9. Requires little (1) – much (1) second opinions 10. Small (1) – large (7) impact on recurring applicant (existing client) 11. Little (1) – much (7) relationship dependent 12. Small (1) – large (7) influence by the lending strategy of the bank 13. Requires little (1) – much (1) intuition 14. Small (1) – large (7) aid from decision supporting systems
Repertory Grid Plot - PCA Analysis Little intuition 13 Management/board F Much relationship dep 11 I Collaterals 11 Little relationship dep Much intuition 13
Repertory Grid Plot Varimax Rotated PCA Analysis – Component 1 Much relationship dep 11 Management/board F Much intuition 13 10 Large imp 2nd time applicant I Collaterals 7 Little oral information Transac- tion Relationship 5 Quantitave information 8 Objective assessment 13 Little intuition 11 Little relationship dep Subjective assessment 8 Qualitative information 5 Much oral information 7 Little impact for 2nd time applicant 10
Repertory Grid Plot Varimax Rotated PCA Analysis – Component 2 Future-oriented assessments Large support system 14 Anticipated fin standing D Much time consuming 6 4 Much future orientation K Bank’s earning opportunity Transac- tion Relationship Little future orientation 4 Industry Risk A 14 Small support system 6 Little time consuming Historically based assessments
Repertory Grid Plot Varimax Rotated PCA Analysis Future-oriented assessments Large support system 14 Anticipated fin standing D Much time consuming 6 4 Much future orientation K Bank’s earning opportunity Much relationship dep 11 Management/board F Much intuition 13 10 Large imp 2nd time applicant I Collaterals 7 Little oral information Transac- tion Relationship 5 Quantitave information 8 Objective assessment 13 Little intuition 11 Little relationship dep Subjective assessment 8 Qualitative information 5 Much oral information 7 Little impact for 2nd time applicant 10 Little future orientation 4 Industry Risk A 14 Small support system 6 Littel time consuming Historically based assessments
Contacts *Mid Sweden University Department of Social Sciences, 851 70 Sundsvall, Sweden Authors: Alexander.Rad@miun.seCorresponding Olof.Wahlberg@miun.se Peter.Ohman@miun.se Einar.Hackner@miun.se