Quest for a Credible Model in Lending Evaluation

Preface

This book examines potential income as an additional independent variable that will complement credit history to predict loan repayment with applicable interest. Lending exposures constitute the most material risk concentrations within banks, and this book contributes to the literature on lending risk management within banks and other lending institutions. Risk management theories have provided emphatic guidelines for risk control and management of banks’ loans, yet the results of other studies indicate that the credit evaluation models do not fully explore all available predictors of loan repayment. This deprives the models of total efficiency at predicting loan repayment with applicable interest, and leads to accretion in the nonperforming loans portfolio. It also leads to inequitable credit rationing practices. The resultant effect is a decrease in both investment and consumer spending that stimulates macroeconomic activities.

This book employs the design and administration of original survey instrument to participants. Loan repayment was the criterion, and credit history and potential income were the predictors. Results of the regression were significant, F (2, 143) = 83.13, p < .001; and credit history and potential income predicted 53.1% of the variance in loan repayment. The findings suggest a policy prescription for lenders: consideration should be given to both credit history and potential income in loan decision making. Lenders may gain useful insight that will help them impose better controls over credit risks.

This book is divided into two parts:

Part I examines the background of the credit evaluation system. It begins with Chapter 1, which provides definitions of key words as used in this book to establish conceptual symmetry with the reader. Next, the chapter provides a rationale for effective credit evaluation system, and then the limitations of credit history as a tool for evaluating credit worthiness. It is then followed by Chapter 2, which identifies the problems with the credit evaluation model and reviews current innovations aimed at solving those problems.

Part II examines potential income as complementary variable to credit history for measuring loan repayment. It starts with chapter 3 with a discussion of the methodology of the study, analysis of data, brief discussion of the concepts of validity and reliability, and provides rationale behind the independently designed survey instrument of the analysis. It is then followed by chapter 4, which provides a discussion of data validation and findings. The book concludes with chapter 5 with a discussion of the impact on social change, actions required to improve upon future studies, and suggestions for future researchers.

Acknowledgments

Several individuals have contributed to this project. I particularly express my gratitude to Professor Reza G. Hamzaee of Missouri Western State University, USA; and Professor William H. Brent of Howard University in Washington, D.C., USA for their constructive critiques and encouragement. Finally, it is a pleasure to acknowledge the debts that I owe to the many researchers and authors whose work this book has greatly benefited from.

Charles K. Addo, Ph.D.

Catholic University College of Ghana

Faculty of Economics and Business Administration

Fiapre, Sunyani

December 2010

Contents

Preface

Acknowledgments

PART I:

Background of the Credit Evaluation System

Chapter 1   Understanding the Credit Evaluation System

Chapter 2   Overview of the Credit Evaluation Model

PART II:

Empirical Analysis Of Potential Income and Credit History as Complementary Variables for Loan Repayment and Creditworthiness

Chapter 3   Methodology of the Study

Chapter 4   Data Validation and Findings

Chapter 5   Summary, Conclusions, and Further Research

References

APPENDIX A

SAMPLE LETTER OF COOPERATION FROM COMMUNITY RESEARCH PARTNER

APPENDIX B

PARTICIPANT CONSENT FORM