CHAPTER FIVE

SUMMARY, CONCLUSIONS AND RECOMMENDATIONS

5.0 Introduction

This chapter presents the summary of the findings, conclusions and recommendation to the study. This was presented according to study objectives which were; to examine the effect of client appraisal techniques on financial performance of micro finance support Centre ltd. Mbale Branch, examine the effect of credit risk control tools on financial performance in micro finance support Centre ltd. Mbale Branch and to examine effect collection policies on financial performance in micro finance support Centre ltd. Mbale Branch.

5.1 Summary of the findings

5.1.1 Background information

Most of the respondents were in the age bracket of 25-30 years with a percentage of 53.8%, 51.9% of the respondents were female   who were more compared to the male, most of the respondents were married with 36.5%, majority of the respondents were Degree holders with 36.5%, most of staff members of MSC had spent a time period of 1-5 years with 44.2%.

5.1.1 The effect of client appraisal techniques on financial performance of micro finance institutions.

In this study, finding on this objective reveal the model summary using predictor loan reveals that adjusted R Square value is 0.727. This implies that 72.7% (0.727 *100) variations in financial performance is explained by client appraisal techniques while the remaining 27.3%           is explained by other factors. It can be deduced from the regression that loan is significance to welfare of teachers at, F=205.744 (0.000^b). Since significance calculated 0.000^bis less than 0.05, the study therefore accepts the hypothesis which stated that “There is a strong positive and significant effect of client appraisal techniques on financial performance”.

5.1.2. Effect of credit risk control tools on financial performance in micro finance support Centre ltd. Mbale Branch.

Results on this objective showed that the model summary in table 4.18 above using predictor saving reveals that adjusted R Square value is 0.784. This implies that 78.4% (0.784 *100) variations in financial performance is explained by credit risk control tools while the remaining 21.6% is explained by other factors. It can be deduced from the regression that saving is significance to financial performance at, F=280.345 (0.000^b). Since significance calculated 0.000^bis less than 0.05, the study therefore reveals that “There is a strong positive and significant relationship credit risk control tools and financial performance.”

5.1.3. Effect collection policies on financial performance in micro finance support Centre ltd. Mbale Branch.

Findings on this objective reveal that the model summary using predictor collection policies reveals that adjusted R Square value is 0.766. This implies that 76.6% (0.766 *100) variations in financial performance is explained by collection policies while the remaining 23.4% is explained by other factors. It can be deduced from the regression that collection policies are of significance to financial performance at, F=252.454 (0.000^b). Since significance calculated 0.000^bis less than 0.05, the study therefore reveals that “There is a strong positive and significant relationship collection policies and financial performance.”

5.2 Conclusion

From the foregoing discussions, the following conclusions are drawn from the findings of the study.

5.2.1 The effect of client appraisal on financial performance.

The results show that client appraisal techniques significantly contribute to financial performance. The correlation between them is r= 0.323, with p=0.003. Therefore, if the organization gives more consideration to client appraisal techniques in line with the objectives of the organization, then financial performance will be improved.

5.2.2 The effect of credit risk control tools on financial performance

Results revealed that there is a positive significant relationship between credit risk control tools and financial performance. This is based on the obtained correlation coefficient of .326 (**) with a significance value of .003. This explains that in a situation where the credit risk control tools are properly assessed, then financial be effectively achieved.

5.2.3 The effect of collection policies on financial performance.

Findings in the table above revealed that there is a positive significant relationship between collection policy and financial performance in MSC. This is based on the obtained correlation coefficient of .298 (**) with a significance value of .002. This explains that in a situation where credit policies are effectively followed, then financial performance will effectively take place.

5.3Recommendations

5.3.1 The effect of client appraisal on financial performance.

The study recommends that there is need for MSC to enhance their client appraisal techniques so as to improve their financial performance. Through client appraisal techniques, MSC will be able to know the credit worthiness of clients and thus reduce non-performing loans.

5.3.2 The effect credit risk control tools on financial performance in micro finance support Centre ltd. Mbale Branch

Furthermore, MSC should reduce on their interest rates as these affect performance of loans. This will help to bring in more borrowers. The risk aspect should be given more attention because when not handled properly, the organization may end up losing.

5.3.3 The effect of microfinance asset financing services on the growth of SMEs.

The study also recommends that MSC should continue to strengthen its credit policies as this has been very effective in improving the organization’s financial performance.

5.4 Suggestions for further research.

The researcher recommends further research to establish the effect of credit management on profitability of micro finance institutions in Uganda.

REFERENCES

Books

ABEDI, S. (2000): Highway to Success, Credit Management Journal, and http:// leathers inters.

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W.F. (2000). Risk Is In. [On-line]. Available http://www.dnb.com(22/10/07).Com

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BINKS, M., AND ENNEW, T. (1996). Financing small firms, small business and entrepreneur, 2^nd edition.

BINKS, M., ANDENNEW, T. (1997). Small business and relationship banking: the impact of participative behavior, entrepreneurship: Theory and practice vol. 21, No.4 pp 83-92.Ed Macmillan.

BRIGHAM, E.F., GAPENSKI, L.C. AND DAVE’S, P.R. (1999). Intermediate Financial Management. Florida: The Dryden press.

CGAP (2009) [Online]. Measuring results of micro finance Institutions Available http://www.gap.org

CHRISTEN, P., E. RHYNE, R. C. VOGEL, AND C. MCKEAN (1995), “Maximizing the Outreach of Microenterprise Finance: An analysis of Successful Micro finance programs “,

EDWARD. B (1993) Credit Management (6^thEd.)  http://www.gowerpublishing.com

EDWARDS, P. &TURNBULL (1994). Finance for small and medium sized enterprises.

KREJCIE and MORGAN, 1970. Determining Sample Size for Research Activities.

https://home.kku.ac.th/sompong/guest_speaker/KrejcieandMorgan_article

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Journals

DEAKINS, D., HUSSEIN, G. (1999).Risk assessment with asymmetric Information: International Journal of Bank Marketing.

NELSON, L. (2002). Solving Credit Problem. Retrieved on 21 July 2015 from http://www.cfo.com

Reports

EPPY, I. (2005) Perceived Information Asymmetry, Bank lending Approaches and Bank           Credit Accessibility by SMES in Uganda Makerere University.

TURYAHEBWA, A (2013) Financial Performance in the Selected Microfinance Institutions In Uganda (unpublished master’s thesis) Kampala International University,West campus,

SHEILAH, A.L. (2011) Lending Methodologies and Loan losses and Default in a Microfinance Deposit Taking Institutions in Uganda; a research report presented to the Makerere University Uganda.

OWINO, M. (2012) Effect of the Lending Policies on the Levels of Non-performing Loans (NPLs) on Commercial Banks of Kenya.

DALLAMI, K. & GUIGALE, M. (2009) Reflection to Credit policy in developing Countries Policy.

DHAKAL, S. (2011), „Risk management in SACCO‟s, Econometric Analysis‟. Second Edition Macmillan. London.

NAGARAJAN, M. (2011), “Credit risk management practices for microfinance institutions in Mozambique”. Unpublished MBA project-University of Maputo.

APPENDICES:

APPENDIX A: QUESTIONNAIRE

QUESTIONNAIRE ON THE EFFECT OF CREDIT MANAGEMENT ON THE FINANCIAL PERFORMANCE OF MICROFINANCE INSTITUTIONS IN UGANDA.  CASE STUDY: THE MICROFINANCE SUPPORT CENTER LIMITED: MBALE BRANCH.

Questionnaire for Microfinance support Centre limited.

Dear respondent

RE:     APPLIED QUESTIONNAIRE

I am a student at MTAC undertaking a Diploma in accounting and finance; I am currently undertaking an undergraduate research project on; the Effect of credit management on the financial performance of Microfinance institutions in Uganda, A case study at Microfinance support Centre limited as partial fulfillment of my degree requirements.

Attached herewith is a questionnaire that I am requesting to be completed. All the information you will provide shall remain strictly confidential.

Your cooperation shall be highly appreciated.

Sincerely,

………………………

NAKUMIZA ALIMA

SECTION 1-     INTRODUCTION  

Instructions: (Please tick or fill in the blank space where appropriate)

SECTION A: General Personal Data

1. Gender

Male                 Female

2. Age group?
3. a) 18-25 b) 25-30 c) 30-40            d) 40-50
4. Marital status?
5. a) Married b) Single
6. c) Divorced d) Engaged
7. Highest level of Education?

Others specify……………………………………..

5. Duration spent working in Microfinance support Centre limited.

6. Department of work

SECTION.B

Part B: Credit Risk Management Practices

CLIENT APPRAISAL TECHINIQUES;

In the following questions answer as follows;

NB SA. Stands for-Strongly Agree A-Agree NS-Not Sure D-Disagree SD-Strongly Disagree

What is your level of agreement on the following statements relating to client appraisal in Microfinance support center limited?

CREDIT RISK CONTROL TOOLS.

COLLECTION POLICY

APPENDIX B: INTERVIEW GUIDE

Date of interview………………………………………………………………………………………..

APPENDIX C: Table for determining sample size from a given population

Note:   “N” is population size

            “S” is sample size.

Krejcie, Robert V., Morgan, Daryle W., “Determining Sample Size for Research Activities”, Educational and Psychological Measurement, 1970.

APPENDIX D: LIST OF FREQUENCE TABLES.

Table 3.2: Showing category, population, sample size and sampling technique.

Table 4.1 shows the response rate of the questionnaires.

APPENDIX E: WORK PLAN.

APPENDIX F: BUDGET.