i Gusau Journal of Accounting and Finance (GUJAF) Vol. 3 Issue 1, April, 2022 ISSN: 2756-665X A Publication of Department of Accounting and Finance, Faculty of Management and Social Sciences, Federal University Gusau, Zamfara State -Nigeria ii © Department of Accounting and Finance Vol. 3 Issue 1 April, 2022 ISSN: 2756-665X A Publication of Department of Accounting and Finance, Faculty of Management and Social Sciences, Federal University Gusau, Zamfara State -Nigeria All Rights reserved Except for academic purposes no part or whole of this publication is allowed to be reproduced, stored in a retrieval system or transmitted in any form or by any means be it mechanical, electrical, photocopying, recording or otherwise, without prior permission of the Copyright owner. Published and Printed by: Ahmadu Bello University Press Limited, Zaria Kaduna State, Nigeria. Tel: 08065949711, 069-879121 e-mail: abupress2013@gmail.com abupress2020@yahoo.com Website: www.abupress.com.ng mailto:abupress2013@gmail.com iii EDITORIAL BOARD Editor-in-Chief: Prof. Shehu Usman Hassan Department of Accounting, Federal University of Kashere, Gombe State. Associate Editor: Dr. Muhammad Mustapha Bagudo Department of Accounting, Ahmadu Bello University Zaria, Kaduna State. Managing Editor: Umar Farouk Abdulkarim Department of Accounting and Finance, Federal University Gusau, Zamfara State. Editorial Board Prof.Ahmad Modu Kumshe Department of Accounting, University of Maiduguri, Borno State. Prof Ugochukwu C. Nzewi Department of Accounting, Paul University Awka, Anambra State. Prof Kabir Tahir Hamid Department of Accounting, Bayero University, Kano, Kano State. Prof. Ekoja B. Ekoja Department of Accounting, University of Jos. Prof. Clifford Ofurum Department of Accounting, University of PortHarcourt, Rivers State. Prof. Ahmad Bello Dogarawa Department of Accounting, Ahmadu Bello University Zaria. Prof. Yusuf. B. Rahman Department of Accounting, Lagos State University, Lagos State. Prof. Suleiman A. S. Aruwa Department of Accounting, Nasarawa State University, Keffi, Nasarawa State. Prof. Muhammad Junaidu Kurawa Department of Accounting, Bayero University Kano, Kano State. Prof. Muhammad Habibu Sabari Department of Accounting, Ahmadu Bello University, Zaria. Prof. Okpanachi Joshua Department of Accounting and Management, Nigerian Defence Academy, Kaduna. iv Prof. Hassan Ibrahim Department of Accounting, IBB University, Lapai, Niger State. Prof. Ifeoma Mary Okwo Department of Accounting, Enugu State University of Science and Technology, Enugu State. Prof. Aminu Isah Department of Accounting, Bayero University, Kano, Kano State. Prof. Ahmadu Bello Department of Accounting, Ahmadu Bello University, Zaria. Prof. Musa Yelwa Abubakar Department of Accounting, Usmanu Danfodiyo University, Sokoto State. Dr. Salisu Abubakar Department of Accounting, Ahmadu Bello University Zaria, Kaduna State. Dr. Isaq Alhaji Samaila Department of Accounting, Bayero University, Kano State. Dr. Fatima Alfa Department of Accounting, University of Maiduguri, Borno State. Dr. Sunusi Sa'ad Ahmad Department of Accounting, Federal University Dutse, Jigawa State. Dr. Nasiru A. Ka’oje Department of Accounting, Usmanu Danfodiyo University Sokoto State. Dr. Aminu Abdullahi Department of Accounting, Usmanu Danfodiyo University Sokoto, State. Dr. Onipe Adebenege Yahaya Department of Accounting, Nigerian Defence Academy, Kaduna State. Dr. Saidu Adamu Department of Accounting, Federal University of Kashere, Gombe State. Dr. Nasiru Yunusa Department of Accounting, Ahmadu Bello University Zaria. Dr. Aisha Nuhu Muhammad Department of Accounting, Ahmadu Bello University Zaria. Dr. Lawal Muhammad Department of Accounting, Ahmadu Bello University Zaria. Dr. Farouk Adeza School of Business and Entrepreneurship, American University of Nigeria, Yola. v Dr. Bashir Umar Farouk Department of Economics, Federal University Gusau, Zamfara State. Dr Emmanuel Omokhuale Department of Mathematics, Federal University Gusau, Zamfara. State ADVISORY BOARD MEMBERS Prof. Kabiru Isah Dandago, Bayero University Kano, Kano State. Prof A M Bashir, Usmanu Danfodiyo University Sokoto, Sokoto State. Prof. Muhammad Tanko, Kaduna State University, Kaduna. Prof. Bayero A M Sabir, Usmanu Danfodiyo University Sokoto, Sokoto State. Prof. Aliyu Sulaiman Kantudu, Bayero University Kano, Kano State. Editorial Secretary Usman Muhammad Adam Department of Accounting and Finance, Federal University Gusau, Zamfara State. vi CALL FOR PAPERS The editorial board of Gusau Journal of Accounting and Finance (GUJAF) is hereby inviting authors to submit their unpublished manuscript for publication. The journal is published in two issues of April and October annually. GUJAF is a double-blind peer reviewed journal published by the Department of Accounting and Finance, Faculty of Management and Social Sciences, Federal University Gusau, Zamfara State Nigeria The Journal accepts papers in all areas of Accounting and Finance for publication which include: Accounting Standards, Accounting Information System, Financial Reporting, Earnings Management, , Auditing and Investigation, Auditing and Standards, Public Sector Accounting and Auditing, Taxation and Revenue Administration, Corporate Governance Issues, Corporate Social Responsibility, Sustainability and Environmental Reporting Issue, Information and Communication Technology Issues, Bankruptcy Prediction, Corporate Finance, Personal Finance, Merger and Acquisitions, Capital Structure, Working Capital Management, Enterprises Risk Management, Entrepreneurship, International Business Accounting and Finance, Banking Crises, Bank‟s Profitability, Risk and Insurance Issue, Islamic Finance, Conventional and Islamic Banks and so forth. 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Finally, manuscript should be send to our email address elfarouk105@gmail.com and a copy to our website on journals.gujaf.com.ng http://www.gujaf.com.ng/ vii PUBLICATION PROCEDURE After receiving a manuscript that is within the similarity index threshold, a confirmation email will be send together with a request to pay a review proceeding fee. At this point, the editorial board will take a decision on accepting, rejecting or making a resubmission of the manuscript based on the outcome of the double-blind peer review. Those authors whose manuscript were accepted for publication will be asked to pay a publication fee, after effecting all suggested corrections and changes made on the manuscript. All corrected papers returned within the specified time frame will be published in that issue. PAYMENT DETAILS Bank: FCMB Account Number: 7278465011 Account Name: Gusau Journal of Accounting and Finance FOR INQUIRY The Head, Department of Accounting and Finance, Federal University Gusau, Zamfara State. elfarouk105@gmail.com +2348069393824 FOR MORE INFORMATION, CONTACT The Editor-in-Chief on +2348067766435 The Associate Editor on +2348036057525 OR visit our website on www.gujaf.com.ng or journals.gujaf.com.ng http://www.gujaf.com.ng/ http://www.gujaf.com.ng/ viii CONTENTS Mediating effect of Audit Committee on Board Dynamic and Creative Accounting in Nigerian Firms Abbas Usman PhD, Shehu Usman Hassan PhD 1 Financial Performance of Banks in Selected African Countries: Does Institutional Quality Matter? Toluwa Celestine Oladele PhD, Peters Ade Sanni 22 Firm-Specific Characteristcs and Financial Performance of Listed Agricultural Companies in Nigeria Abdulrazaq T. Jimoh, John A. Attah 33 Effect of Financial Leverage on Stock Returns of Listed Companies in Nigeria Capital Market Abdulrahman Abubakar, Prof. Ahmad Bello, Prof. S. A. Abdullahi, Dr. M. D. Tahir 45 Efficiency of Deposit Money Banks in Nigeria: Data Envelopment Analysis Approach Mayowa Gabriel AJAO, PhD, Lucky Charity OMOREGIE, PhD 57 Credit Appraisal, Collection Policy and Loan Performance of Microfinance Banks in Kwara State, Nigeria Lukman A. O. Abdulrauf 69 Environmental Sustainability Disclosure and Market Value of listed Oil and Gas firms in Nigeria Munir Aliyu Saleh, Sirajo Bappah, Prof. Gbegi Daniel Orsaa, Ibrahim Adamu Saleh PhD 81 Audit Quality, Tenure and Real Earnings Management of Listed Nonfinancial Firms in Nigeria Ahmed Mohammed, Ademu Yahaya, Musa Zakariya 95 Effect of CEO Pay and CEO Power on Risk-Taking of Listed Deposit Money Banks in Nigeria Ismaila Yusuf, Dr. Salisu Abubakar, Dr. Idris Ahmed Aliyu, Dr. (Mrs) Aneitie Charles Dikki 104 Nexus Between Taxation and Foreign Direct Investment in Nigeria Daniel Ayegbeni Ulokoaga, Esther Ikavbo Evbayiro-Osagie (Mrs), Ph. D 115 Working Capital Management and Profitability of Listed Consumer and Industrial Goods Companies in Nigeria Kwasau Ntyak Leah, Samuel Eniola Agbi PhD, Lateef Olumide Mustapha PhD 125 Value Relevance of Earnings and Book Value: A Comparative Analysis Between Big4 and Non-Big4 Audited Listed Firms in Nigeria Abdu Abubakar, Ishaya Luka Chechet PhD, Muazu Saidu Badara PhD, Yunusa Nasiru PhD 136 ix Value Relevance of International Financial Reporting Standard 4 (IFRS 4) of Listed Nigerian Insurance Firms Mariya Mohammed Hafiz, Muhammad Mustapha Bagudo PhD, Salisu Abubakar PhD 145 Determinants of Audit Fees of Listed Insurance Companies in Nigeria Sagir Lawal, PhD, Mohammed Ibrahim, PhD 158 Taxation and Social Services: Evidence from Nigeria ADEGBITE, Tajudeen Adejare, PhD, ABDUSSAMAD, Olarinde 171 Ownership Structure and Financial Performance of Quoted Mortgage Banks in Nigeria Awotundun, D. A., PhD, Jinadu, M. Y. B., Fakunmoju, S. K., PhD. 183 Capital Structure and Profitability of Listed Deposit Money Banks in Nigeria Rahji Ohize Ibrahim, Kamaldeen Ibraheem Nageri, PhD, Abdullai Agbaje Salami, PhD 194 1 CREDIT APPRAISAL, COLLECTION POLICY AND LOAN PERFORMANCE OF MICROFINANCE BANKS IN KWARA STATE, NIGERIA Lukman A. O. Abdulrauf Department of Accounting and Finance Kwara State University, Malete, Nigeria okelukman2003@yahoo.com Abdul Olalekan Hassan Department of Accountancy, Kwara State Polytechnics, Ilorin Abstract The arrival of microfinance banks as another channel to mainstream the provision of financial services has become a major succour. Yet, the banks encountered high risk of default which is not unconnected with the peculiarities in its lending policies. In view of this, the study examines the effect of credit appraisal policy and credit collection policy on loan performance of MFBs in Kwara State, Nigeria. The study employed survey research design and the population consists of bank managerial and senior staffers from which one hundred and forty (140) were drawn conveniently as sample Data obtained through questionnaire were analyzed using descriptive and inferential statistics. The hypotheses for the study were tested using ordered logistic regression with average partial effects. The study found that collection policy significantly affects the loan performance of MFBs while credit appraisal policy does not significantly affect their loan performance as evidenced by their p-values. The study therefore concluded that collection policy influence loan performance of MFBs in Kwara State. Therefore, the study recommends that the credit appraisal policies should be restructure to capture the relevant information which will help these banks to determine the default intent of customers. Also, further monitoring mechanism should be put in place for bank loan collection policy in order that its effectiveness in increasing loan performance is improved. Keywords: credit appraisal policy, collection policy, microfinance, loan performance 1. Introduction The unfolding of microfinance as another avenue to mainstream provision of financial services has offered an enormous succuor for most people and institutions that are hitherto unable to partake in the formal financial sector. Aside contributing to the level of credit accessibility and financial inclusion, microfinance institutions have been described to assert great influence on socio-economic status of people, particularly, those in the rural areas (Hitchcock, 2014). It is important that such a great contributor to socio-economic development is given required attention regarding its loan operations and performance. According to the World Bank Group of the International Finance Corporation (IFC) (2018), microfinance around the world, has built a solid track record as essential catalyst for poverty amelioration and has gained access to financial mainstream. It is equally on record that the recent industrial growth all over the world (which has reached approximately a hundred and thirty million clients) is traceable to the emergence of microfinance. In spite of this, the coverage of microfinance among the over three billion poor people in the world is still less than 20 percent of its potential market (Arhin et al. 2019). mailto:okelukman2003@yahoo.com 2 Extension of credit facilities is one of the major activities of all microfinance institutions, microfinance banks inclusive. This activity accounts for greater percentages in the overall operating assets of these lending institutions. However, some of the facilities extended by these institutions usually become nonperforming and eventually result in bad debts with adverse consequences for the overall financial performance of the institutions. The default risk arises as a result of a number of external factors, particularly, those related to economic downturn, as well as failure of internal processes within the lending institutions. These include, majorly, the business cycle (or economic fluctuations) and the prevailing lending policy of these institutions. Lending institutions face multiple risks in their line of business due to the nature of business (lending) and prominent among these risks is the risk of default from borrowers. In fact, issue of loan default (NPLs) is becoming an increasing problem that threatens the sustainability of MFIs in Nigeria (Nwanna, &Oguezue, 2017). Specifically, NPL has been a source of misery for MFBs in Nigeria because it adversely affects their financial position and operations in terms of liquidity, profitability, debt- servicing capacity, lending capacity and ability to raise additional capital. For instance, according to estimates from statistical bulletin of the Central Bank of Nigeria, the population of MFBs in Nigeria in 2000 was 881, which corresponds to a liquidity of 61.42 percent. These numbers fell in 2011 to 821 MFBs and 58.7 percent liquidity ratio and fell further in 2018 to 529 MFBs and 23.57 percent of liquidity. The NPL problem of MFBs might be linked to a number of factors; one of it is the MFBs‟ policies that back the lending process (Omare, 2016). The major lending policies relate to credit appraisal procedure, management policy, collection policy and interest rates policy (Lieber, 1986). Prominent among the NPL problem of MFBs are not unconnected with the credit appraisal procedure and collection policies. The procedure for appraising loan applications, which include the technical feasibility of the credit, its economic viability and creditworthiness of the borrower are usually time taking and with prohibitive costs. As such many MFBs do not have the capacity to carry out such operations in short period of time with the fact that there is pressure not to over-delay the appraisal process (Omare, 2016). The collection policy and the way it affects non-performing loans of MFBs is another issue of great concern. Borrowers of microfinance, as the name implies are small and micro entities, who are relatively more difficult to trace and locate when loans are due for repayment. An adequate collection policy might be helpful in ensuring a substantially large proportion of the granted loans and hence, reduce the non-performing components of loan portfolio. However, the micro nature of borrowers from microfinance banks poses a great challenge in the loan collection process. It is on the context of the problems above and the economic importance of MFBs that this study examines the impact that credit appraisal policy and credit collection policy have on loan performance of MFBs in Kwara State, Nigeria. In conformity with the problem stated above, the following research hypotheses stated in null form were tested to achieve the study objectives: Ho1: Credit appraisal policy does not have significant effect on the loan performance among deposit taking MFBs in Kwara State. Ho2: Collection policy does not have significant effect on the loan performance among deposit taking MFBs in Kwara State. 3 2. Review of Relevant Literature Microfinance consists primarily of providing financial services including, savings, micro- credit, micro insurance, micro leasing and transfers in relatively small transactions designed to be accessible to micro-enterprises and to low-income households. The definition implies that microfinance are small credits or smaller scale advances offered to destitute individuals or people that have low salary or are independently employed or working (Olanike & Adebola, 2014). There are 3 classifications of MFBs in Nigeria namely Unit Bank, State Bank and National Bank Unit MFBs are licensed to operate in only one location, and also mandated to have a capital base of N200million. State MFBs are licensed to operate in a State or Abuja, the Federal Capital Territory. Their capital requisition is N1billion and they are permitted to have branches opened within the same state or Abuja, which federal capital territory. National MFB are licensed for operation in more than a State which including Abuja, the Federal Capital Territory. It is mandated to have paid-up capital base of N5 billion. The term Non-Performing Loans is used interchangeably with Bad loans and impaired loans as identified in Fofack (2005). Berger and De young (1997) also describes these types of loans as “problem loans” In broad context, loans that are outstanding in both interest and principal for a period of time contrary to terms and conditions spelt out in the loan agreement are considered as non-performing loans. Addae-Korankye (2014) defined non-performing loans as loans that have not been repaid for a period of ninety days. Microfinance banks are majorly known for their credit facilities functions, with loans as their dominant assets, representing about seventy-five percent of their total assets. The implication of this is that loans stand as the operating income of microfinance banks, which may expose them to higher risks of failure if not repaid by borrowers (Nyarko-Baasi, 2018). Defaulted loans are not favorable to microfinance banks, especially when the amount involved is high. Although securities are held for most of the loans granted to borrowers, there is uncertainties surrounding the repayment. Therefore, it becomes a non-performing loan when this risk turns out to materialize. According to the CBN prudential guidelines, an MFB is not permitted to fund any client beyond 7.5 per cent of its shareholders funds unimpaired by losses. The provisions for performing and non-performing loans are also given in terms of number of days of missed payment, description and allowance for probable loss as follows: Table 1: Provision for Classified Assets Number of Days of Missed Payment Description Allowance for Probable Loss (%) Not more than 30 days Performing 1 Above 30 days but less than 60 Days Pass and Watch 5 At least 60 days but not more than 90 days Substandard 20 At least 91 days but not more than 180 days Doubtful 50 4 More than 180 days Lost 100 Source: Central Bank of Nigeria, 2019 According to this requirement, any loan with not more than 30 days of unpaid principal and/or interest is considered as a performing loan and there is only a 1% allowance for probable loss for such loans; a loan with above 30 but less than 60 days of unpaid principal and/or interest is considered as a pass and watch loan and there is a 5% allowance for probable loss for such loans; a loan with 61 to 90 days of unpaid principal and/or interest is considered as a substandard loan and there is a 20% allowance for probable loss for such loans; a loan with 91 to 180 days of unpaid principal and/or interest is considered as a doubtful loan and there is a 50% allowance for probable loss for such loans; and a loan with above 180 days of unpaid principal and/or interest of missed payment is considered as a lost loan and there is a 100% allowance for probable loss for such loans. Given these classifications, all MFBs are required to review their loans and advances and other assets at least once every thirty days, and make appropriate provisions. Lending policy is a set of guidelines and criteria developed by a bank and used by its employees to determine whether an application for a loan should be granted or turned down. It is also known as a statement of philosophy, standards, and guidelines that its employees must observe in granting or refusing a lending request (Jacobson and Roszbach, 1998). Based on the previous studies, lending policy components include but not limited to Credit appraisal procedure policy, Credit Portfolio planning and management policy, Collection policy and Interest rates policy. This study only considers two prominent policies that is Credit appraisal policy and Collection policy. The former has to do with how a lender appraises the technical feasibility, economic viability and bankability including creditworthiness of the prospective borrower. The latter systemizes the steps taken to recover amounts due prior to litigation. This includes: when costumers should be contacted, how they should be contacted, how disputes are resolved, when internal or external “collectors are used to step-up collection efforts, when and whether to turn the account over to litigation or write- off the debt. Theoretically, study is rooted in the postulations of the institutional theory regarding the importance of strong institutions in creating rules guiding economic activities to achieve legitimate outcomes which may not be efficient ones. Strong institutions give birth to effective policies that can guide corporate activities, specifically in this case, the lending process. When the rules of the „lending game‟ are strong, effective policies such as those related to credit appraisal, management, collection and interest rates are developed to ensure appropriate checks are in place to guarantee a good loan performance which ensures borrowers pay back the borrowed financial facilities. Wondimagegnehu (2012) examine the factors that account for of loans performance status in Ethiopia. The mixed research approach was adopted for the study. Survey was conducted with professionals engaged in both private and state-owned Banks in Ethiopia holding different positions using a self-administered questionnaire. In addition, the study used structured review of documents and records of banks and in-depth interview of senior bank officials in the Ethiopian banking industry. The findings of the study showed that poor credit assessment, failed loan monitoring, underdeveloped credit culture, lenient credit terms and conditions, aggressive lending, compromised integrity, weak institutional capacity, unfair 5 competition among banks, willful default by borrowers and their knowledge limitation, fund diversion for unintended purpose, over/under financing by banks are ascribed to loan default. Addae-Korankye (2014) analyzed the causes and control of loan delinquency/default in microfinance institutions in Ghana. The study showed that high interest rate, inadequate loan sizes, poor appraisal, lack of monitoring, and improper client selection are significantly John (2016) conducted a research on non-performing loans portfolio and its effect on bank profitability in Nigeria. The results show that that non-performing loans portfolio has negative effect on bank profitability. The study further reveals that insider dealing involving over-extension of loans to promoters, directors and significant others that became bad and irrecoverable, is the bane of large non-performing loan portfolio in Nigeria. 3. Methodology The study used descriptive survey design which according to Churchill (1991) is appropriate where the study seeks to describe the characteristics of certain groups, describes what exists and considers the existing conditions or relationships, current processes and tangible developing effects. Population of the study comprises the managerial and senior staffers of tweny-nine (29) licensed MFBs operating in Kwara State. A sample of 140 managerial and senior staffers (7 from each bank) was drawn from the 20 MFBs operating in Ilorin, the state capital using convenience sampling technique. This is based on the suggestion of Owino (2013), that these are the most conversant individuals to the issue related lending policies and non-performing loans. 5-point likert scale (for independent variables) and ordinal scale (for dependent variable) questionnaire was used to collect the data. Data were analysed and the hypotheses were tested using ordinal logit regression model. Following the theoretical postulation of the institutional theory, a multiple regression model is specified here by adapting the model from the study of Abugah et al. (2017) as follows: …………………………………………… 1 Whereas: LP is loans performance of Microfinance Banks in Kwara State CRPP is credit appraisal procured policy CPY is collection policy is the intercept term are the coefficients of the independent variables ε is the error term A priori expectations: β1 > 0, β2> 0, 4. Results and Discussions Descriptive Statistics Out of the 140 questionnaires distributed only 135 were returned and this represents 97.8% response rate which is considered adequate for the study. Demographic Information of the Respondents Table 2: Demographic Distribution of Respondents Frequency Percent Cum. Percent Gender Female 36 26.67 26.67 Male 99 73.33 100.00 Age 6 18 – 27 years 11 8.15 8.15 28 – 37 years 41 30.37 38.52 38- 47 years 58 42.96 81.48 48-57 years 20 14.81 96.29 58years and above 5 3.71 100.00 Marital Status Single 39 28.89 28.89 Married 82 60.74 89.63 Others 14 10.37 100.00 Education Secondary/Technical 12 8.89 8.89 OND/NCE 25 18.52 27.41 BSC/HND 74 54.81 82.22 Postgraduate 24 17.78 100.00 Position Managing Director 16 11.85 11.85 Manager/Head of unit 79 58.52 70.37 Senior staff 40 29.63 100.00 Experience Less than 5years 23 17.04 17.04 6-10 years 62 45.93 62.97 11-20 years 31 22.96 85.93 Over 20 years 19 14.07 100.00 Source: Author’s Computations, 2022. As for the respondent gender, there is wide difference in the number of male and female gender of the respondents. Only 26.67% (36respondents) of the surveyed managing directors, managers and senior officers are female whereas male group makes up to 73.33% (99 respondents). Regarding the respondents age, results show that majority (representing 42.96%) falls within the age group of 38 – 47 years. 8.15% (11 respondents) fall within age-range less than 18-27 years, 30.37% (41 respondents) fall within age-range less than 28-47 years, 14.81% (20 respondents) fall within age-range less than 48-57 years and only 3.71% (5 respondents) fall within age-range 58years and above. With regards to marital status of the respondents, 28.89% (39 respondents) are single, 60.74% (82 respondents) are married while only 10.37% 7 (14 respondents) fall within the categories of others who may be window, divorced among others. Regarding their highest educational qualifications, majority of the respondents have attained B.Sc./HND degree level. 54.81% (74 respondents) have B.Sc./HND as their highest educational qualification, 18.52% (25 respondents) are OND/NCE holders, only 8.89% (12 respondents) are Secondary/Technical certificate holders and 17.78 (24 respondents) have postgraduate qualifications. As for the distribution of the respondents regarding the position they occupy in the organization, results show that majority of them are managers or unit heads with 58.52% (79 respondents) being managers or unit heads, 29.63 (40 respondents) are senior officials and 11.85% (16 respondents) being managing directors of their various banks. In terms of experience on their current positions, the results show that majority of the sampled respondents 45.93% (62 respondents) have being on their current position for between 6-10 years. 17.04% (23 respondents) have spent less than 5 years on their current role, 22.96% (31 respondents) have between 11-20 years of experience and only 14.07% (19 respondents) have over 20 years‟ experience on their current role in their banks. Over all, the descriptive results of the demographic characteristics of the respondents reveal that the sampled respondents are relatively mature, and possess the least educational exposure and job experience required to reasonably provide answers to questionnaire items. Preliminary Analysis of the Data This section presents the results of the preliminary „check and balance‟ analysis both prior to and after the main analysis. The tests carried out include Reliability test (using cronbach‟sAlpa) and Multicolinearity Test (Variance Inflation Factor) and model specification tests (using linktest). Normality test was not conducted as it is not a pre- requisite for Linear Probability Models. Reliability Test The result as presented in Table 3 depicted that the cronbach alpha statistics of 77%, 74% and 71% for loan performance, Credit Appraisal Policy and Collection Policy respectively which are adjudged adequate. An acceptable standard is that it should range between 0.7 and 0.8 (Field, 2006). This attests to the reliability of research instrument of data gathering. Table 3: Cronbach’s Alpha Statistics Variables Cronbach‟s Alpha N Loan Performance 0.77 5 Credit Appraisal Policy 0.74 8 Collection Policy 0.71 5 Source: Author’s Computation, 2022 Multicollinearity Assessment Multicollinearity test was carried out on the explanatory variables involved in the multiple regression analysis using Variance Inflation Factor (VIF). The variance inflation factor also indicates that problematic multicollinearity is not present in the model. This is obvious from the average VIF of below 10 as presented in Table 4. Hence, multicolinearity problem is not severe or nonexistent. Table 4: Variance Inflation Factor Variable VIF 1/VIF Credit Appraisal Policy 2.37 0.2114 8 Collection Policy 4.82 0.2301 Mean VIF 3.60 Source: Author’s Computations, 2021. Asteriou and Hall (2016) are of the opinion that VIF values greater than 10 generally indicate a situation of problematic multicollinearity. This is always the case when R-squared of the model is exceeds a threshold of 0.9. Model Specification Tests Table 5 depicts the test for loan performance model specification with a view to ascertaining the correctness or otherwise of the model specified for the study. In other words the test is crucial to detect if the model specified is devoid of specification error. Table 5: Model Specification Test – Loan Performance Model Lending Policies Coefficient p-value _hat 1.052 0.001 _hatsq 0.108 0.056 Constant 0.231 0.289 Source: Author’s Computation, 2021. The study employs link test specification test. The test uses the linear predicted value (_hat) and linear predicted value squared (_hatsq) as the predictors of good model. For the model to be well specified the variable _hat must be statistically significant and the variable _hatsq must not have much predictive power except by chance that is, it must not be statistically significant at 0.05. Also, as depicted in Table 5 the _hat is statistically significant and _hatsq is not statistically significant at 0.01 and 0.05 respectively. The statistical significance of _hatsq 0.1 level of significant is an indication of nothing but a weak importance. Conclusion can thus be drawn that the model is correctly specified. Analysis of Effect of Credit appraisal policy and Collection policy on Loan Performance among Microfinance Banks in Kwara State To achieved research objective and test the study hypotheses Linear Probability Model known as Ordered Logit Model with Average Partial Effect was employed. The model is tagged “model for loan performance”. In the model for loan performance, the study dependent variable is categorical and can be ordered, taking values of 1, 2, 3, 4 and 5 if the loan performance status for the MFBs is Loss, Doubtful, Substandard, Pass and watch, and performing respectively. The set of explanatory variables are also categorized in this model into Credit Appraisal Policy and Collection Policy. Table 6: Ordered Logit Regression Model of Lending Policies Effects on Loan Performance VARIABLES Coefficients p-value CRPP 0.0316 0.683 (0.0773) CPY 1.126** 0.034 (0.527) Observations F-statistic Pseudo R-squared 135 7.10 *** 0.4958 Wald test 8.15*** 9 Jackknife Robust Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 Source: Author’s Computations, 2022 Estimation of the model was done with Jackknife robust estimates of standard errors to take care of the probable heteroskedasticity that may affect it. The results reveal F-statistic value of 7.10 with p-value of 0.01 indicating that the overall model is significantly explaining the probability of loan performance of MFBs. Reported pseudo R-squared of 0.4958 also shows that the independent variables (lending policies) explain the dependent variables to a fairly large extent. The Wald test of joint significance for all the two lending policies shows value of 8.15 which is statistically significant at 0.01. Therefore, all lending policies (Credit Appraisal Policy and Collection Policy) are jointly significant in influencing loan performance. On the one hand, from the estimation results of the ordered logit regression of the model in Table 6, Loan Collection Policy is statistically significant lending policy affecting the probability of loan performance of MFBs as evident from each of their low probability values. On the other hand, Credit Appraisal Policy is statistically insignificant policy affecting the probability of loan performance of MFBs (with higher probability values than conventional significance level). More specifically, the MFBs‟ Collection Policy has increased probability of having a loan performing. Table 7: Average Partial Effects after Ordered Logit Regression of Lending Policies Effects on Loan Performance Loss Doubtful Substandard Pass and Watch Performing Variables Coef p-val Coef p-val Coef p-val Coef p-val Coef p-val CRPP -0.004 0.578 -0.0006 0.555 0.0009 0.572 0.002 0.795 0.026 0.132 (0.008) (0.001) (0.003) (0.03) (0.009) CPY -0.098** 0.038 -0.043* 0.075 0.032** 0.001 0.132* 0.067 0.034*** 0.003 (0.028) (0.022) (0.007) (0.074) (0.006) Jackknife Robust Standard errors in parentheses *** p<0.01, ** p<0.05, * p<0.1 Source: Author’s Computations, 2022 Average partial effect, after ordered logit results, in Table 7 shows how each of these factors affects the likelihood of each of the loan performance status. From the loan performance model, the MFBs‟ Loan Collection Policy significantly reduces the likelihood of recording a loss loan This indicates that MFBs‟ Collection Policy have lower possibility of loan being loss by 0.098 probabilities. For doubtful loan status, Collection Policy significantly reduce the likelihood of microfinance bank loan having doubtful status. This indicates that Collection Policy has possibility of reducing the doubtful loans by 0.043 probabilities. For substandard loan status, the average partial effect shows that Collection Policy significantly increases the likelihood of recording a substandard loan. This indicates that MFBs‟ Loan Collection Policy has higher possibility of loan being substandard by 0.032 probabilities. Regarding the pass and watch loan status which is very close to performing, Table 7 reveals that Collection Policy significantly increases the likelihood of microfinance bank loan being 10 pass and watch status. This indicates that MFBs‟ Collection Policy increases the possibility of loan being pass and watch by 0.132 probabilities. For the performing loans status, Loan Collection Policy is an important factor that influences the likelihood of bank loans performing. This indicates that MFBs‟ Loan Collection Policy increases the possibility of loan being performing by 0.034 probabilities. Summary of Hypothesis Testing Table 8 below depicts the summary of the results of the hypotheses tested, which show the rejection or otherwise for each of the hypotheses relating to Lending policies and Loan Performance among Microfinance banks in Kwara State. Table 8: Summary of Hypothesis Testing Numbering Hypotheses Techniques Findings Remarks Ho1 Credit appraisal policy does not have significant effect on the loan performance among deposit taking MFBs in Kwara State. Ordered logit Insignificant P-value= 0.683 Not rejected Ho2 Collection policy does not have significant effect on the loan performance among deposit taking MFBs in Kwara State. Ordered logit Significant (+ve) P-value= 0.034 Rejected Source: Author’s Compilation, 2022 Table 8 shows that the results of the study offer full support for the rejection of one out of two study hypotheses. The rejection of hypothesis implies that the explanatory variable influence the probability of loan performance of MFBs. It follows therefore that Loan Collection Policy of MFBs influences their loan performance at 5% level of significance while the credit appraisal policy does not influence their loan performance even at 10% level of significance. However, for all the lending policies, the Wald test reveals a value of 8.15 with p< 0.01 implying that all the policies are jointly important in influencing the loan performance for the MFBs in the study area. The consistency or otherwise of these findings with the theories and previous studies are discussed in the subsequent section in the study. Discussion of Findings This section is devoted to discussing the findings that emerged from the results of this study, particularly, those from the results used to verify the hypotheses of this study. As revealed in the results that the first hypothesis, which states that credit appraisal policy does not affect loan performance of MFBs in Kwara State, is not rejected, the findings of this study in this situation imply that credit appraisal policy has not been effective in determining the performance of loans granted by MFBs in Kwara State. This finding does not conform to the stated a priori expectation of this study, which was postulated that credit appraisal policy will increase the loan performance of these microfinance banks. Furthermore, the finding does not conform to the studies of Wondimagegnehu (2012), Addae-Korankye (2014), Ngeno (2017), Namutenda and Muturi (2017), as it was in revealed in these studies that credit appraisal has effect in reducing non-performing loans and enhancing better performance of loans given out. Further findings of this study revealed that loan collection policy has positive impact on loan performance of MFBs in Kwara State. This finding suggests that the second hypothesis is rejected and consequently makes the finding to conform to the a priori expectation of this study which was postulated that collection policy will increase the loan performance of these 11 MFBs. This finding is also in line with the findings of the Wondimagegnehu (2012) and Namutenda and Muturi (2017). This finding implies that effective collection policy put in place by these MFBs have been able to enhance the retrieval of granted loans as at the due dates and has in turn promote the increase in the level of loan performance of these MFBs. 5. Conclusion, Policy Implication and Recommendations The study concluded that the collection policy developed by MFBs in Kwara State has been very effective in helping them to reduce their amount of non-performing loans they experienced from their customers and consequently increase the amount of performing loans they experienced. However, that credit appraisal policy put in place by microfinance banks in Kwara State has not been effective in determining the performance of loans granted by these microfinance banks. A policy implication which may be drawn from this study is that inadequate and ineffective credit appraisal practices remain the bane of incessant non- performing loan usually recorded by MFBs in Kwara State. The inadequacy and ineffectiveness of credit appraisal procedure might stem from the fact that, policies put in place by managements of these MFBs have not taken into account, key issues that can enable them to screen out loans that have strong tendency of becoming non-performing. These issues include proper investigation of the loan applicants‟ past financial history, capital contribution, financial capacity, collateral adequacy, financial literacy and social engagements and the lending conditions, all of which can determine his or her loan repayment behaviour. The study recommended that the credit appraisal policies of microfinance banks in Kwara State should be restructured and strengthened to capture the relevant information which will help these banks to determine the default intent of customers. Also, collection policy should be monitored further in order that its effectiveness in increasing loan performance is improved. This should be done with increased and consistent reminder on the consequence of loan default and the benefits in timely repayment. References Abugah, W. K., Michael, N., & Odoyo, (2017). Effects of Lending Policies on Loan Performance of Selected Commercial Banks in Kisii County, Kenya. International Research Journal of Advanced Engineering and Science, 2 (3), 270-273. Addae-Korankye, A. (2014). Causes and Control of Loan Default/Delinquency in Microfinance Institutions in Ghana.American International Journal of Contemporary Research, 4(12), 112-120. Arhin, E., Issifu, R., Akyeampong, B., & Opoku, I. N. (2019). 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