Small loans, big dreams: unpacking the critical role of lending offices in microfinance contracts Open Access

At least 20 years ago, credit facilities were not accessible to Pakistan's poor without assets or collateral. To obtain credit facilities, those who are less fortunate must get in touch with respectable moneylenders. In contrast, poor people can now get credit facilities from microfinance institutions (MFIs) in the form of small loans without any assets or collateral, thanks to the development of microfinance organizations. One of Pakistan's most potent tools for combating the rising levels of poverty is MFIs. The Pakistani MFIs then rapidly started to compete with one another. As a result, the topic of loan payback performance is of interest to many financial authorities and academics. However, currently, Pakistan has three different types of banks offering credit: commercial banks, specialized banks and microfinance banks. All kinds of banks experience loan payback issues, but MFIs experience the problem to a considerably greater extent. According to the State Bank of Pakistan, non-performing loans from commercial banks climbed by 63.08% over the last five years (2017–2021). Similar to this, specialized banks' non-performing loans increased by 0.67% over the previous five years. Additionally, during the past five years (2017–2021), non-performing loans from microfinance banks have increased by 436.39% (State Bank of Pakistan). The figures on non-performing loans cited above show that microfinance banks have much more serious problems with loan repayment than commercial banks and specialized banks.

The largest number of non-performing loans is endangering Pakistan's banking industry. Although cash is a part of the assets, when cash or loans cannot be covered, it affects liquidity risk and credit growth, which puts the bank into trouble. Problems with loan repayment are equally important to MFIs and borrowers. In situations where loan default and growing loan delinquency are present, borrowers are unable to receive further credit at a marginal interest rate. When loan payback rates are lower, MFIs experience client losses in addition to financial losses as a result of declining profitability and liquidity. In terms of outreach, the rising trend of loan default and delinquency has had a detrimental effect on the viability of MFIs and banks. The weak loan repayment portfolio has also undermined the trust of the external donor. As their capacity to exist, grow and maintain stability depends on their ability to repay their loans, MFIs must be able to do so. The performance of loan repayments is a crucial concern for the banking sector, especially for MFIs.

A growing number of regulatory agencies and the scholarly community in Pakistan are paying attention to the issue of loan repayment performance. Redzuan et al. (2023) recently did a study to determine the effects of internal (HR capacity, operational cost and innovation) and external (competition, language and awareness) factors on loan repayment performance in the setting of Pakistani MFIs. Meanwhile, Iqbal and Rao (2023) found significant impact of borrower characteristics (gender, age, group or individual loan and saving of borrower), loan characteristics (interest rate, purpose of loan, frequency of interest rate and frequency of principal payment of loan) and lender characteristics (lag time between loan applied and loan approved, difference between amount of loan applied and approved, difference between time of loan applied and approved, visiting frequency of lending officer, provision of training and operational assistance) on loan repayment performance in the context of Sri Lankan economy. Similarly, Nkundabanyanga et al. (2017) validate the positive and significant impact of financial management and competitive advantages on loan repayment performance. Likewise, Shah et al. (2023) found a significant effect of multiple variables (age, education level, gender, size of family, purpose of loan, loan size, loan processing and disbursement time and location of borrower business premises) on loan repayment performance.

In light of this, Charles and Mori (2017) confirm the importance of the link between multiple borrowing, progress lending and loan repayment efficiency. It is interesting to note that Umar and Sun (2018) demonstrated how macroeconomic variables like interest rates, discount rates, currency rates, inflation rates and unemployment rates have a big impact on how well MFI borrowers repay their loans. Additionally, Singh and Kapoor's (2019) research support the detrimental effects of opportunity cost (travelling time, meetings, training sessions and time spent visiting bank offices), real cost (travelling expenses, photocopying fees, revenue stamp costs and stationery costs) and real cost (travel expenses) on loan repayment performance in the context of Indian MFIs. Therefore, in the context of Pakistani MFIs, Iqbal, Rao and Studies (2023) also discovered a large and favorable effect of social capital and loan credit terms on client–business performance (CBP) as well as on client loan repayment performance. Furthermore, Iqbal et al. (2021) quantified the considerable and advantageous effects of serial borrowing on levels of over-indebtedness and loan repayment success. In addition to the moderating effect of moral hazard on the association between over-indebtedness and loan repayment performance, he reported the mediating role of over-indebtedness between multiple borrowing and loan repayment performance.

As there is a significant difference between the lending procedures of commercial banks, specialized financial institutions and MFIs. There is no question that loans are a common service provided by all different sorts of banks, but each bank's lending methods are unique. To compare the operational procedures of banks and MFIs about managing the loan portfolio, which includes loan approval, distribution and collection operations. The main difference between commercial banks and MFIs is the requirement for collateral as security. There is no requirement for loan collateral for MFI loans, unlike commercial banks and specialized banks. In-depth examination, several procedures, including the borrower's reputation, financial background and enforcement of collateral, are all things that commercial/specialized banks do. Strong internal applications that weed out dangerous concepts are used to accomplish this. If a loan is approved, the funds are disbursed by the banks in one or more instalments (Iqbal et al., 2020).

MFI loans, on the other hand, are often issued to individuals or organizations from various geographical locations without much inspection. The peer group participants carry out the oversight and examination and “peer pressure” serves as collateral because it reduces the risk of default (Iqbal et al., 2020). The commercial/specialized bank has a strict collection mechanism. Banks can collect the loan amount in the event of nonpayment by forfeiting the collateral, but MFIs are not covered by this clause. As a result, the ratio of loan delinquency and loan default has increased significantly. Additionally, lending officers play a minimal role in approving or rejecting loan applications because commercial banks and specialized banks follow a uniform process. The loan will be approved based on the advice of the lending officer's credit evaluation, in contrast to MFIs, where the lending officer plays a substantial role in accepting or rejecting the loan application. Therefore, in the case of MFIs, loan repayment success is largely dependent on the lending officer's function, which includes the accuracy of the credit evaluation, integrity and experience in the field of banking. However, previous research rarely looked at the impact of procedural deficiencies (PD) and Malpractices in credit assessment on loan repayment problems and client firm success in the context of Pakistani MFIs.

Pakistan's microfinance industry is built on ethics and trust, with a focus on the accountability of lending officials and borrowers alike (Adusei, 2021). Lending staff thoroughly assess each borrower's creditworthiness before extending a loan based on trust (Ali et al., 2023). The strict ethical guidelines established by microfinance organizations serve as the basis for this rating (Berns et al., 2021). As a result, it is the major duty of borrowers to uphold the same moral principles and openly reveal their financial situation and business position (Berns et al., 2021). Lending officers must simultaneously maintain the highest ethical standards in their evaluations to guarantee impartial and accurate assessments of borrowers' creditworthiness. This mutual adherence to ethics fosters a reliable and sustainable microfinance ecosystem (Tadele et al., 2022).

Thus, loan repayment problems remain a critical concern for MFIs, particularly in developing economies where credit access is expanding rapidly but institutional controls are often weak. While existing literature has explored various financial and behavioral determinants of repayment performance, limited attention has been given to how internal institutional practices – specifically PD and malpractices in credit assessment – shape borrower outcomes. This study addresses this crucial gap by examining not only the direct effects of these internal inefficiencies on loan repayment problems but also the mediating role of CBP and the moderating effect of lending officer experience. Unlike prior studies that tend to focus on borrower-related factors or macroeconomic influences, this research emphasizes the operational realities within MFIs and their downstream consequences. The novelty of this work lies in its integrated approach: combining procedural and ethical dimensions of lending with performance-based and behavioral mediators/moderators to produce a more comprehensive model of loan repayment dynamics. By identifying how institutional failures and human factors jointly affect credit outcomes, this study offers fresh theoretical insights and practical relevance, contributing new knowledge to both academic literature and financial practice.

As a result, this study addresses the following eight important questions: (1) Does procedural deficiency made by the lending officer during credit assessment have a significant impact on MFIs' CBP? (2) Do malpractices in credit assessment significantly affect the client's business performance of MFIs institutions? (3) Does the loan repayment problem significantly affect the procedural deficiency made by the lending officer during credit assessment? (4) Does the loan repayment problem significantly affect the malpractices in credit assessment made by the credit officer? (5) How do procedural shortcomings and issues with loan repayment relate to CBP? (6) How does the client's business performance play a balancing act between malpractices in credit assessment and loan-repayment problems (LRP)? (7) Does the lending officer's professional expertise play a mitigating influence in the relationship between PD and LRP? (8) Does the lending officer's professional-experience (PE) have a moderating impact on the relationship between malpractice in credit assessment and LRP?

The remainder of the research paper is structured as follows: Section 2 presents a review of the literature, a hypothesis and numerous theories that have been utilized to support this study. The research technique is described in Section 3 of this article. The study's findings will be presented in Section 4 in light of the literature and theory, whereas discussion, conclusion, limitation, implication and the research's future direction are given in Section 5 of this article.

The quantitative variables under inquiry are supported by a variety of theories in this study. The information on the theories used to support this investigation is provided in the following parts, along with pertinent literature on the variables that are being considered in this study.

The agency theory is the first theory that is applied in this study. According to agency theory, both the principal (higher-level management of MFIs) and the agent (lending officer) have aims that are out of sync. As a result, neither party has adhered to the letter or the spirit of the contract (Adusei, 2021). The higher-level management of MFIs and the agent (lending officers), both parties to the contract, are not working together and pursuing their interests as a result of the MFIs' continuously falling loan-repayment performance in Pakistan (Ali et al., 2023). By this idea, the principal (higher level management of MFIs) and agent (lending officer) have distinct goals, which causes motivation levels to differ in various ways. As was said in the introduction section, the lending officer's credit evaluation is a key factor in the choice to lend in the case of MFIs (Moya-Dávila and Rajagopal, 2020). Accordingly, the lending officer has a big impact on the lending practices of MFIs. In Pakistan, a large number of lending officers made credit assessments of the clients based on favoritism and nepotism (Berns et al., 2021). Additionally, it was discovered that some lending officers broke fundamental MFI credit assessment rules for their own gain and caused issues with agency costs by accepting bribes or commissions (Berns et al., 2021).

The Asymmetric Information Theory is the second theory applied in this investigation. Asymmetric information describes instances where one party has greater knowledge than the others, but the other parties involved do not. Information asymmetry occurs when the higher-level management of MFIs has access to far more information about lending practices than the newly hired lending officer who performed credit assessments in the context of lending decisions (Berns et al., 2021). This theory contends that when lending officers and upper-level management disagree about the facts at hand, a poor credit evaluation results, which in turn causes MFIs in Pakistan to perform worse in terms of loan repayment (Tadele et al., 2022). The Fraud Risk is the third theory that was used in this study. According to the fraud risk theory, phantom loans, kickback schemes, bribery and the lending officer's failure to record client repayments are the main sources of fraud in microcredit operations. In Pakistan, a sizable portion of lending officers engaged in corrupt activities, which had the effect of lowering MFI loan-repayment performance (Blanco-Oliver et al., 2023).

According to Chichaibelu and Waibel (2017), a sizable portion of MFI lending officers were discovered to be engaging in corrupt practices and had approved loan applications from borrowers who, based on MFI standard operating procedures, were not eligible for loans and later proved unable to fulfil their contractual obligations. As per findings of Shreya (2021), an excessively indebted borrower or client “consistently fails to fulfil payback dates and structurally needs to make disproportionately large sacrifices due to his/her loan commitments,” and the primary causes of these failures were the lending officer's poor credit assessment made for commission or bribery. According to Rehman et al. (2024), the lending officer's bad client selection increases over-indebtedness, which results in subpar business success and subpar loan payback performance. Wahab et al. (2024) proclaimed that PD and malpractices in credit assessment did not matter in the context of CBP. They additionally stated that the client's effectiveness and their capacity to manage the firm mattered most when it came to loan-repayment performance. According to Charles and Mori (2017), lending money to a successful business unit has an impact on how well a company performs. Even when such a company unit offered bribes or commissions to meet needs, it had little to no effect on their ability to operate profitably and return loans.

Meanwhile, Rizvi Jafree et al. (2023) discovered a similar disparity between borrowers who obtained loans based on merit and those who received loans in exchange for paying a commission to the lending officer. Similar to this, the business success of borrowers who obtained loans on the basis of merit outperformed borrowers who received loans as a result of favoritism and nepotism. According to Matzanke (2014), the majority of microenterprises struggled to manage their business operations because the lending officer kept a sizable amount of the debts as commission or bribes. According to Charles and Mori (2017), borrowers who obtain loans by breaking the rules and regulations of financial institutions eventually struggle to run their businesses because a sizeable portion of the loan amount is used to manage their credit assessment report by paying a commission to the credit officer. Additionally, some borrowers received larger loans based on inaccurate credit assessments; as a result, these borrowers were unable to generate a sufficient return on their investment and were hit with non-performing loan notices (Afonso et al., 2017). According to Charles and Mori's (2017) research, borrowers who managed their credit assessment report through the lending officer were unable to run their businesses successfully due to capital rationing because they were required to pay the lending officer a sizable amount of the loan as commission or a bribe. In addition, PD in credit assessment, such as weak risk evaluation and poor documentation, hinder timely and accurate lending, negatively affecting CBP by limiting access to necessary funds (Raza et al., 2024). Additionally, malpractices like favoritism and bribery distort credit allocation, leading to financial stress and reduced operational efficiency for deserving businesses (Negi, 2025). Thus, based on these justifications and earlier empirical data, the following hypotheses were developed:

The main reasons for problematic loans in MFIs, according to this study, were lax credit evaluation, improper appraisal and a lack of credit management policy (Jafree and Mustafa, 2023). Additionally, many MFI personnel accepted commissions or bribes from clients as a result of their poor salaries and eventually lost the moral reason for receiving loan repayments from consumers (Azim et al., 2017). However, because of the difficult credit evaluation process, most borrowers gave the lending officer additional funds and utilized a sizable percentage of their loans to comply with the lending officer's illegal demands (Mia et al., 2019). Similar to this, if borrowers expressed resistance to the illicit payment as bribes, lending officers threatened and placed pressure on them (Kassim and Rahman, 2018). Additionally, insider lending is a substantial contributor to loan default and delinquency in the context of microfinance. Insider lending was identified as the primary cause of subprime loans, which contributed to the demise of MFIs and the borrowers (Naz et al., 2024). Another significant obstacle to the MFIs in Pakistan's loan payback performance is the extremely poor knowledge level of the available human resources, which is insufficient to run this process smoothly (Omidiji et al., 2025). MFIs are substantially impacted by loan payback issues due to poor supervision and violations of the fundamentals of microfinance during the credit assessment. While this was going on, lending officers' insufficient credit assessments of the borrowers’ exposed holes that ultimately led to loan default and delinquency (Iqbal et al., 2021). Officers, nonetheless, are typically in charge of the poor client loan selection. When evaluating a borrower's credit, lending personnel frequently act against the fundamental rules of lending in order to further their interests. The lending officer might have, for example, coerced lending to meet a target or granted the loan based on partiality and nepotism after receiving a commission or bribe from the customer. As a result of the aforementioned factors, the lending officer lost moral justification for accepting a loan from the borrowers at its maturity and ultimately ran into loan payback issues (Charles and Mori, 2017).

Additionally, the ratio of borrowers to lending officers significantly and favorably affects loan default and delinquency. Prior to now, MFIs have let profitability take precedence over their primary goal of eradicating poverty. As a result, every MFI strives to reduce costs to increase profitability by placing an increased burden on lending officers from clients and the ratio of borrowers to lending officers steadily rises, leading to quick decision-making and subpar credit evaluation (Iqbal et al., 2021). The majority of credit department workers, especially branch managers, operations managers and lending officers, violate the fundamental guidelines for loan approval and disbursement after receiving a commission from the borrowers in the form of a predetermined percentage. In this instance, borrowers failed to put the loan's proceeds to their intended use. The lending officer may lack the moral authority to demand full repayment of the loan. Additionally, some lending officers who engage in insider lending obtain loans for their businesses before later declaring such loans to be bad debts (Sinha and Ghosh, 2022). However, the findings of this study did demonstrate that the behavior and operational procedures of the lending officer also influence the issue of loan recovery. If the lending officer and other microfinance bank management are not optimal and careful, the non-performing loans (NPL) ratio will rise and vice versa (Otiti et al., 2022). Credit is given based on orders from above, sacred letters or katabolic (credit command), and this is seen as the outcome of a conspiracy, implying that the NPL issues are brought on by any oversight or odor of collusion, where more than 90% of crimes are committed in the bank's collaboration with the people in the area (Kebede et al., 2023). As a result of the lending officer's sanction of false credit and commission or bribery obtained by the lending officer, this investigation concluded that the lending officer's authority to collect the loan was compromised (Ghosh et al., 2020). During the assessment of borrowers' creditworthiness, lending officers should adhere strictly to the ethical standards of the microfinance economic system (Ali et al., 2023). By avoiding PD and malpractices, they ensure a fair and accurate evaluation process (Berns et al., 2021). This ethical approach not only upholds the integrity of the microfinance system but also enhances loan-repayment performance by fostering trust and accountability between borrowers and lenders. Consequently, it supports a more robust and sustainable financial environment for all stakeholders involved (Iqbal et al., 2021). However, PD in credit assessment, such as weak borrower evaluation and poor documentation, often lead to LRP by allowing high-risk clients to receive credit (Behera and Mohini, 2025). Malpractices like bribery and favoritism further worsen the issue by enabling unqualified borrowers to access loans, increasing default rates and non-performing loans (Iqbal and Rao, 2023). However, the following hypothesis has been put out in this regard based on past research and the accessible literature.

Credit evaluation played a crucial role in MFI lending procedures, and approving loans based on subpar business performance results in bad loans (Blanco-Oliver et al., 2023). On the other hand, most lending officers neglected to assess the borrowers' company performance as a result of their hasty decisions, and these loans led to problems with repayment (Joseph and Quayes, 2024). Similar to this, lending officials' corruption at the expense of MFIs through bribes, commissions, poor credit evaluation, insider lending and the sanctioning of loans based on nepotism has significantly hampered MFIs' capacity to recoup their loans (Azim et al., 2017). It is noteworthy to observe that the lending officer was not always strictly compliant with the lending process. Before approving a loan, the lending officer typically did not visit the client's place of business but instead made the choice based on the client's poor credit, an inaccurate credit evaluation or in opposition to a disputed business unit (Adusei and Adeleye, 2024). A percentage of the loan amount was taken as “sule,” or bribery, by lower-middle-level and middle-level employees, which had a negative effect on loan payback performance. Owing to a lack of moral authority following this incident, bank management was unable to enforce the loan agreement's terms and conditions on the clients. Additionally, some lending officers approved phantom bank loans for their clients' firms even though they had no business plan. Additionally, some bank staff approved phantom loans to pay off existing debt or demonstrate questionable loan payback performance (Bote et al., 2024). Additionally, it was noted that some MFIs have diverted from their social objective of eradicating poverty and switched their attention to more commercial lending, which has a higher repayment rate than the standard lending practices (Redzuan et al., 2023). Furthermore, when compared to the lending officer's dishonest actions, procedural flaws and minor documentation problems have little impact on the repayment rate. However, due to inadequate managerial ability, MFIs/ Microfinance Banks (MFBs) were unable to create innovative, competitive products that could meet the specific needs of microfinance customers (Bedaiwy and Peter, 2022). It is interesting to note that this analysis held banking systems accountable for non-performing loans when applied to MFIs. He continued by saying that microfinance bank lending officers lack adequate financial literacy, making it impossible for them to accurately assess a client's credit in light of banking procedures and, ultimately, preventing them from offering the borrowers any operational assistance that would improve their business performance (Parvin and Birner, 2022).

This study did point out a few procedural flaws that increase loan default and delinquency. These factors primarily include a lack of aggressive credit collection tactics, a quick decision to grant loans and insider lending, all of which have a significant impact on how well borrowers repay their loans if the lending officer fails to assess the borrower's business capacity in terms of profitability and sales (Kassim and Rahman, 2018). In the case of the MFIs industry, the problem of loan default and delinquency was often explained by adverse selection brought on by information asymmetry. In the context of the MFIs contract, similarly, the borrower lacks knowledge of the lenders, while the lender lacks knowledge of the borrowers (Jafree and Mustafa, 2023). Occasionally, borrowers who gave bribes for loans had better loan payback records than those who did not because they received their loans on time and benefited from possibilities for small businesses (Lamichhane, 2021). Minor documentation errors can cause issues for the borrowers if they are not remedied promptly. On the other hand, loan officials occasionally used delay strategies while authorizing loans and then afterwards demanded commission from the borrowers. Borrowers occasionally missed small business opportunities as a result of the lending officer's pitiful approach, which hurt both their business performance and loan-repayment performance (Iqbal et al., 2021). In a few instances, it was also shown that the borrowers handled additional funds from their commercial activities to pay the lending officer's illegal demands or payments, which were made to him as bribes. Similar to this, borrowers keep a positive connection with the lending officer through bribery, allowing them to receive additional concessions from the lending officer, such as timely loans, readjustments, concessions and grace periods, among other things (Charles and Mori, 2017). Additionally, the additional funds given as bribes to the lending officer led to a decrease in the amount of capital needed to conduct the business affairs, which ultimately had an impact on the performance of the enterprise in terms of sales and profitability (Iqbal et al., 2020). The results of this study intriguingly revealed that bribes given to lending officers might promote client repayment, provided the lending officer promptly provides a loan facility and the borrower generates sufficient cash from better business performance to pay off the various debt obligations. Additionally, in some instances, clients enhance the operation of their businesses by promptly utilizing a credit facility and by coordinating the repayment schedules for all of their obligations with their cash inflows and outflows (Sakyi-Yeboah et al., 2025). Thus, the CBP mediates the link between PD and LRP, as weak assessment processes reduce business efficiency, leading to higher default risks (Blanco-Oliver and Irimia-Diéguez, 2021). Similarly, malpractices in credit assessment harm business outcomes, which in turn contribute to repayment failures (Alfa et al., 2024).

Another important component that significantly affects loan repayment issues is the lending officer's performance and effectiveness. This study found that a more seasoned lending officer improved credit evaluations by minimizing documentation errors, which improved loan repayment performance (Okpukpara et al., 2023). However, a less qualified and experienced lending officer was unable to evaluate the borrowers' creditworthiness by the lending policy and left gaps in the paperwork process that made it difficult to reclaim the loan when it was due (Kassim and Rahman, 2018). Additionally, an experienced lending officer aids in the control of problems related to poor loans by eliminating procedural errors and delays (Mia et al., 2025). However, a novice lending officer was unable to comprehend the mindset of borrowers and the fundamental elements of lending products and during the product development phase, he or she did not offer useful suggestions to create a compatible product that effectively met the needs and desires of borrowers. Last but not least, the lending officer interacts directly with borrowers and has a greater awareness of the procedural flaws and dishonest behavior that ultimately result in difficulties with loan repayment (Kebede et al., 2023). The officer has also noted the link between errors in credit evaluation and issues with loan repayment in this study on the moderating function of lending. The results of this study did, however, show that the younger and less experienced individual is initially more mindful about the career and did not receive bribery from his clients. Therefore, the link between malpractices and loan repayment performance was unaffected by youthful and less experienced employees. On the other side, an expert may be more aware of the system's flaws and demand bribes from borrowers to approve loans (Iqbal et al., 2021). Intriguingly, this study discovered that younger and less experienced lending officers who are more concerned with their career development completed all formalities and procedures during the credit assessment and made every effort to reduce loan repayment issues by carrying out all responsibilities and policies set forth by the MFIs for credit assessment and loan sanctioning (Rizvi Jafree et al., 2023).

However, the results of another study indicated that a senior lending officer with greater experience understands different borrowers' behaviors better and makes better assessments of the clients' credit ratings based on their experience, which may ultimately reduce the likelihood of loan delinquency and default because of their judgment (Rehman et al., 2024). Additionally, it was found in this study that if a lending officer has previously worked as a lending officer and shares their former expertise in this field with their new employer, PE has a significant influence on the association between procedural faults and loan-repayment concerns (Iqbal and Rao, 2023). The ratio of non-performing loans is also greatly influenced by the experience of the lending officers because they are more knowledgeable about the lending process and execute better credit assessments as a result of their extensive lending expertise. Additionally, this study hinted that skilled lending officers can also engage in dishonest behavior because they are aware of systemic flaws (Wahab et al., 2024). However, the effectiveness and expertise of the MFIs' field staff also have a big impact on how well loans are repaid. At the same time, the majority of them are quite young and possess matriculation or intermediate education. As a result of their lack of experience, they are unable to handle the procedural errors that occur during credit evaluation. In addition to this, they engage in malpractices due to their lack of training and expertise in the banking industry (Kassim and Rahman, 2018). Additionally, the higher level of PE led to fewer payback problems and skill shortages during the credit evaluation. Regarding the moderating impact of lending officer PE on the link between credit assessment fraud and problems with loan repayment in MFIs, however, a mixed conclusion was reached (Masood, 2004). Contrarily, credit assessments made by those with less expertise had certain errors that contributed to the issue of loan default in the end. Increased expertise was connected to malpractices and corruption, though, which caused agency problems for the MFIs. However, a less experienced employee would be less familiar with the system and consequently be more reluctant to commit unfair activities (Nkundabanyanga et al., 2017). The majority of the lending procedure and credit assessment were handled using computerized software; therefore, the PE of lending officers had no impact on fraud and loan-repayment performance, among other interesting discoveries (Iqbal et al., 2021). During the credit assessment process, lending officers should prioritize the ethical standards established by microfinance institutions over their personal preferences or interests (Iqbal et al., 2021). Adhering to these ethical guidelines ensures fair, unbiased and transparent evaluations, which are crucial for maintaining the integrity and trustworthiness of the microfinance system (Kassim and Rahman, 2018). This practice not only enhances the accuracy of credit assessments but also fosters a more reliable and sustainable financial environment, ultimately improving loan-repayment performance and supporting the overall mission of microfinance institutions (Iqbal et al., 2021). Moreover, PE of MFI employees moderates the impact of PD by enabling staff to manage credit processes better, thus reducing loan-repayment problems (Githaiga, 2024). Similarly, malpractices have less influence on experienced employees, weakening the link between unethical assessments and repayment issues (Raza et al., 2024). As a result, the empirical data from earlier investigations support the wording of the following claim. Thus, the proposed relationship among the underpreparing variables is shown in Figure 1 

In this study, five reflected constructs, including PD, malpractices in credit assessment, CBP, LRP and PE of credit officer were used. All five of these constructs were evaluated using a five-point Likert scale, with information gathered using a structured questionnaire. The 316 middle-level employees of microfinance institutions who were separated into four useful groups – operations manager, relationship officer, credit officer and product manager – were used as the study's unit of analysis. They were chosen using stratified sampling approaches (Ahmadini et al., 2021). The final sample was then created by selecting 150 operations managers, 66 relationship officers, 55 credit managers and 45 product managers according to the sampling guidelines. This study used a two-stage structural equation modeling approach for additional data analysis. This strategy first examines the validity and reliability of the data gathering tool by utilizing an outer-model (measurement-model). Second, the relationship and impact of underpinning constructs will be observed through the inner-model (structural-model) application (Hair et al., 2019; Henseler et al., 2014; Hair et al., 2011). Indicator reliability of the data collecting tool will first be ensured by loading factors based on the threshold (>0.6) that are suggested by Oke et al. (2022) and Hair et al. (2021).

Second, Cronbach's alpha and composite reliability will be used to assure internal consistency reliability based on their recommended thresholds of (>0.6) and (>0.7), respectively, by both (Oke et al., 2022; Hair et al., 2021; Burns and Bursn, 2000; Lai, 2021). However, validity and reliability are connected, and reliability would not be useful until the instrument's validity was confirmed (Ahmed and Ishtiaq, 2021; Shafie et al., 2021; Oke et al., 2022; Kumar et al., 2021). To ensure the validity of the data collection instrument, two robust measures were used in this study. The first is the convergent validity, which will be assessed using the Average Variance Extracted (AVE) and the threshold value for AVE is recommended to be ≥0.50 (Hair et al., 2021). The Fornell–Larcker Criterion and the HTMT (Heterotrait-Monotrait) ratio are two separate measures that will be used to establish discriminant validity. The threshold values for these measures are (0.90) and are advised by the (Roemer et al., 2021; Hair et al., 2019; Oke et al., 2022).

In addition, multicollinearity is another problem that arises when two independent variables are correlated with each other. On the other hand, a problem known as multicollinearity might arise while processing data. Multicollinearity is a characteristic that makes it challenging to analyze results and generates methodological issues (Hair et al., 2019). If the Variance Inflation Factor (VIF) values of the construct's items are <3.30 and they are not correlated with one another, collinearity between those items is not an issue (Akinwande et al., 2015). The Coefficient of Determination (R2) technique was applied to measure the predictive power of the model. Finally, the inner-model (structural model) will be applied, and a bootstrapping procedure was then used to test a significant level of different path coefficients (β) using the p-value and t-value (Hair et al., 2017). T-Statistics (t-values) and p-values were developed due to the bootstrapping technique, allowing researchers to assess the significance level of the path coefficient (β). The standardized approach of bootstrapping was used in this study with a subsample size of 5,000 to assess the significance level of the path coefficient (β). The threshold for t-values was set to 1.96, and the threshold for p-values was set to (p < 0.01) at a significance level of (α) = 10%. (Henseler and Sarstedt, 2015). However, further details regarding statistical tools applied under the measurement model and structural model have been given in Table 1 and 2, respectively.

As it was earlier discussed in the methodology section, in this study, two-stage structural equation modeling techniques have been applied. Therefore, outcomes related to the outer-model (measurement-model) and inner-model (structural-model) have been presented in the following section, respectively.

Table 3 presents the Inner VIF values to assess common method bias among the study constructs. All VIF values range between 1.341 and 1.841, which are well below the common threshold of 3.3, indicating that multicollinearity is not a concern. This suggests that all values are <3.3, which means there is no serious issue of bias or overlap between the variables. This suggests the data are reliable, and the variables are measured separately and clearly. Inner-Model (measurement-model) as shown in Table 4 and Figure 2 indicated that values of factor loading of each item of all constructs are >0.60; therefore, indicator reliability has been established in this study. Similarly, in this study, internal consistency reliability has also been established as the values of Cronbach's alpha and CR (Composite-Reliability) of each construct, as mentioned in Table 4, are >0.6 and 0.7, respectively. Meanwhile, the issue of multicollinearity was also not found in this study, as the value of VIF of each item of the construct, as shown in Table 2, is less than the minimum threshold of 3.30. After measuring the reliability of the instrument, the AVE approach was applied to ensure the convergent validity and convergent validity in this case has been ensured as the value of AVE of each construct, as shown in Table 4, is greater than the threshold values (>0.50) as recommended after ensuring the convergent-validity two robust measured applied in this study to ensure the discriminant-validity of the data collection instrument. The outcomes related to the Fornell–Larcker criterion have been presented in Table 5, which indicates that discriminant validity in this case has been established as the values of this table are less than the minimum threshold of (<0.90). Likewise, discriminant validity through the HTMT (Heterotrait-Monotrait) is also established as the values of the HTMT ratio mentioned in Table 6 are less than the minimum threshold of 0.90.

In this study, the reliability and validity of the data collection instruments have been established as recommended by various researchers in the methodology section. Finally, inner-model (structural model) will be applied, and a bootstrapping procedure will then use to test a significant level of different path coefficients (β) using the p-value and t-value (Hair et al., 2017). Table 7 displays the model's ability to determine coefficients. The coefficient of determination (R2) tells us how much variation in the dependent variable is brought on by changes in the independent variables. The coefficient of determination (R2) is another sign of a construct or variable's ability to predict. Coefficients of determination (R2) values for the endogenous constructs were also evaluated to assess the predictive effectiveness of the study model. But (R2) also represented the total variance of all independent variables and assessed the model's anticipated efficacy (Hair et al., 2019; Hair et al., 2021). Subsequently, the value of R2 in this study is 0.162, which means that 16.2%% variance in the mediating variable (CBP) reported by the independent variables (PD and malpractices in credit assessment), considering the mediating role of CBP between all the independent variables (PD and malpractices in credit assessment) and the dependent variable (LRP). Whereas in the context of the direct effect, the R² value of R2 is 0.488, which indicates a 48.8% variance in the dependent variable (LRP) caused by the independent variables (PD and malpractices in credit assessment).

Table 8 and Figure 3 present the hypotheses testing results based on the significance of the path coefficients (β-Values), t-value and p-values. The first hypothesis (H1), which states that “PD have a positive impact on CBP,” is accepted (β = 0.167; t = 1.892; p < 0.059). It means PD can lead to delays in accessing critical funds, missed business opportunities and cash flow interruptions. As a result, affected clients may experience a decline in sales, reduced profit margins and an overall weakening of performance relative to their competitors, who face fewer procedural obstacles. Therefore, findings pertaining to hypothesis (H1) is consistent with several past studies (Wahab et al., 2024; Rizvi Jafree et al., 2023; Negi, 2025; Raza et al., 2024; Raza et al., 2024).

Meanwhile, the second hypothesis (H2), which suggests that malpractices in Credit Assessment have a positive impact on CBP was accepted (β = 0.302; t = 3.831; p < 0.000). Thus, when loans are granted based on flawed assessments rather than merit and business viability, deserving clients may either be denied access to needed capital or receive insufficient funds. On the other hand, poorly vetted clients may obtain financing but fail to utilize it productively. For legitimate businesses, this leads to reduced competitiveness, as they may face capital shortages, delayed expansion and disrupted operations. Ultimately, such malpractices harm CBP by undermining profitability, lowering sales and weakening their standing compared to competitors who operate under more transparent and equitable financial systems. The finding related to (H2) is further justified by various empirical studies that reported similar results (Wahab et al., 2024; Rizvi Jafree et al., 2023; Negi, 2025; Raza et al., 2024; Raza et al., 2024).

Similarly, the third hypothesis (H3), which recommended that “Procedural- Deficiencies (PD) have a positive impact on Loan-Repayment-Problems (LRP)” was accepted (β = 0.242; t = 4.838; p < 0.000). PD – such as delays in disbursement, unclear repayment terms, inconsistent loan monitoring and poor communication – can directly contribute to repayment challenges. When clients face uncertainty in loan processing or encounter administrative hurdles, their ability to plan and allocate borrowed funds effectively is compromised. Such inefficiencies may lead to cash flow mismanagement, missed investment windows and rising operational costs. These conditions reduce a borrower's financial capacity to meet repayment schedules on time. As a result, procedural weaknesses within lending institutions not only undermine the borrower's financial planning but also elevate the risk of default, leading to more frequent and severe LRP. The finding related to (H3) is further justified by various empirical studies that reported similar results (Jafree and Mustafa, 2023; Mia et al., 2019; Naz et al., 2024; Omidiji et al., 2025).

Although, the fourth hypothesis (H4), which quantified that “Malpractices in Credit Assessment have a positive impact on Loan Repayment Problems (LRP),” has also been supported by the bootstrapping results of the structure model (β = 0.214; t = 3.312; p < 0.001). It means, when loans are issued without careful scrutiny of the client's repayment capacity, financial health or business viability, the chances of a mismatch between loan size and repayment ability increase significantly. This can result in clients receiving more credit than they can handle or loans structured with terms that don't align with their actual cash flow patterns. Consequently, such flawed assessments contribute to poor loan performance, delayed payments and higher default rates, thereby directly increasing LRP for both borrowers and lending institutions. The outcome of this hypothesis (H4) is consistent with several past studies (Sinha and Ghosh, 2022; Otiti et al., 2022; Kebede et al., 2023; Berns et al., 2021; Behera and Mohini, 2025).

Correspondingly, the fifth hypothesis (H5), which specifies that the “Client-Business Performance (CBP) has a mediating role between the Procedural-Deficiencies (PD) and Loan-Repayment-Problems (LRP)” is rejected (β = 0.028; t = 1.480; p < 0.139). This finding suggests that while PD directly affect LRP, their impact is not channeled through CBP. One possible explanation is that PD may influence repayment behavior in ways that bypass business performance metrics – such as through administrative delays, lack of clarity in terms or inefficient support structures. Additionally, clients experiencing low profitability, poor sales and reduced performance relative to competitors may already be under financial stress, making them vulnerable to repayment issues regardless of procedural efficiency. In such cases, the direct burden of institutional inefficiencies overwhelms the potential buffering effect of business performance, rendering CBP an ineffective mediator in the PD–LRP link. The finding related to (H5) is in line with many past studies that reported similar results (Joseph and Quayes, 2024; Adusei and Adeleye, 2024; Bote et al., 2024; Parvin and Birner, 2022).

Likewise, the sixth hypothesis (H6), which indicated that the “CBP has a mediating role between the MPCA and Loan-Repayment Problems (LRP)” is accepted (β = 0.051; t = 2.294; p < 0.022). This result indicates that malpractices in credit assessment contribute to LRP indirectly by weakening CBP. When credit officers engage in unethical or negligent practices – such as overlooking accurate financial analysis, ignoring risk profiles or showing favoritism – borrowers may either receive inappropriate loan amounts or face terms unsuitable to their actual business needs. As a result, client businesses may suffer from misallocated resources, financial strain and an inability to capitalize on growth opportunities, ultimately leading to reduced profitability, lower sales and weakened competitive performance. This deterioration in business performance, in turn, increases the likelihood of repayment delays or defaults. Thus, poor credit assessment practices undermine borrower performance, which then fuels LRP through a clear mediating pathway. Therefore, findings pertaining to hypothesis (H6) are consistent with several past studies (Jafree and Mustafa, 2023; Sakyi-Yeboah et al., 2025; Alfa et al., 2024).

Although the seventh hypothesis (H7), which quantified that “Professional-Experience (PE) of MFIs employees moderate the relationship of Procedural-Deficiencies (PD) and Loan-Repayment-Problems (LRP)” has also been supported by the bootstrapping results of the structure model (β = −0.116; t = 1.910; p < 0.056). This finding suggests that experienced lending officers are better equipped to handle or compensate for procedural inefficiencies during the credit assessment process. Through their knowledge, judgment and familiarity with client behavior and credit risks, experienced officers can navigate unclear guidelines, spot potential red flags and ensure smoother loan processing even when formal systems are lacking. By reducing errors, delays and miscommunication during loan assessment and disbursement, they help maintain client trust and ensure better alignment between loan structures and client needs. Consequently, their expertise reduces the likelihood that procedural flaws will escalate into serious LRP, thereby enhancing institutional effectiveness and credit portfolio quality. The outcome of this hypothesis (H7) is consistent with several past studies (Okpukpara et al., 2023; Mia et al., 2025; Kebede et al., 2023; Rizvi Jafree et al., 2023).

On the other hand, the eight hypotheses (H8), which quantified that “Professional -Experience (PE) of MFIs employees moderate the relationship of MPCA and Loan Repayment Problems (LRP)” has also been rejected by the bootstrapping results of the structure model (β = −0.003; t = 0.039; p < 0.969). While one might expect experienced lending officers to reduce the negative impacts of malpractices, the results suggest a more complex reality. In practice, experienced officers often possess deeper knowledge of institutional procedures and system loopholes, which may inadvertently contribute to agency problems. Rather than mitigating malpractices, their familiarity with internal processes could allow them to bypass controls or manipulate credit assessments in favor of certain clients or for personal gain. As a result, although the direction of the effect is negative, the relationship is statistically insignificant, indicating that PE does not play a meaningful role in reducing LRP when malpractices are present in the credit assessment process. The finding related to (H8), is in line with many past studies that reported similar results (Rehman et al., 2024; Iqbal and Rao, 2023; Wahab et al., 2024; Githaiga, 2024; Raza et al., 2024).

The lending practices of MFIs in Pakistan are completely different from those of other banks. When it comes to MFI financing, the lending officer's credit assessment report is heavily weighted in the decision-making process. Therefore, this study considers the direct impact of independent variables (PD and malpractices-in-credit-assessment) on the dependent variable (LRP) and mediating variable (CBP). This study also finds the mediating role of CBP between the independent variables (PD and malpractices-in-credit-assessment) and the dependent variable (LRP). The moderating impact of the lending officer's PE on the relationships between procedural errors and loan-repayment issues, as well as between Malpractices in credit assessment and loan-repayment issues, is also considered in this study, which also considers the lending officer's influence on the lending decision. However, this study found that unethical lending practices and dishonesty on the part of lending officers during the credit evaluation considerably raised the rate of subprime loans (Kassim and Rahman, 2018). Additionally, MFI borrowers experienced issues managing their businesses as a result of the lending officer's unfavorable position in the context of procedural errors and fraud in the credit assessment (Iqbal et al., 2021). The research's findings also showed that procedural flaws and minor documentation mistakes had no effect on CBP, and as a result, clients' loan-repayment issues did not worsen at all (Bakar et al., 2020). However, this study discovered that MFI borrowers must pay the price for the lending officer's misconduct in the form of subpar company performance, which also affects loan-repayment performance (Blanco-Oliver et al., 2023). Additionally, this study discovered that the lending officer's professional competence lessened the influence of procedural errors and malpractices on loan-repayment issues. It implies that a lending officer with expertise would be familiar with the clients' lending policies and mindset. Therefore, by carrying out the lending policies of the MFIs in letter and spirit, the lending officer may contribute to decreasing the ratio of bad loans (Blanco-Oliver and Irimia-Diéguez, 2021).

As was previously mentioned, the lending methods of MFIs are completely distinct from those of other institutions in the banking industry. In the case of MFIs, the lending decision is mostly dependent on the credit evaluation report created by the lending officer. The role of the lending officer in the context of procedural errors, fraud in the credit evaluation process, subpar CBP and problems with loan repayment was rarely examined in prior studies (Hiena, 2020). However, the role that CBP plays in the context of procedural flaws, fraud in the credit assessment process and issues with loan repayment was also scarcely explored in the context of MFIs in Pakistan (Shreya, 2021). Additionally, this study considered the moderating effect of MFI employees' experiences on the link between the independent variables (PD and Malpractices in credit-evaluation) and the dependent variable, keeping in mind the significance of the lending officer (LRP) (Ali et al., 2023). The MFIs in Pakistan can learn a lot from the study's conclusions. Therefore, in light of the results of this study, MFIs might alter their lending practices and rules. The findings of this study may be used by MFIs to design a variety of operational assistance and training programs for their staff and consumers to improve loan payback performance (Ali et al., 2023).

There are obviously some drawbacks to this study. First of all, in this study, data were collected from the middle-level management of the MFIs (operations managers, relationship officers, credit officers and product managers) and input of other stakeholders (lower-level management, top-level management and borrowers) was not considered due to the time and other resource constraints (Iqbal et al., 2021). This study used a self-administered questionnaire, similar to other research, and no follow-up interviews with respondents were conducted to account for changes in the target population's behavior over time (Tadele et al., 2022). Likewise, econometrics types of study could not be conducted due to the secondary data constraints. However, other significant influencing factors that have a significant impact on loan-repayment performance were not considered in this study. These elements include the frequency of loan repayment, rental income, agricultural revenue, inherited assets and the number of borrowers' dependents (Ghosh et al., 2020). However, this study is based on the formal MFIs that are working in Pakistan. Whereas, someone may further expand the scope of this study to the informal MFIs and traditional money lenders. In addition, someone may consider the comparison of interest-free microfinance institutions in the context of South Asian countries. Furthermore, if secondary data are accessible, econometrics model types might be considered for additional research. Last but not least, a longitudinal study is also advised for in-depth investigation of the subject of loan-repayment issues in the context of MFIs in Pakistan (Iqbal et al., 2020). However, the summary regarding the key findings is given below in Table 9.

Agency theory discusses conflicts of interest and problems that arise when one person (the agent) makes decisions on behalf of another (the principal). In the framework of MFIs, when determining creditworthiness and allocating loans, the institution (agent) works on behalf of its clients (principals). Furthermore, improper credit evaluation procedures and practices can result in moral hazard, as MFIs take advantage of opportunities and put their interests ahead of those of their clients. For example, MFIs may grant loans without conducting the necessary due diligence fulfill personal incentives or meet disbursement targets, which would raise the default rate (Blanco-Oliver et al., 2023). Asymmetric Information Theory also draws attention to the issues that can occur when one party has access to more or superior information than the other. This hypothesis can explain why information asymmetries make it difficult for MFIs to appropriately evaluate a client's creditworthiness (Bakar et al., 2020). However, in the context of agency theory and asymmetric information theory, PD in credit assessment create a gap between lending officers (agents) and lending institutions (principals), leading to misaligned incentives and poor screening of borrowers, which increases the likelihood of loan defaults in Pakistan's microfinance sector (Ahmad, 2012). Moreover, malpractices such as favoritism and bribery exacerbate information asymmetry by concealing borrowers' true risk profiles, resulting in adverse selection and moral hazard, which directly contribute to LRP (Kore et al., 2024). These issues undermine the trust and efficiency of microfinance operations, reflecting the agency conflict and incomplete information typical in such financial relationships (Nordin et al., 2019).

Similar to this, when agency issues and information asymmetries combine, the assessment of credit is not ideal, leading to the approval of loans for high-risk clients. Owing to their potential inability to make good use of the loans, these clients are more likely to experience problems with business performance and financial hardship (Kendo and Tchakounte, 2022). Similarly, MFIs experience increased default rates as clients with subpar company performance find it difficult to repay their loans. This sets up a vicious cycle in which the institution's financial stability is jeopardized, which can result in tighter lending guidelines or higher interest rates, which would make it even harder for borrowers to make their repayments (Blanco-Oliver and Irimia-Diéguez, 2021). In a similar vein, recurrent procedural errors and misconduct can undermine client confidence in MFIs. Customers might stop interacting with MFIs, which would make it harder for the organization to assist regional economic growth and fulfill its goal of financial inclusion. In summary, resolving procedural flaws and malpractices in credit evaluation is essential to balancing the interests of MFIs and their clients, minimizing information asymmetry and enhancing overall business performance and loan payback results (Blanco-Oliver and Irimia-Diéguez, 2021). The sustainability and efficacy of microfinance organizations in fostering economic growth may be improved by this alignment (Ali et al., 2023).

The study looks at how credit evaluation errors and procedural defects affect CBP and loan-repayment concerns, with a focus on the moderating role of lending officer experience in MFIs in Pakistan (Ali et al., 2023). However, based on these study outcomes, MFIs should develop and implement standardized credit assessment protocols to minimize PD. This includes thorough vetting of client information, standardized risk assessment tools and regular updates to the credit assessment criteria based on market conditions and client feedback (Bakar et al., 2020). Likewise, in light of the findings of this study, lending officers should have access to ongoing training programs that provide them with the most recent information on credit assessment methods and resources. This lowers the likelihood of malpractices and guarantees that all officers follow best procedures (Lassoued, 2022). Furthermore, this study can assist in identifying gaps and opportunities for development by enabling the MIFs to establish methods for client input on the credit evaluation process. To improve evaluation processes and make sure they are client-centric, client insights can be helpful (Berns et al., 2021).

This study proposed ways to improve the overall efficacy of the credit assessment process, such as establishing mentorship programs wherein more seasoned lending officers coach less seasoned employees. This information sharing can aid in creating a more capable team that can lower malpractice rates (Adusei, 2021). According to this study, businesses can perform better by offering support to their clients both before and after loans are disbursed. To make sure that clients can successfully use the loan for business growth, this includes continuous advising services, financial literacy training and help with business planning (Iqbal et al., 2021). Additionally, proactive intervention can be aided by the development of early warning systems to identify client indicators of financial hardship. Then, in order to avoid defaults, lending officers might collaborate with clients to modify loans or offer extra assistance (Kassim and Rahman, 2018). It is also advised to strengthen the regulatory framework to impose strict credit assessment criteria on all MFIs in order to lessen procedural flaws and malpractices. Regulatory agencies may also be involved in keeping an eye on compliance and, if required, implementing corrective measures (Hiena, 2020). In conclusion, utilizing the expertise of lending officers to remedy procedural flaws and malpractices in credit assessment will greatly enhance CBP and lessen loan payback issues. These managerial and practical ramifications for microfinance institutions in Pakistan may result in better customer outcomes, more sustainable lending practices and sector growth overall.

To guarantee that microfinance contracts are successfully fulfilled, microfinance institutions might create thorough ethical standards or guidelines for lending officers as well as borrowers based on the study's findings (Iqbal et al., 2020). These guidelines should emphasize transparency, fairness and accountability in the lending process. For borrowers, the standards would include clear expectations for financial disclosure and responsible repayment behavior (Ghosh et al., 2020). For lending officers, the guidelines would stress impartiality, thorough evaluation of creditworthiness and adherence to institutional ethics over personal interests. Microfinance organizations may promote a culture of trust and dependability by putting these moral principles into practice. This will increase loan payback rates and ensure the long-term viability of their programs (Hiena, 2020).

Besides all these, this study offers critical insights for lending institutions aiming to reduce LRP by addressing internal shortcomings. The findings suggest that PD and malpractices in credit assessment contribute significantly to repayment issues, particularly when they undermine CBP. Therefore, improving procedural transparency, ensuring compliance with standard credit protocols and minimizing subjective or unethical lending practices can directly enhance borrower performance and repayment behavior. Moreover, the moderating role of lending officer experience highlights the value of investing in training and retaining experienced staff. Experienced officers may be better equipped to navigate procedural gaps or detect malpractice, thereby mitigating their negative effects on client outcomes. Financial institutions should consider integrating continuous professional development programs and stricter oversight mechanisms to reinforce ethical conduct. These practical steps help create a more robust, client-oriented lending environment that promotes long-term financial stability and reduces default risk.

Despite offering valuable insights into the institutional factors affecting LRP in microfinance settings, this study is not without limitations. First, the data were collected solely from middle-level employees of microfinance institutions, which may limit the generalizability of the findings. Frontline loan officers and senior management may hold different perspectives on PD, credit assessment practices and client interactions that were not captured in this analysis. Second, the reliance on self-reported data through structured questionnaires introduces the potential for response bias, particularly concerning sensitive topics such as malpractices in credit assessment. Additionally, while the two-stage SEM approach provides robust analytical power, it is still subject to assumptions of linearity and model specification, which may not fully capture the complex dynamics of real-world lending practices. Future research should consider incorporating multi-level data sources, longitudinal designs or qualitative methods to enrich understanding and validate these findings across broader contexts and stakeholder groups.

Future research could use a longitudinal design to expand on the results of this study and better understand the causal linkages that exist over time between procedural flaws, malpractices, business performance and loan-repayment issues. This would enable a more dynamic examination of the interactions and variations between these variables, offering more profound understanding of the long-term consequences of credit evaluation procedures. More studies should use objective measures of loan payback and business performance, such as financial records and repayment histories, to complement self-reported data and reduce biases. More specific insights may also be obtained by closely examining the effects of various procedural flaws and malpractices, such as poor client screening, incomplete recordkeeping or biased decision-making. Contextualizing the results and identifying larger trends may also be aided by looking into the impact of numerous external factors, such as changes in regulations, technology improvements and economic situations, on credit assessment procedures. Lastly, broadening the study's focus to include a comparative examination of MFIs in various nations or areas may offer insightful information on how environmental variables affect the connection between procedural flaws, corporate success and loan payback. In order to improve credit evaluation processes in a variety of contexts, this could assist in identifying best practices and provide guidance for policy recommendations.