Dr Arthur Sunday, Dr Abanis Turyahebwa, Dr Derick Ssekajugo, Dr Mabonga Eric
Abstract
Microfinance has evolved by providing micro credits to respond to the furthermost financial and non-financial needs of the citizens, to eradicate poverty and increase financial inclusion. Most studies undertaken in the past few years have focused mainly on outreach of MFI’s and their impact on profitability and not on internal control system and lack of clarity on the extent to which internal control system influences financial performance (Narver, 2007) will therefore continue to inhibit common understanding and explanation which might deter performance improvement in Ugandan microfinance institutions. Failure by MFIs to monitor portfolio quality closely and take action when necessary and this has threatened the going concern of microfinance industry in Uganda. The study analyzed the relationship between internal control system and financial performance of MFIs in central region Uganda and it was hypothesized that internal control system positively influences financial performance of MFIs in central region Uganda. MFIs have come under spotlight for cases of poor financial performance. Lack of empirical studies to assess the impact of internal control system on the financial performance of microfinance institutions in Uganda is the motivation behind this study. Therefore, this study is important not only because it fills the gap, but also it set out to address this evident knowledge gap. The study adopted positive-phenomenological, epistemology and quantitative-qualitative methodology dimension with cross sectional and correlation designs, the unit of analysis was Microfinance Institutions registered with Association of Microfinance Institutions, and employees were the units of inquiry. Structural Equations Modeling with Analysis of Moment Structures were used to for statistical modeling
Besides, Hierarchical regression was used to test the predictive power of the variables and indicate precisely what happens to the model as different predictor variables are introduced in the model fit. This study revealed that two of the predictor variables are strong predictors of financial performance of MFIs. The study further revealed that internal control system was found to be strongly and positively correlated with financial performance. And internal control system elements were found to be positive predictors of financial performance. The present study supported a multi-theoretic approach in explaining financial performance of MFIs in Uganda. The study supports the stewardship theory in explaining the controls system together with stakeholder as the theories that help in explaining financial performance of MFIs. The study confirmed efficient control system factor structure of observed variables and the latent variables. As a result, the study provided models for efficient internal control systems. These models can then used to provide a trajectory for improving financial performance of MFIs in Uganda .Regardless of the existence of control systems in MFI, the results revealed that internal control systems were less efficient due to lack of close monitoring. It recommended that MFIs should enhance controls to ensure that resources are obtained and used effectively and efficiently in the accomplishment of the organization’s goals Policy makers, AMFIU, PSFU and MFIs may use these findings as a way of improving financial performance of MFIs in Uganda since the MFIs are great contributors to the Ugandan economy
Key Words : Internal Control System, Financial Performance, microfinance, Institution
Introduction
Microfinance has evolved by providing micro credits to respond to the furthermost financial and non-financial needs of the citizens, to eradicate poverty and increase financial inclusion .The microfinance movement has received enthusiasm as a poverty alleviation tool that has eventually become a self-sustaining industry. Microfinance institutions (MFIs) worldwide have been seen and identified as vital institution to nations’ quest for solutions to the development challenge (CGAP, 2002). Most microfinance institutions have embraced a more business-oriented outlook and maintained their target groups of economically-active poor, in order to achieve financial sustainability (Kalyango, 2004; Baguma, 2008). The micro finance institutions in developing economies are widely growing from time to time. Various studies on different countries on the performance of the MFIs confirm this (Adongo and Stork 2005, Zeller and Meyer 2002, Meyer 2002, Robert cull et al. 2007).
Approaches used by microfinance institutions in Uganda to deliver financial services to the poor are similar to those used in other countries where microfinance institutions operate. The approach used depends on the nature and structure of the respective microfinance institution. The institutions providing microfinance services include: Tier I: formal financial institutions Comercial banks, TierII; credit institutions, Tier III; microfinance deposit taking institutions, Tier IV; Saccos (BOU Policy on MFIs 1999).
Microfinance institutions in Uganda from time and again been faced with high operating costs to provide financial services to the poor people and Small and Medium Enterprises (Micro banking Bulletin, 2002). And as such, are unable to meet their obligations when they become due usually resulting from poor cash flow planning, failure to monitor portfolio quality closely and take action when necessary. Portfolio quality has deteriorated more rapidly in Microfinance institutions than in traditional financial institutions due to the short-term and unsecured nature of micro lending and micro loan portfolios (Srinivasan, 2006 due to unsecured nature of micro lending, micro loan portfolios which are volatile. IMF Report (2001) most MFIs in Uganda had large portfolios in arrears, with overdue loan repayments stretching back into the distant past mainly because lending policies were usually poorly enforced and systems to track and manage arrears. An enduring problem facing microfinance institutions, however, is how to attain financial sustainability (Dunford, 2003; Schreiner, 2000; Woller 2000; Hollis and Sweetman, 1998; Christen et al, 1995). This problem has attracted attention of numerous researchers in recent decades and, as a result many strategies have been identified to ensure that institutions are sustainable (Randhawa and Gallardo, 2003; Schreiner, 2000; Yaron, 1992). Abernethy and Brownell (1999) discussed the interactive use of management control systems and their experimental findings indicated that interactive use of internal control systems can alleviate disruptive performance in a business enterprise. Ledgerwood (1999) as cited by Lincolin Arsyad (2005), conceptualizes financial performance as; Financial viability (operational self-sufficiency, financial self-sufficiency) Profitability (return on assets ratio, return on business ratio, return on equity ratio) and Portfolio quality (portfolio at risk, repayment rates). Financial performance being a critical factor in the success of microfinance Institutions, therefore, this research focused on financial performance and not social performance
Most of the studies on financial performance of microfinance institutions apply and use different methodologies as in the case of Tilahun (2009) , however this study employed a descriptive research design based on quantitative data. The researcher collected and analyzed annual reports using descriptive statistics. A number of theories have been used to explain what influences the financial performance of the firm but their applications have no terminal point. Theories that have been used to explain firm financial performance include, among others Resource-Based View of the firm (RBV), agency theory (Jensen and Meckling 1976), stakeholder theory (Freeman 1984), and stewardship theory. All these theories provide a detailed account of firm performance using available resources inspite of the limitations in their application. Though there is no agreed theoretical base for research on financial performance of microfinance institutions (Parum, 2005), a review of the literature indicates that the above four main theoretical frameworks have been used to explain and analyse the association between management control system and financial performance of microfinance institutions.
Poor financial performance marked by deteriorating returns and portfolio quality has taken a center stage and remained unexplained in microfinance Institutions (Performance Monitoring Tool 2006/2009/). Portfolio quality has deteriorated more rapidly in Microfinance institutions than in traditional financial institutions due to the short-term and unsecured nature of micro lending, micro loan portfolios which tend to be more volatile (Ssewanyana 2009). According to the IMF Report (2001) most MFIs in Uganda had large portfolios in arrears, with overdue loan repayments stretching back into the distant past mainly because lending policies were usually poorly enforced and systems to track and manage arrears hardly existed. Microfinance institutions in Uganda face poor cash flow problems due to changes in market interest rate and failure to monitor portfolio quality closely and take action when necessary and this has threatened the going concern of microfinance industry in Uganda (Bank of Uganda 2010/2011)
Most studies undertaken in the past few years have focused mainly on outreach of MFI’s and their impact on profitability (Migiri, 2002). Lack of clarity on the extent to which internal control system influences financial performance (Narver, 2007) will therefore continue to inhibit common understanding and explanation which might deter performance improvement in Ugandan microfinance institutions. Though some studies have identified ICS as a possible predictor of financial performance in different industries, there are still gaps as a result of absence of representative empirical studies that would address the issue of financial performance of microfinance institutions as a result of management control systems (PekChen, 2005).More so, theories and models apparently used to explain financial performance in firms have proved to be weak and inadequate in explaining this phenomenon. Empirical studies aimed at assessing the impact of ICS on the financial performance of microfinance institutions in Uganda are missing. Therefore, this study is important because it fills this gap of knowledge
Literature Review
Synthesizing existing studies in the broad area of explaining financial performance of MFIs, indicate a clear dearth of studies examining multiplicative effect of various elements the predictor variable ie internal control system(control procedures, risk assessment, control environment, Monitoring and internal audit ) on financial performance of MFIs . (see for review
Welsh (2003), Simons (1995), Chow et al (1999), Merchant (2007), appreciate that internal control systems are the formal, information-based routines and procedures managers that ensure that errors and fraud are detected, safe guard company’s assets and opine that ICS greatly influences firm performance.
Recent studies draw from the original organizational theorists (Burns & Stalker 1961, Lawrence & Lorsch 1967, Thompson 1967, Perrow 1970, Galbraith1973) to develop arguments that explain how the effectiveness of control systems (Chenhall 2003).
Bisbe and Otley (2004), findings indicated that the application of control systems has a huge contingency effect on firm performance. However, Bisbe’s research did not discuss the importance of human effect to control system (Snell, 1992; Abernethy and Brownell, 1997; Keller, 2001; Widener, 2004)
Simon (1995), asserted that internal control systems have different impacts on organization performance, Abernethy and Brownell (1999) discussed the interactive use of internal control systems and their experimental findings indicated that interactive use of internal control systems can alleviate disruptive performance when a company is changing its strategies, Davila (2000), in his study his study findings indicated that different strategies will need different interactive use of management controls to raise firm performance.
Dexon (2010), findings revealed that Internal Control Systems have a significant positive effect in achieving Value for Money. All the constructs of Internal Control Systems (Control environment, control activities, risk assessment) have a significant positive relationship with Value for Money in a business entity
Internal control process reduces uncertainty and improves firm performance, Ivancevich (1976), Steers (1976), Imoisili (1989), Locke & Schweiger (1979), Mia (1989), Ezzamel (1990), Hirst & Lowy (1990) etc. Another study on control process and firm performance relationship by scholars (Merchant, 1980; Peel & Bridge, 1988; Edward, et al., 2001) and empirical results (Merchant, 1980) show that control systems enhance the accuracy the degree of information accuracy. In turn, it results in higher performance in organizations. The increased use of comprehensive ICS practices can be assumed to result in better improved financial performance among firms (e.g. Chenhall 2003, see also discussions in Gul 1991, Gul & Chia 1994, Hoque & James 2000, Ittner et al. 1998, 1998, Scott & Tiessen 1999)
ICS acts as a driver variable in firm strategy and performance as found in Chong & Chong (1997) and Baines & Langfield-Smith (2003). Report of bank of Uganda (2002), Simon (1995), results showed that there is indeed a positive association between certain internal control practices when are used concurrently with other strategic initiatives and improvement in financial performance. Abernethy and Brownell (1999) also discussed the interactive use of internal control systems and their experimental findings indicated that interactive use of internal control systems can alleviate disruptive performance when a company is changing its strategies
The findings confirm the report findings of Armesh (2010) on the influences of internal control system on organizational performance in Malaysia, which showed that Internal Control System influences the behavior and performance of the organizational to ensure that resources are obtained and used effectively and efficiently in the accomplishment of the organization s objectives.
On the other hand however, McMahon (2001) did not find any significant relationship between use of internal control practices and firm performance. Donaldson (2001) found no significant associations were between the use of comprehensive Management Control System and measures of growth in net sales and profitability.
Additionally, McMahon & Davies (1994) and McMahon (2001) have not found any significant relationships between internal control practices and performance of businesses. Thus, the empirical results on the relationship between various dimensions of MCS and performance seem to be rather mixed
Jonathan (2005), study findings revealed that most of the microfinance institutions in Namibia are not yet financially sustainable and it was attributed to the fact that interest rates that Microfinance institutions require to break-even exceed the ceiling imposed. Portfolio quality has deteriorated more rapidly in Microfinance institutions than in financial institutions (Srinivasan, 2006), Studies by Bontis (2002), Chong and Richardson (2006), explained similar performance trends in Portuguese. Study findings revealed that average ROA for MFIs is 3.57%. This concur with study findings of Lafourcade (2005), the findings revealed that, Africa MFIs have the lowest financial performance of ROA of 2% as compared to 7.6%-10% of Eastern Europe and Central Asia. The findings are in agreement with Tilahun (2009), study findings on ‘the financial performance and sustainability of microfinance institutions in Ethiopia’; the result of the study indicates that there was a negative shift in the performance indicators particularly in the year 2009 and the gross loan portfolio has declined by 15.73% in the year 2009.
Furthermore, contrary to Chong and Richardson (2006), study findings, McMahon (2001), did not find any significant relationship between use of control System of Australian business firms and profitability.
Furthermore, Perera et al. (1997) have also reported a respective non significant relationship in manufacturing firms. Malmi et al. (2004) likewise did not find a significant direct relationship between management practices and profitability, even though they reported an interaction effect of the practices and use of other relationship management control systems to be significant in relation to firm performance.
Both theoretical and empirical studies show that strong and efficient systems that maintain high levels of capital adequacy are important in determining financial institutions profitability. Sufian and Habibullah (2009), found out that good systems have a positive impact on bank profitability in China. This confirms Athanasoglou, et al. (2008, 2006) and Kosmidou (2008) who also finds a positive and significant effect of strong control system on bank profitability, reflecting the sound financial condition of banks.
This shows that maintaining strong and efficient internal control system is highly associated with high financial performance in Microfinance Institutions (Gramling et al. 2004; Hermanson & Rittenberg 2003; 2004
First, Reid & Smith (2000) found out those developing control systems, especially in the areas of management and accounting applications, lead to high firm performance, Reid & Smith (2002) , Reid & Smith (2000, 2002) holds that high performers firms use and apply internal control systems for daily financial monitoring and for identifying important trends in key variables for their further survival. On the other hand, Reid & Smith (2002), argue that static performers at satisfactory financial levels tend not to value control systems as much as the others. Consequently, the relationship between internal control system and firm performance seem to be U-shaped
The foregoing reviews reveal that the application of internal control system elements in any organization differ and different interactive use of internal controls to raise firm performance.
The level, application and interactive use of internal control system in Ugandan microfinance industry is elusive. This, therefore, caused the need for a scientific investigation on the use internal control system elements influences financial performance in Uganda’s microfinance industry. This necessitated the study to evaluate the relationship between internal control system and financial performance of the selected microfinance institutions in central region Uganda
Methodology
The study adopted a positivist quantitative paradigm with cross sectional and correlation designs. Correlation design was used to establish relationships between internal control system and financial performance of MFIs. Logical positivism quantitative designs were applied in data collection, analysis and presentation which also helped to test hypothetical deductive generalizations. The study population consisted of 36 MFIs in central region Uganda registered with AMFIU from where the sample size of 33 MFIs were determined comprising a sample of 356 which was consistent with the sample size guidelines of Ntoumanis (2001) and Field (2006). Ntoumanis (2001) and Field (2006), multistage, simple rondom sampling and purposive tequniques were used. Primary and secondary data sources were used in the study.Structural Equations Modeling with Analysis of Moment Structures were also used to for statistical modeling.
Cronbach’s alpha was used to test the reliability of the instruments and the instruments were found to be reliable at 0.78. Content validity of the two instruments was ensured through use of valid concepts which measure the study variables . Content validity was used to ensure that the questionnaire was content valid. The content validity results were obtained and for all the constructs were above 0.7 as recommended by Sakaran (2000). The study used Means and standard deviations in order to summarize the results. The means were used because they show a summary of data and standard deviation clearly shows how well the means represent the data (Field, 2009). Hierarchical regression was used to estimate the predictive power of the predictor variable on the criterion variable in the model fit.
Findings and Discussion
| Descriptive Statistics of the Predictor Variable and Criterion Variable | ||||||||
| N | Range | Minimum | Maximum | Mean | Std. Deviation | Variance | ||
| C. Procedure | 356 | 2.67 | 1.24 | 3.90 | 3.2002 | .01436 | .27098 | .073 |
| C. Environment | 355 | 3.18 | .82 | 4.00 | 3.2101 | .01757 | .33106 | .110 |
| R. Assessment | 356 | 2.70 | 1.30 | 4.00 | 3.1967 | .01465 | .27644 | .076 |
| Monitoring | 356 | 2.11 | 1.50 | 3.61 | 2.9259 | .01350 | .25466 | .065 |
| I. Audit | 356 | 2.25 | 1.75 | 4.00 | 3.2342 | .01894 | .35735 | .128 |
| F.Performance | 356 | 2.89 | .91 | 3.81 | 3.0993 | .01325 | .25005 | .063 |
Source: Primary Data 2017
Results showed that internal control system among MFIs is defined in terms of the five observed variables, control procedures, control environment, risk assessment, and monitoring and internal audit. And financial performance was conceptualised in terms of Return on Assets, return on Equity, profit margin and portfolio quality. The findings indicate small and minimal standard deviations compared to mean values; it is evident that the data points are close to the means and hence calculated means highly represent the observed data. The findings revealed that standardized regression weights for the predictor variable(Internal control system), in explaining financial performance were significant(p<0.001) signifying a strong relationship between internal control system and financial performance of MFIs in central region Uganda and Zero order correlation was applied to determine the correlation between internal control system and financial performance of MFIs
Zero order correlation between internal control system and financial performance of MFIs
| Variables | a | B | C | D | E | f |
| C. Procedure (a) | 1 | 1 | ||||
| C. Environment(b) | .131* | |||||
| R. Assessment (c) | .310** | .499** | 1 | |||
| Monitoring (d) | .259** | .151** | .264** | 1 | ||
| I.Audit (e) | .133* | .131* | .323** | .127* | 1 | |
| F.Performance (f) | .650** | .183** | .388** | .638** | .249** | 1 |
| *. Correlation is significant at the 0.05 level (2-tailed). | |||
| **. Correlation is significant at the 0.01 level (2-tailed). | |||
| Hypothesis | Supported/not supported | ||
| H1: There is a positive and significant relationship between control procedure and Financial performance of MFIs (r= 0.650, p< 0.05). | supported | ||
| H2: There is a positive and significant relationship between control environment and Financial performance of MFIs (r= 0.183, p< 0.05). | supported | ||
| H3: There is a positive and significant relationship between risk assessment and Financial performance of MFIs (r= 0.388, p< 0.05). | supported | ||
| H4: There is a positive and significant relationship between monitoring and Financial performance of MFIs (r= 0.638, p< 0.05). | supported | ||
| H5: There is a positive and significant relationship between internal audit and Financial performance of MFIs (r= 0.249, p< 0.05). | supported | ||
| H5: There is a positive and significant relationship between internal control system and Financial performance of MFIs (r= 0.355, p< 0.05). | supported | ||
To test the predictive power of the study variables, from the hypothesized model
Y = α+β1X1+β2X2+β3X3+β4X4+ β5X5+e
Where Y is the Dependent Variable – Financial Performance
α = Constant
X = representing the constructs of the predictor Variable- ICS
X1 = Control Procedure
X2 = Risk assessment
X3 = Control Environment
X4 = Monitoring
X5 = Internal Auditing
ß1–5 = Coefficients of beta
e = error term in ascertaining the influence of individual element on Financial performance, all the models as indicated the model fit
Model1: Y = α+β1X1+e
Y = 1.154+0.607X1
(t =14.201), (t=7.830), R2= 0.431, F = 83.26, DW = 1.366
Model2: Y = α+β1X1+β2X2+e
Y = 1.470+0.536X1+0. 250X2
(t =13.011), (t=5.190), (t= 6.693) R2= 0.491, F = 76.07, DW = 1.366
Model 3 Y = α+β1X1+β2X2+β3X3+e
Y = 1.427+0.535X1+0.264X2+0.022X3
(t =12.102), (t=4.6513), (t= 5.353) (t=1.671) R2= 0.492, F = 42.08, DW = 1.366
Model 4 Y = α+β1X1+β2X2+β3X3+β4X4+e
Y = 1.474+0.452X1+0.160X2+0.026X3+0.457X4
(t =10.261), (t=3.544), (t= 4.773) (t=1.482) (t =1.875) R2= .683, F = 39.28,
DW = 1.366
Model 5 Y = α+β1X1+β2X2+β3X3+β4X4+ β5X5+e
Y = 1.295+0.450X1+0.131X2+0.023X3+0.455X4+0.061X5
(t =9.371), (t=3.623), (t= 4.897) (t=1.495) (t =1.910), (t = 2.130) R2= .690, F = 33.66, DW = 1.366
In Model 1, Control Procedure accounts for 43.2% of variance in financial performance of MFIs (F = 83.26, P < .005) and caused a statistically-significant non-standardized coefficient (B =0. 607, P <0.05).
In Model 2, the introduction of Risk Assessment in the equation yielded an extra effect 6% to the explanatory power of the model. This clearly implies that Risk Assessment accounts for an additional 6% of the variance in financial performance. This means that a unit change in Risk Assessment leads to 6% increase in financial performance (F=76.07, p < 0.05), and caused a statistically-significant coefficient (B =0. 250, p <0.05);
Results for Model 3 indicate that the introduction of Control Environment in the equation yielded a low significant effect of 0.1% to the explanatory power of the model. This means that Control Environment explained an additional 0.1% of the variance in financial performance (F = 42.08, P < 0.05), and caused statistically very low significant coefficient (B =0.022, p<0.05); these results indicate that Control Environment influence financial performance of MFIs but with minimal effect.
In Model 4, the introduction of Monitoring in the equation also yielded a less significant 19.1% to the explanatory power of the model. Thus monitoring account for additional 19.1% of the variance in financial performance (F =39.28, p<0.05) and lead to statistically significant contribution in coefficient (B = 0.457, p<0.05).
In Model 5, after the internal audit was included, a less significant additional 0.7% was yielded and added to the explanatory power of the model. These results indicate Internal audit account for only 0.7% of the variance in financial performance (F= 33.66, p < 0.05), and caused a statistically less significant coefficient (B =0.061, p <0.05). However, model 5 shows the overall explanatory power of the model to be 69%. This clearly shows that internal control system predicts 69 % of the variance in the financial performance of MFIs in central region Uganda. Considering, the unstandardized coefficients, control procedures has the highest beta followed by monitoring and then risk assessment, internal audit and finally control environment.
This study revealed that two of the predictor variables are strong predictors of financial performance of MFIs. The study further revealed that internal control system was found to be strongly and positively correlated with financial performance leading to the acceptance of the hypothesis that internal control systems are positively related with financial performance among the MFIs in central region Uganda.. And internal control system elements were found to be positive predictors of financial performance.
The present study supported a multi-theoretic approach in explaining financial performance of MFIs in Uganda. The study supports the stewardship theory in explaining the controls system together with stakeholder and resource based view as the theories that help in explaining financial performance of MFIs. The study confirmed that efficient control system factor structure of observed variables and the latent variables. As a result, the study provided models for efficient internal control systems. These models can then used to provide a trajectory for improving financial performance of MFIs in Uganda. It recommended that MFIs should enhance controls to ensure that resources are obtained and used effectively and efficiently in the accomplishment of the organization’s goals
Policy makers, BOU, MOFEP AMFIU, PSFU and MFIs may use these findings as a way of improving financial performance of MFIs in Uganda since the MFIs are great contributors to the Ugandan economy.
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