THE EFFECT OF FINANCIAL INNOVATION ON THE FINANCIAL PERFORMANCE OF SACCOS IN KENYA
PRESENTED BY: PAMELA AWUOR YINDA
REG NO: D61/85429/2016
A RESEARCH PROPOSAL SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE AWARD OF THE DEGREE OF MASTERS IN BUSINESS ADMINISTRATION, UNIVERSITY OF NAIROBI
DECLARATIONI declare that this is my original work and has not been submitted to any institution for academic purpose.NAME REG NO SIGNPAMELA AWUOR YINDA D61/85429/2016 ___________This project has been submitted for examination with our approval as the University Supervisors.Mr. Dominic Murage
School of Business
University of Nairobi
Dr. Erastus Sifunjo
School of Business
University of Nairobi
This project has been submitted for examination with my approval as the University Chairman.
Dr. Mirie Mwangi
School of Business
University of Nairobi
LIST OF ABBREVIATIONSANOVA- Analysis of Variance
ATM- Automated Teller Machine
CBK- Central Bank of Kenya
CMA- Capital Market Authority
DTS – Deposit Taking Saccos
FOSA- Front Office Service Authority
GDP- Gross Domestic Product
OECD- Organization for Economic Co-operation and Development
ROE- Return on Equity
RTGS- Real Time Gross Settlement
SACCO- Savings and Credit Co-operative Societies
SASRA-Sacco Society Regulatory Authority
Table of Contents
TOC o “1-3” h z u DECLARATION PAGEREF _Toc526670072 h iLIST OF ABBREVIATIONS PAGEREF _Toc526670073 h iiCHAPTER ONE PAGEREF _Toc526670074 h 1INTRODUCTION PAGEREF _Toc526670075 h 11.1Background to the Study PAGEREF _Toc526670076 h 11.1.1Financial Innovation in SACCOs PAGEREF _Toc526670077 h 21.1.2Financial Performance of SACCOs in Kenya PAGEREF _Toc526670078 h 31.1.3The Effect of Financial Innovation on Financial Performance of SACCOs PAGEREF _Toc526670079 h 41.1.4Savings and Credit Co-operative Societies in Kenya PAGEREF _Toc526670080 h 41.2Research Problem PAGEREF _Toc526670081 h 51.3 Research Objectives PAGEREF _Toc526670082 h 61.4 Value of the Study PAGEREF _Toc526670083 h 6CHAPTER TWO PAGEREF _Toc526670084 h 8LITERATURE REVIEW PAGEREF _Toc526670085 h 82.1 Introduction PAGEREF _Toc526670086 h 82.2 Theoretical Review PAGEREF _Toc526670087 h 82.2.1 Transaction Cost Innovation Theory PAGEREF _Toc526670088 h 82.2.2 Schumpeter Innovation Theory PAGEREF _Toc526670089 h 92.2.3 Diffusion Innovation Theory PAGEREF _Toc526670090 h 92.2.4 Constraint Induced Innovation Theory PAGEREF _Toc526670091 h 102.3 Determinants of Financial Performance PAGEREF _Toc526670092 h 102.3.1 Operational Efficiency PAGEREF _Toc526670093 h 102.3.2 Interest Rate PAGEREF _Toc526670094 h 112.3.3 Size of the Company PAGEREF _Toc526670095 h 112.3.4 Financial Innovation PAGEREF _Toc526670096 h 122.4 Empirical Review PAGEREF _Toc526670097 h 122.4.1 International Studies PAGEREF _Toc526670098 h 122.4.2 Local Studies PAGEREF _Toc526670099 h 142.5 Conceptual Framework PAGEREF _Toc526670100 h 152.6 Summary of Literature Review PAGEREF _Toc526670101 h 16CHAPTER THREE PAGEREF _Toc526670102 h 17RESEARCH METHODOLOGY PAGEREF _Toc526670103 h 173.1 Introduction PAGEREF _Toc526670104 h 173.2 Research Design PAGEREF _Toc526670105 h 173.3 Population PAGEREF _Toc526670106 h 173.4 Sample Design PAGEREF _Toc526670107 h 173.5 Data Collection PAGEREF _Toc526670108 h 183.6 Diagnostic test PAGEREF _Toc526670109 h 183.6.1 Multicollinearity PAGEREF _Toc526670110 h 183.6.2 Normality PAGEREF _Toc526670111 h 183.6.3 Autocorrelation PAGEREF _Toc526670112 h 193.6.4 Heteroscedasticity PAGEREF _Toc526670113 h 193.6.5 Linearity test PAGEREF _Toc526670114 h 193.7 Data Analysis PAGEREF _Toc526670115 h 20REFERENCES PAGEREF _Toc526670116 h 21APPENDIX I: A LIST OF DEPOSIT TAKING SACCOS IN KENYA LICENCED BY SASRA PAGEREF _Toc526670117 h 26
CHAPTER ONEINTRODUCTIONBackground to the StudySACCOs are an integral part of the Kenyan government’s economic strategy which was implemented to enhance income generating opportunities; they contribute to 45% of Kenya’s GDP (Hardoon, 2017). SACCOs play an important role in mobilizing savings and allocating credit contributing to 80% of accumulated savings (Ayieko, 2016). However, due to wealth maximization objective SACCOs have found it challenging to absorb their operational losses which affect their growth and ability to positively contribute to Kenya’s GDP (Mwania, 2016). The aim of studying the factors that influence the financial performance of SACCOs in Kenya is to come up with means of maximizing the full potential that SACCOs hold for the socio-economic development of Kenya and also contribute to poverty alleviation (Ayieko, 2016). The financial performance of a SACCO is measured through the ability of the institution to meet the demands of its customers taking into account the economic status of its members (Miriti, 2014).
There are several theories used in this study that show the importance of financial innovation and its relationship to financial performance such as; the Schumpeterian theory of innovation developed by Schumpeter (1939) which emphasizes on the need of financial innovation in order to enhance the financial performance of organizations, the constraint induced innovation theory developed by Silber (1983) which states that the need by financial institutions to maximize on profit despite various constraints and in the process of finding ways of overcoming these constraints financial innovation is adopted, the transaction cost innovation theory developed by Hicks (1983) which emphasises on financial innovation as a way to reduce transaction cost which can improve the financial performance of firms and the diffusion innovation theory developed by Rogers (2005) which emphasizes that the extent to which financial innovation impacts on financial performance depends on the adaptation by the financial institution.
Various studies on the effect of financial innovation on the financial performance of SACCOs have been conducted by several scholars who came up with different findings. A research conducted by Mugo (2012) showed a strong positive relationship between financial innovation and financial performance of micro-finance institutions, Malhotra and Singh (2009) in their study on internet banking in India and its implications on the Indian banking industry found that there is a strong negative relationship between internet banking and profitability of Indian banks, Muteke (2015) in his study on the effect of financial innovation on SACCOs in Kenya found that institutional innovation marginally but positively influenced financial performance and Kojo and Yazidu (2015) carried out a study on financial characteristics and innovations in microfinance institutions in Ghana found a slight negative relationship between financial innovation and financial performance MFIs.
Financial Innovation in SACCOsIt is widely recognized that financial innovations are crucial in the economic development process, especially for financing small- and medium-sized enterprises and mobilizing local resources from low- and middle-income groups (Schrieder ; Heidhues, 1995). According to White (2002) financial innovation is a new or modified thing that causes reduction in costs and risks and provides an improved product/service/instrument that satisfies the demands of the participants. Financial innovation can be looked at as a product, process and institutional innovation CITATION Joa11 l 1033 (Blach, 2011). Institutional innovations refer to restructuring and changes in the legal and supervisory framework (Llewellyn, 2009). Process innovation refers to the introduction of new business processes as means of increasing efficiency, market expansion, and client data management. These may include electronic banking, automated teller machines (ATMs), and Real Time Gross Settlement (RTGS) (Llewellyn, 2009). Product innovations include the introduction of goods or service with improved characteristics to respond to changes in market demand or to improve the efficiency. These may include new credit cards, personal unsecured loans, money transfer services, and mobile banking.
The FOSA offers bank-like services, like withdraw able savings, deposits, debit cards, advances, money transfers etc and they are only offered by deposit taking SACCOs (Kiragu, 2012). When banks withdrew from many rural areas the people who relied on banks for simple services like processing the salaries, en-cashing cheques, acquiring cheques were left unbanked, this action created an opportunity for FOSA which ended up providing banking services such as receiving salaries for the people who were inconvenienced and they were able to do this because Sacco’s with FOSAs can be found all over the country and include both Rural and Urban Sacco’s (Langat, 2016). Front Office Service Activity (FOSA) was introduced in 1997 with only 450 customers, today FOSA is very popular with the society membership with over 3500 customers (Kimani, 2010)
Financial Performance of SACCOs in KenyaAccording to Maxwell Scientific Organization (2011), financial performance means a firm’s overall financial health over a given period of time. Financial performance of a firm can be measured using variables such as profitability and liquidity CITATION DAS14 l 2057 (Sanghani, 2014). Profitability is used to measure the level of profit a firm gets from the factors of production (Onduso, 2013). Four useful measures of firms’ profitability are Return on Assets (ROA), Return on Equity (ROE), Operating Profit Margin and Net Income (Aliabdi, 2013). Liquidity, on the other hand, measures the ability of the firm to meet financial obligations as they fall due, without disrupting the owner equity, using the market value of assets. Liquidity refers to the firs ability to meet financial demands as they arise. Liquidity can be measured using the current ratio, net working capital and quick acid-test ratio CITATION ZAM13 l 2057 (Maaka, 2013).
The financial performance of a Sacco can be calculated using key financial ratios for a certain period ranging from the past three to five years as a way of measuring progress and performance; the ratios which are usually presented in percentages are a comparison of two or more elements of the data (Ahmad, 2011). The ratios tell how well the Sacco is able to generate revenue or income from available assets hence the need to be analyzed effectively, this is because the management is usually guided by the financial performance in when it comes to decision making on strategies and policies (Almazari, 2011). Financial performance determines how well a firm is generating value; it creates implications such as demand for better salary for staff and higher dividends for stakeholders.
The Effect of Financial Innovation on Financial Performance of SACCOsMerton (1986) stated that, financial innovation drives the financial system towards the performance the economy. Financial institutions use financial innovation to gain competitive advantage against competitors, it can improve their performance and maintain their effectiveness on market (Batiz-Lazo, 2006).
Lyons (2007) argued that the relevant aspects of technological change include innovations that reduce costs related to the collection, storage, processing, and transmission of information, as well as innovations that transform the means by which customers’ access financial services. ATMs (automated teller machines), telephone banking, internet banking, and e-money are among the significant innovations affecting the financial system. Love (2009) added that client relationship management systems, bank management technologies, and various other technologies are among the major changes in internal banking systems that also have exercised a positive influence on the performance of financial institutions.
According to Alam (2010) firm performance is a multidimensional construct that consists of four elements, that is Customer-focused performance, including customer satisfaction, and product or service performance; financial and market performance, including revenue, profits, market position, cash-to-cash cycle time, and earnings per share; human resource performance, including employee satisfaction; and organizational effectiveness, including time to market, level of innovation, and production and supply chain flexibility.
According to Davila (2006) innovation is a necessary ingredient for sustained success and is an integral part of the business. Much weight has been accorded on building innovative institutions and the management of the innovation progression as necessary elements of institutional survival.
Savings and Credit Co-operative Societies in Kenya
The co-operative societies Act No. 12 of 1997 governs the management of co-operative societies and subsequent cooperative societies (Amendment) Act No. 2 of 2004 that comply with the guidelines of the International Co-operative Alliance (ICA). Co-operative societies contribute to about 45% of Kenya’s GDP (Hardoon, 2017). A large proportion of Kenyans depend on cooperatives to be able to make a living. Approximately 63% of Kenyans derive their livelihoods from cooperative based activities. Cooperatives have enabled members to acquire wealth, alleviate poverty and create employment (Kiplagat, 2005). There are 2 categories of cooperatives: Financial and non-financial cooperatives (includes farm produce and other commodities, marketing, housing transport ;investment cooperatives) CITATION EJo05 l 2057 (Jones, 2005). Through the establishment of SACCO societies Act 2008, prudential regulations have been introduced to guide SACCOs’ growth and development through the placement of SASRA as the licensing, supervising and regulatory body of deposit-taking (Sacco supervision annual report, 2012). To be able to attain sustainable competitive advantage and enhance growth, SACCOs in Kenya have embraced technological advancements such as mobile and internet banking (Mwania, 2017).
As of December 2017 there were 424 DTS of which were licensed to carry out deposit taking activities (SASRA website). DTS is comprised of societies undertaking both withdraw able and non-withdraw able deposits. According to the SASRA report, 2015.The financial performance of DTS is measured by financial activities and operational activities. According to SACCO act (2010) loan portfolio is a large asset for DT-SACCOs plays a big part in assessing the financial performance of DTS. DTS are required to maintain a minimum of 15% of their saving deposits together with short term liabilities as liquid assets (Saccos Societies Act, 2010). Survival of deposit taking SACCOs in Kenya depends on their innovation capabilities since they face stiff competition from other financial institutions (Okwach, 2017).
Research ProblemMore than 80% of Kenyans rely on SACCO’s to access financial services (FinAccess, 2015). However, the use of SACCOs by Kenyans as a financial service provider has been declining over the last five years (Ibid, 2016). The decline has been from a high of 13.5% in 2012 to as low as 9.1% by the end of the year 2016. During the same period, customers accessing commercial banks for financial services has grown from a low of 13.5% in 2009 to 29.2% in 2016 (Ibid, 2016). This trend in loss of customers is attributed to the competition from banks through proactive outreach and offering of easy access transactions accounts as well as consumer loans through financial innovations (FinAccess, 2016).SACCOs have been losing their market share in spite of their geographical spread in the country compared to other financial providers (Nyaga, 2012).
Although financial innovation has been recognized as an important contributing factor to better performance it remains an area which has not been widely studied, most of the studies which have been undertaken do not take into account the contributing factors to innovation inside and outside the financial institution, all of which could influence this relationship. Tufano, Lerner and Peter (2011) in their study on consequences of financial innovations contend that existing empirical evidence and conceptual frameworks can tell more about financial innovation, but there are substantial unanswered questions in the areas of social welfare impact of financial innovations, the impact of innovations on financial institutions and a lot of financial innovations research is mainly on case studies. Rafael and Francisco (2007) studied the impact of various regional banking sector developments and innovations during 1986- 2001 in Spain. The study found out that product and service delivery innovations contribute positively to regional Gross Domestic Product (GDP), investment and gross savings growth.
Despite the fact that there have been studies on financial innovation and financial performance of SACCOs, a few have focused on deposit taking SACCOs hence there have not been substantial findings on the effect of financial innovation on the financial performance of deposit taking SACCOs in Kenya, this study aims to bridge this research by providing information on the role that financial institutions play on the financial performance of financial institutions and as a resulting answer the question; how does financial innovation impact the financial performance of financial institutions?
1.3 Research ObjectivesThis study aims to determine the effect that financial innovation has on the financial performance of deposit-taking SACCOs in Kenya
1.4 Value of the StudyThe management and staff of financial institutions will gain insight into how their companies can effectively use financial innovations to enhance their desired financial goals. Management can gain the best policies for applications. This will nonetheless improve on the existing theory and knowledge on the changes that financial institutions are going through in relation to financial innovation in the dynamic environment.
Regulatory bodies like the Capital Markets Authority (CMA) can use this study to improve on the framework for regulation and implement a new set of policies and regulations regarding financial innovation in the financial institutions in Kenya.
The study findings will benefit scholars and researchers by adding to the existing field of knowledge of working capital management and provide scholars with the necessary literature review to carry out further study.
The research will also be a reliable source to authenticate existing stands in financial innovation in relation to financial performance.
CHAPTER TWOLITERATURE REVIEW2.1 IntroductionThis chapter presents a review of the literature on the relationship between financial innovation and the financial performance of financial institutions in Nairobi. The chapter focuses on studies undertaken by various scholars and theories that reflect the relationship between financial innovation and the financial performance of financial institutions. The first part (section 2.2), will focus on the theories that apply to financial innovation. The second part (section 2.3) will mainly focus on the determinants of financial performance of financial institutions. Section 2.4 gives the empirical review of the past similar and related research by various scholars. Section 2.5 summarizes the entire chapter.
2.2 Theoretical ReviewA number of theories exist on financial innovation and they will form the theoretical foundation of this section on literature review.
2.2.1 Transaction Cost Innovation TheoryAccording to Niehans (1989) transaction cost innovation theory, refers to the reduction of the cost of labour required to bring a good or service to the market. Transaction cost can basically be viewed as the expenses incurred by buyers as commissions to agents or brokers which makes the difference between the price that the buyer would have paid and the actual price he/she ends up paying. An efficient market is a one which has no transaction cost and as a result capital and labour is channelled into more productive activities. Communication barrier between an investor and a saver is an example of transaction cost, in such a situation banks act as middlemen by using the savers’ funds to finance loans for investors and return charge a certain fee for such funding. Niehans (1989) pioneered the theory of the transaction cost by arguing that the financial innovation can be used to reduced transaction costs. Financial innovation can be used as a tool to eliminate transaction costs.
2.2.2 Schumpeter Innovation TheorySchumpeter (1939) started studying how the capitalist system was affected by market innovations. He came up with a theory which linked the ability of a company to innovate with the size. Initially, his studies showed that smaller companies have an advantage over larger companies when it comes to adopting innovation due to the flexible nature of small companies and bureaucratic nature of large companies. Schumpeter (1982) argued that entrepreneurs, who could be independent inventors or research and development (R&D) engineers in large corporations, created the opportunity for new profits with their innovations. In turn, a group of imitators attracted by super profits would start a wave of investment that would erode the profit margin for the innovation. Schumpeter (1939) drew a clear distinction between the entrepreneurs whose innovations create the conditions for profitable new enterprises and the bankers who create credit to finance the construction of the new ventures. Therefore, as independent agents who have no proprietary interest in the new enterprises they fund, bankers bear all the risk. This requires having the special ability to judge the potential for success in funding entrepreneurial activities. According to Schumpeter (1939) it is just as important to deny credit to those that lack that potential as it is to supply those that have the potential for success.
2.2.3 Diffusion Innovation TheoryInnovation Diffusion Theory (IDT) by (Rogers, 2005) has been employed in studying technology adoption. According to the theory, four elements of diffusion including innovation, time, communication channels, and social systems affect the adoption of innovation. Rogers (2005) states that the adaptation of technological advancements by an individual largely depends on the individual’s perception on the relative advantage, compatibility, complexity, trial ability, and observation of the innovation, as well as social norms. Rogers (2005) identified five general attributes that consistently influenced the adoption of innovations which are; Relative Advantage-The degree to which an innovation is perceived as being better than its precursor (Rogers, 2005),Compatibility-The extent to which the innovation is perceived as being in line with values, needs and experiences of prospective adopters (Hernandez, 2006),Complexity-The degree to which an innovation is perceived as difficult to understand and use (Rogers,2005),Observability-The degree to which the results of an innovation are visible to others (Rogers, 2005).
2.2.4 Constraint Induced Innovation TheorySilber (1983) advanced the constraint-induced innovation theory by stating that the main reason for financial innovation is profit maximization though there is some micro and macro environmental factors which prevent the realization of profit maximization which tend to undermine the efficiency of financial institutions. These constraints can be self- imposed, market- imposed or government imposed. According to Silber (1983) a simple linear programming model of optimization can be used to explain an institution’s behaviour where firms maximize utility subject to a number of internal and external constraints. The study concluded that the model explains around 60% of all innovations that have taken place during the last period. The theory concluded that a better allocation of risk and circumvention of out-dated regulation are two main constraints which lead to increase of economic benefit through cost reduction.
2.3 Determinants of Financial PerformanceDeterminants of financial performance include variables like operational efficiency, macro- economic measures like interest rate, micro economic measures like the size of the firm and financial innovation are discussed below.
2.3.1 Operational Efficiency
The operational efficiency refers to the ability to produce maximum output at a given level of input, and it is the most effective way of delivering small loans to the very poor in SACCO context. This involves cost minimization and income maximization at a given level of operation, and it has an enduring impact on financial performance of SACCOs. Although a high return margin reflects better performance, a lower margin does not automatically indicate a lower rate of return on assets turnover. Relatively, more efficient firms tend to maintain more stability levels in terms of output and operating performance compared to their other industry peers (Mills and Schumann, 1985). There are several ratios of measuring operational efficiency. We can use the Total Asset Turnover ratio by dividing net sales by average total assets. Secondly we can use the Fixed-Asset Turnover ratio by dividing net sales by average net fixed assets. Lastly we can use Equity Turnover calculated as the ratio of net sales to average total equity. These ratios shows whether the firm is managing operational cost efficiently which will ultimately have an influence upon its profitability (Rao &Lakew, 2012).
2.3.2 Interest RateInterest rate is a macro environment factor which is a percentage of the principal charged by the lender as a compensation for the loss of asset use. It is usually expressed as a percentage of the total amount loaned. Higher interest rates offer lenders in an economy a higher profitability relative to other countries. Increasing interest rate and capital flow volatility are found to raise inflation uncertainty and encourage financial investments while discouraging fixed investments by real sector firms (Felix, 1998). Interest rates are generally higher for borrowers who are more likely to default. Interest is often compounded, meaning that the interest earned on a savings account for example, is considered part of the principal after a predetermined period of time. Interest is then earned on the larger principal balance during the next period and the process begins again (Canner et al., 1997). Interest rate is influenced by a number of factors namely the risk of default, the length of the loan, inflation rates, and the real rate. A study by Ovamba (2014), on the relationship between macroeconomic factors and bank profitability had results indicating that factors (real GDP, inflation and exchange rate) have a significant effect on profitability and financial performance
2.3.3 Size of the CompanyThe size of a firm is the production capacity and ability a firm possesses to run its operations and meet the needs of its customers, it basically refers to the market share a firm holds in an industry. The size of a firm is a primary factor in determining the profitability of a firm due to the concept is known as economies of scale which can be found in the traditional neoclassical view of the firm (Sritharan, 2015). It reveals that larger firms produce items at a lower cost that smaller firms hence a positive relationship between firm size and profitability is expected. Other theories of the firms advise that managers in larger firms pursuing self-interested goals may substitute profit maximization of the firms’ objective function (Niresh, 2014). The size of a firm is a primary factor in determining the profitability of a firm due to the concept is known as economies of scale which can be found in the traditional neoclassical view of the firm. From this concept it can be seen that there is a positive relationship between firm size and its financial performance is expected.
Large firms are more likely to manage their working capitals more efficiently than small firms. Most large firms enjoy economies of scale and thus are able to minimize their costs and improve on their financial performance. In their study, Kodongo et al., (2014), findings suggested that asset tangibility, sales growth and firm size are important determinants of profitability and consequently determine the financial performance. A study by Omondi and Muturi (2013), suggest that firms should expand in a controlled way with the aim of achieving an optimum size so as to enjoy economies of scale which can ultimately result in higher level of financial performance
2.3.4 Financial InnovationVarious scholars have contended that there is a significant relationship between financial innovation and financial performance of commercial banks while other scholars have claimed scholars that the relationship is insignificant. Both Agbola (2007) and Dittmar( 2007) have pointed out that there is a positive relationship between financial innovation and financial performance while Prager (2001) and Allen (2002) concluded that innovations have negative effects on performance. This study will establish the nature and significance of the effect of financial innovation on the financial performance of SACCOs.
2.4 Empirical ReviewThis section will present a chronology of various studies that have been conducted on the relationship between financial innovation and financial performance both internationally and nationally, and that has been supported by appropriate sets of data. These studies have been conducted in various markets and the results are diverse.
2.4.1 International StudiesAccording to Schumpeter (1982) innovations can lead to a competitive advantage that can be exploited by innovative firms. Based on his work substantial body of research suggests that the relationship between a firm s level of innovation and financial performance should be positive. Schumpeter (1982) put emphasis on the fact that entrepreneurship would play a great role in generating income by creating new opportunities. However, he did so with reference to a distinction between invention or discovery on one hand and innovation, commercialization and entrepreneurship on the other side.
According to Chanaka (2010) despite the fact that internet banking results in cost and efficiency gains for bank, the percentage of banks that embraced internet banking in the U.K was low. Klomp (2001) found a positive relationship between innovation output and sales growth but does not show any form of relationship between the innovation output and the employment growth. Prager (2001) found that the level of ATM surcharge is negatively related to deposits market share of small banks.
Shirley (2006) carried out a study to investigate the impact of information technology on the banking industry in the United States. The study used theoretical and empirical studies to analyze the link between information technology and financial innovations like internet banking, electronic payments, security investments, and information exchanges can affect bank profits via competition in financial services that are offered by the banks. The study used a panel of 68 US banks for a period of over 20 years to estimate the impact of IT-related financial innovations on the profitability of banks. The study findings found out that though IT might lead to cost-saving, higher IT spending can create network effects lowering bank profits. They further contend that the relationship between IT expenditures and bank’s financial performance is conditional to the extent of the network effect. They say that if the network effect is too low, IT expenditures are likely to; reduce payroll expenses, increase market share, and increase revenue and profit.
Claeys (2008) conducted a study to compare the performance of different online banking models over the period 1995-2004 in Finland, Spain, Italy, and the UK and concluded that internet banks were performing better in terms of equity and ran a lower operational costs for the income they generated. They explain the performance of banks using a group of selected bank-specific features, but also adding country-specific macroeconomic indicators and information technology related ratios. They further say that by focusing mostly on bank deposits, the banks cannot gain benefits from more rewarding banking activities and clients interested in value-added products still prefer interaction with a physical branch and therefore internet banks need to reach a minimum dimension in order to become profitable. They further argued that online banking is largely driven by macro economic factors such as a percentage of households with access to the internet at home, a higher broadband penetration rate, and higher outlay on R&D employment that are all factors positively influencing internet bank performance
2.4.2 Local StudiesAccording to Mwangi, 2007, in Kenya where less than a quarter of the population has bank accounts, banks have spurred into action in the consumer market by the success of the mobile money transfer services. Mobile money transfer was first launched in Kenya by Safaricom mobile operator in 2007 through M-Pesa and other mobile operators today provide similar services. This innovation has brought about significant changes in the country’s banking and financial services landscape.
According to King’ori (2008) one of the latest boosts to financial services in Kenya is the partnership between mobile operators and commercial banks which, above doing away with account-opening fees and monthly charges, pays interest and offers account holders access to emergency credit facilities. King’ori (2008) observed that from his study on the determinants of income velocity of money in the Kenyan financial sector, innovations and changes are taking over the financial sector by storm. This has increased competition in the Kenyan financial services sector. The greater circulation of money means more businesses are coming up, and leads to better investment prospects as investor fell more comfortable.
Githikwa (2009) researched on the relationship between financial innovation and profitability of commercial banks in Kenya. The findings concluded that banks conceptualized financial innovation as a means to create an impact on the profit performance. The studies revealed that through implementing the product, process, and institutional innovation, commercial banks become more flexible in their operations and it leads to the acquisition of more qualified personnel in the bank, quality products and allows bank expansion. The study also revealed that implementation of financial innovation requires more banks to have a lot of resources, however, it reduces costs of operations, reduce cost per transaction and equally enable banks tosatisfy the customer needs.
Waweru (2012) in her study on the effects of financial innovations on risk management of commercial banks in Kenya, concluded that financial innovations have exposed commercial banks in Kenya to various risks, these are; credit risk, liquidity risk, interest rate risk, country risk, compliance risk, and reputational risks. The researcher recommended a more robust risk mitigation practices and policies to ensure that all elements of risk are captured in the risk index factors of commercial banks.
2.5 Conceptual FrameworkMugenda (2003) viewed a conceptual framework as a hypothesized model identifying the model under study and the relationships between the dependent variable and independent variables. A researcher conceptualizes the relationship between variables in the study and shows the relationship graphically or in a diagram.
Fig 2.5 Conceptual model
Independent variables Dependent variable
(Return on equity)
Size of the firm
2.6 Summary of Literature ReviewThis chapter reviewed the relevant literature in relation to financial innovation. Four theories have been specifically reviewed; transaction cost innovation theory, Schumpeter innovation theory, diffusion theory, and constraint-induced innovation theory. Determinants of financial performance were also reviewed. A review of empirical studies on financial innovation and its effect on the financial performance of financial institutions was also done based on studies done in and outside Kenya most of which show that there is a positive relationship between financial innovation and the financial performance of financial institutions.
CHAPTER THREERESEARCH METHODOLOGY3.1 IntroductionThis chapter outlines the general methodology used to conduct the study. It specifies the research design, target population, sampling design, data collection method, instruments, data analysis, and interpretation.
3.2 Research DesignA research design is a structure used to investigate a set of data collected for a study so as to be able to come up with answers to research questions. The plan is the overall scheme or program of the research (Robson, 2002). The main purpose of this research was to determine the relationship between financial innovation and the performance of financial institutions in Nairobi. Therefore a descriptive research was used to study whether there is a effect of financial innovation on the financial performance of SACCOs in Nairobi.
The research used both descriptive and quantitative research design. The major purpose of the descriptive research was to provide information on characteristics of a population or phenomenon.
3.3 PopulationA population is an entire area from which a sample is drawn CITATION OMu03 l 1033 (Mugenda, 2003). The population of this study comprised of 164 financial institutions in Nairobi between the years 2013 to 2017, the figure was arrived at by using directories provided by various financial authorities and also reports from the national treasury and central bank of Kenya.
3.4 Sample DesignStratified sampling was adopted so as to give each item in the population an equal probability of being selected. Saunder (2003) asserts that stratified random sampling involves dividing a population into subgroups and giving a number to every stratum of the accessible population and then randomly selecting the final subjects proportionally from the different strata. Stratified sampling was chosen for this study because it would help to account for differences within the population. According to Mugenda and Mugenda (2003) at least 10% of the target population was important for the study, the study therefore involved 19 SACCOs in Kenya whose financial data were accessible.
3.5 Data CollectionThe study collected secondary data. The secondary data collected included the financial statements and financial reports from the sampled financial institutions for a period of five years starting from 2013 to 2017.
3.6 Diagnostic testDiagnostic tests are procedures for regression analysis used to assess the validity of a model. The diagnostic tests that will be used in this study are normality, homoscedasticity, multicollinearity, linearity and autocorrelation
3.6.1 MulticollinearityMulticolinearity occurs if two or more independent variables are strongly correlated among each other, it is a problem because it weakens the significance of the model by reducing either the individual t-statistics or F and by lowering the R-square (Gani, 2015). Usual symptoms are counter-intuitive sign for the regression coefficients and Significant F-statistics and non significant t-statistics or vice-versa. Multicollinearity testing can be done by looking at value of Variance Inflation Factors (VIF) and Tolerance, if the value of VIF; 10 and the value of Tolerance;0.1 then there is multicollinearity and if multicollinearity is found in the data deducting the mean score might help to solve the problem (Nachrowi, 2006). Other alternatives to tackle the problems is conducting a factor analysis and rotating the factors to insure independence of the factors in the linear regression analysis
3.6.2 NormalityA regression model assumes that the error terms in the model are normally distributed, mutually independent and have uniform variance (Santoso, 2010). This assumption can best be checked with a histogram and a fitted normal. Shapiro Wilk method uses a data base that has not been processed in the frequency distribution table. Data is sorted then divided into two groups to be converted in the Shapiro Wilk (Rahman et al, 2014). Significance test of the value of T3 with Shapiro Wilk table can be seen in the probability value (p). If the value of p; 5%, then the data are normally distributed. When the data is not normally distributed a non-linear transformation, e.g., log-transformation might fix this issue.
3.6.3 AutocorrelationLinear regression analysis requires that there is little or no autocorrelation in the data. Autocorrelation occurs when the residuals are not independent from each other (Poole ; Farrell, 1970) . Tests for first order autocorrelation among the error terms can be carried out using a Durbin Watson test, if the DW’s value of calculated is outside the lower limit (dL) and the upper limit (dV), then the model is not autocorrelation (Ghozali, 2007). Presence of autocorrelation may be eliminated by transforming the data or by introducing further independent variables into the model and then using ordinary least-squares methods.
3.6.4 HeteroscedasticityThe linear regression model assumes that there is homoscedisticity across all values of the independent variables, that is, the variance is the same across all values of the independent variables. When the size of the variance differs across values of an independent variable then the model is said to posses heteroscedasticity (Ghozali, 2007). Heteroscedasticity testing can be done by Glejser Test method which is conducted by regression between independent variable and absolute residual as dependent variable. If the significance value > 0.05, then there is no heteroscedasticity (Hill, Griffiths and Lim, 2011). To eliminate or reduce heteroscedasticity the input data may be transformed or a modified form of the regression model, weighted regression, may be used (Poole & Farrell, 1970).
3.6.5 Linearity testIt is used to determine whether two or more variables have a significant linear relationship or not. The results of these tests can then be used to help make decisions in determining the regression model that will be used appropriately. Linearity testing can be done by the Sig. linearity and Sig. deviation from linearity in Table ANOVA. Value Sig. linearity indicates the extent to which the independent variable value just in a straight line. If the value of Sig. linearity < significance level (?), then the linear regression can be used to explain the influence of variables that exist. While the value of Sig. deviation from linearity shows what the data is used as linear. If the value of Sig. deviation from linearity > significance level (?), then the linear regression can be used to explain the influence of variables that exist (Widhiarso, 2010)
3.7 Data AnalysisThe whole process which starts immediately after data collection and ends at the point of interpretation and processing data is data analysis (Donald & Cooper, 2006). Chandran (2004) defines statistics as a discipline that provides the tools of analysis in research and one which refers to facts, information or data and to a system of data collection and analysis.
Descriptive statistics and inferential statistical techniques were used to analyze the data and the analyzed data was presented in frequency distributions tables and pie charts for ease of understanding and analysis. Multivariate regression Model based on Cross-sectional pooled data from the financial reports and other financial data will be used to assess the impact of venture capital financing on the growth of start ups and to complement the regression analysis correlation analysis will be used in the study to analyze the relationship between financial innovation and the financial institutions.
The data collected will be analyzed using the multiple linear regressions below;
Y=? +?1X1+?2X2+?3X3+?4X4 +e1
Where: Y= Financial Performance will be measured by return on equity
X1= Financial innovation
X4=Size of the firm
E = error
? = Coefficient of regression
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APPENDIX I: A LIST OF DEPOSIT TAKING SACCOS IN KENYA LICENCED BY SASRANO NAME OF SOCIETY
1. 2NK SACCO SOCIETY LTD
2. AFYA SACCO SOCIETY LTD
3. AGRO-CHEM SACCO SOCIETY LTD
4. AINABKOI SACCO SOCIETY LTD
5. AIPORTS SACCO SOCIETY LTD
6. ALL CHURCHES SACCO SOCIETY LTD
7. AMICA SACCO SOCIETY LTD
8. ARDHI SACCO SOCIETY LTD
9. ASILI SACCO SOCIETY LTD
10. BANDARI SACCO SOCIETY LTD
11. BARAKA SACCO SOCIETY LTD
12. BARATON UNIVERSITY SACCO SOCIETY LTD
13. BI- HIGH SACCO SOCIETY LTD
14. BIASHARA SACCO SOCIETY LTD
15. BIASHARA TOSHA SACCO SOCIETY LTD
16. BINGWA SACCO SOCIETY LTD
NO NAME OF SOCIETY
17. BORESHA SACCO SOCIETY LTD
18. CAPITAL SACCO SOCIETY LTD
19. CENTENARY SACCO SOCIETY LTD
20. CHAI SACCO SOCIETY LTD
21. CHUNA SACCO SOCIETY LTD
22. COSMOPOLITAN SACCO SOCIETY LTD
23. COUNTY SACCO SOCIETY LTD
24. DAIMA SACCO SOCIETY LTD
25. DHABITI SACCO SOCIETY LTD
26. DIMKES SACCO SOCIETY LTD
27. DUMISHA SACCO SOCIETY LTD
28. ECO-PILLAR SACCO SOCIETY LTD
29. EGERTON SACCO SOCIETY LTD
30. ELGON TEACHERS SACCO SOCIETY LTD
31. ELIMU SACCO SOCIETY LTD
32. ENEA SACCO SOCIETY LTD
33. FARIDI SACCO SOCIETY LTD
34. FARIJI SACCO SOCIETY LTD
35. FORTUNE SACCO SOCIETY LTD
36. FUNDILIMA SACCO SOCIETY LTD
37. GITHUNGURI DAIRY ; COMMUNITY SACCO
38. GOOD FAITH SACCO SOCIETY LTD
39. GOOD HOPE SACCO SOCIETY LTD
40. GOODWAY SACCO SOCIETY LTD
41. GUSII MWALIMU SACCO SOCIETY LTD
42. HARAMBEE SACCO SOCIETY LTD
43. HAZINA SACCO SOCIETY LTD
44. IG SACCO SOCIETY LTD
45. ILKISONKO SACCO SOCIETY LTD
46. IMARIKA SACCO SOCIETY LTD
47. IMARISHA SACCO SOCIETY LTD
48. IMENTI SACCO SOCIETY LTD
49. JACARANDA SACCO SOCIETY LTD
50. JAMII SACCO SOCIETY LTD
51. JOINAS SACCO SOCIETY LTD
52. JUMUIKA SACCO SOCIETY LTD
53. KAIMOSI SACCO SOCIETY LTD
54. KATHERA RURAL SACCO SOCIETY LTD
55. KENPIPE SACCO SOCIETY LTD
56. KENVERSITY SACCO SOCIETY LTD
57. KENYA ACHIEVAS SACCO SOCIETY LTD
58. KENYA BANKERS SACCO SOCIETY LTD
59. KENYA CANNERS SACCO SOCIETY LTD
60. KENYA HIGHLANDS SACCO SOCIETY LTD
61. KENYA POLICE SACCO SOCIETY LTD
62. KIMBILIO DAIMA SACCO SOCIETY LTD
63. KINGDOM SACCO SOCIETY LTD
64. KIPSIGIS EDIS SACCO SOCIETY LTD
65. KITE SACCO SOCIETY LTD
66. KITUI TEACHERS SACCO SOCIETY LTD
67. KMFRI SACCO SOCIETY LTD
68. KOLENGE TEA SACCO SOCIETY LTD
69. KONOIN SACCO SOCIETY LTD
NO NAME OF SOCIETY
70. KORU SACCO SOCIETY LTD
71. K-UNITY SACCO SOCIETY LTD
72. KWETU SACCO SOCIETY LTD
73. LAINISHA SACCO SOCIETY LTD
74. LAMU TEACHERS SACCO SOCIETY LTD
75. LENGO SACCO SOCIETY LTD
76. MAFANIKIO SACCO SOCIETY LTD
77. MAGADI SACCO SOCIETY LTD
78. MAGEREZA SACCO SOCIETY LTD
79. MAISHA BORA SACCO SOCIETY LTD
80. MENTOR SACCO SOCIETY LTD
81. METROPOLITAN NATIONAL SACCO SOCIETY LTD
82. MMH SACCO SOCIETY LTD
83. MOMBASA PORTS SACCO SOCIETY LTD
84. MUDETE TEA GROWERS SACCO SOCIETY LTD
85. MUKI SACCO SOCIETY LTD
86. MWALIMU NATIONAL SACCO SOCIETY LTD
87. MWIETHERI SACCO SOCIETY LTD
88. MWINGI MWALIMU SACCO SOCIETY LTD
89. MWITO SACCO SOCIETY LTD
90. NACICO SACCO SOCIETY LTD
91. NAFAKA SACCO SOCIETY LTD
92. NANDI FARMERS SACCO SOCIETY LTD
93. NASSEFU SACCO SOCIETY LTD
94. NATION SACCO SOCIETY LTD
95. NAWIRI SACCO SOCIETY LTD
96. NDEGE CHAI SACCO SOCIETY LTD
97. NDOSHA SACCO SOCIETY LTD
98. NEW FORTIS SACCO SOCIETY LTD
99. NG’ARISHA SACCO SOCIETY LTD
101. NRS SACCO SOCIETY LTD
102. NUFAIKA SACCO SOCIETY LTD
103. NYALA VISION SACCO SOCIETY LTD
104. NYAMBENE ARIMI SACCO SOCIETY LTD
105. NYAMIRA TEA SACCO SOCIETY LTD
106. NYATI SACCO SOCIETY LTD
107. OLLIN SACCO SOCIETY LTD
108. PATNAS SACCO SOCIETY LTD
109. PRIME TIME SACCO
110. PUAN SACCO SOCIETY LTD
111. QWETU SACCO SOCIETY LTD
112. SAFARICOM SACCO SOCIETY LTD
113. SHERIA SACCO SOCIETY LTD
114. SHIRIKA SACCO SOCIETY LTD
115. SHOPPERS SACCO SOCIETY LTD
116. SIMBA CHAI SACCO SOCIETY LTD
117. SIRAJI SACCO SOCIETY LTD
118. SKYLINE SACCO SOCIETY LTD
119. SMART CHAMPIONS SACCO SOCIETY LTD
120. SMARTLIFE SACCO SOCIETY LTD
121. SOLUTION SACCO SOCIETY LTD
122. SOTICO SACCO SOCIETY LTD
123. SOUTHERN STAR SACCO SOCIETY LTD
124. STAKE KENYA SACCO SOCIETY LTD
NO NAME OF SOCIETY
125. STIMA SACCO SOCIETY LTD
126. SUBA TEACHERS SACCO SOCIETY LTD
127. SUKARI SACCO SOCIETY LTD
128. SUPA SACCO SOCIETY LTD
129. TABASAMU SACCO SOCIETY LTD
130. TAI SACCO SOCIETY LTD
131. TAIFA SACCO SOCIETY LTD
132. TAQWA SACCO SOCIETY LTD
133. TARAJI SACCO SOCIETY LTD
134. TEMBO SACCO SOCIETY LTD
135. TENHOS SACCO SOCIETY LTD
136. THAMANI SACCO SOCIETY LTD
100. THE NOBLE SACCO SOCIETY LTD
137. TIMES U SACCO SOCIETY LTD
138. TOWER SACCO SOCIETY LTD
139. TRANS- ELITE COUNTY SACCO SOCIETY LTD
140. TRANSCOUNTIES SACCO SOCIETY LTD
141. TRANSNATION SACCO SOCIETY LTD
142. TRANS-NATIONAL TIMES SACCO SOCIETY LTD
143. UFANISI SACCO SOCIETY LTD
144. UKRISTO NA UFANISI WA ANGALICANA SACCO
145. UKULIMA SACO SOCIETY LTD
146. UNAITAS SACCO SOCIETY LTD
147. UNI-COUNTY SACCO SOCIETY LTD
148. UNISON SACCO SOCIETY LTD
149. UNITED NATIONS SACCO SOCIETY LTD
150. UNIVERSAL TRADERS SACCO SOCIETY LTD
151. VICTAS SACCO SOCIETY LTD
152. VIHIGA COUNTY SACCO SOCIETY LTD
153. VISION AFRICA SACCO SOCIETY LTD
154. VISION POINT SACCO SOCIETY LTD
155. WAKENYA PAMOJA SACCO SOCIETY LTD
156. WAKULIMA COMMERCIAL SACCO SOCIETY LTD
157. WANAANGA SACCO SOCIETY LTD
158. WANANCHI SACCO SOCIETY LTD
159. WANANDEGE SACCO SOCIETY LTD
160. WASHA SACCO SOCIETY LTD
161. WAUMINI SACCO SOCIETY LTD
162. WEVARSITY SACCO SOCIETY LTD
163. WINAS SACCO SOCIETY LTD
164. YETU SACCO SOCIETY LTD