REG NO: D61/85429/2016

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I declare that this is my original work and has not been submitted to any institution for academic purpose.
PAMELA 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
SIGN ……………………. DATE……………………….
Dr. Erastus Sifunjo
School of Business
University of Nairobi
SIGN ……………………. DATE……………………….

This project has been submitted for examination with my approval as the University Chairman.
Dr. Mirie Mwangi
School of Business
University of Nairobi

SIGN ……………………. DATE……………………….

ANOVA- 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
1.1 Background to the Study 1
1.1.1 Financial Innovation in SACCOs 2
1.1.2 Financial Performance of SACCOs in Kenya 3
1.1.3 The Effect of Financial Innovation on Financial Performance of SACCOs 4
1.1.4 Savings and Credit Co-operative Societies in Kenya 4
1.2 Research Problem 5
1.3 Research Objectives 6
1.4 Value of the Study 6
2.1 Introduction 8
2.2 Theoretical Review 8
2.2.1 Transaction Cost Innovation Theory 8
2.2.2 Schumpeter Innovation Theory 9
2.2.3 Diffusion Innovation Theory 9
2.2.4 Constraint Induced Innovation Theory 10
2.3 Determinants of Financial Performance 10
2.3.1 Operational Efficiency 10
2.3.2 Interest Rate 11
2.3.3 Size of the Company 11
2.3.4 Financial Innovation 12
2.4 Empirical Review 12
2.4.1 International Studies 12
2.4.2 Local Studies 14
2.5 Conceptual Framework 15
2.6 Summary of Literature Review 16
3.1 Introduction 17
3.2 Research Design 17
3.3 Population 17
3.4 Sample Design 17
3.5 Data Collection 18
3.6 Diagnostic test 18
3.6.1 Multicollinearity 18
3.6.2 Normality 18
3.6.3 Autocorrelation 19
3.6.4 Heteroscedasticity 19
3.6.5 Linearity test 19
3.7 Data Analysis 20


1.1 Background to the Study
SACCOs 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.
1.1.1 Financial Innovation in SACCOs
It 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 (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)
1.1.2 Financial Performance of SACCOs in Kenya
According 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 (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 (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.

1.1.3 The Effect of Financial Innovation on Financial Performance of SACCOs
Merton (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.
1.1.4 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) (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).
1.2 Research Problem
More 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 Objectives
This 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 Study
The 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.

2.1 Introduction
This 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 Review
A 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 Theory
According 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 Theory
Schumpeter (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 Theory
Innovation 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 Theory
Silber (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 Performance
Determinants 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 Rate
Interest 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 Company
The 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 Innovation
Various 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 Review
This 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 Studies
According 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 Studies

According 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 Framework
Mugenda (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

Control Variables

2.6 Summary of Literature Review
This 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.


3.1 Introduction
This 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 Design
A 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 Population
A population is an entire area from which a sample is drawn (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 Design
Stratified 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 Collection
The 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 test
Diagnostic 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 Multicollinearity
Multicolinearity 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 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 Autocorrelation
Linear 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 Heteroscedasticity
The 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 test
It 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 (Widhiarso, 2010)
3.7 Data Analysis
The 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
X2=Operational efficiency
X3=Interest rates
X4=Size of the firm
E = error
? = Coefficient of regression
a= Constant