Transaction Income and Financial Performance of Deposit-Taking Savings and Credit Cooperative Societies in Nairobi County, Kenya

Purpose: Deposit-taking Savings and Credit Co-operative Societies in Kenya are important due to the role they play in financial intermediation. The deposit-taking SACCOs pool members’ deposits and issue loans to them at a predetermined rate of interest. The financial performance of deposit-taking SACCOs is highly dependent upon the interest income they receive from loans. Consequently, diversification by deposit-taking SACCOs into non-interest income has steadily been demanded due to the need for financial institutions to ground their financial performance in the wake of declining income, mainly due to overdependence on interest income. This study sought to determine the effect of transaction income on the financial performance of deposit-taking SACCOs in Nairobi County in Kenya. Methodology: The study targeted all 39 DT-SACCOs in Nairobi County, Kenya; hence, a census study was conducted. Descriptive statistics, including frequencies, averages, and root mean square deviation, were produced for all the numerical data. Inferential statistics was done using the panel regression model. The results were presented using tables. A data collection matrix was used to collect data on the financial performance of the DTSACCOs, and was analyzed using STATA 18, and the outcome is presented in tables using statistics such as means, standard deviation, frequencies, and percentages. Findings: The findings of the panel regression model indicated a positive and significant effect between transaction income and the financial performance of DT-SACCOs in Nairobi County, Kenya. Unique Contribution to Theory, Practice and Policy: The study recommends that DTSACCOs in Nairobi County, Kenya, establish a diversified transaction-based revenue policy that allows them to sustainably monetize essential member services while ensuring affordability and transparency. The policy can be done by introducing a tiered pricing structure based on the type of service, frequency of usage, and channel used (e.g., mobile, in-person, or digital).