Loan Portfolio Risk and Capital Adequacy in Kenya’s Deposit-Taking Savings and Credit Cooperative Societies: Implications for Financial Stability and Inclusive Growth

Deposit-Taking Savings and Credit Cooperative Societies (DT-SACCOs) constitute a pivotal segment of Kenya's financial system by fostering domestic savings, facilitating affordable credit access, and advancing financial inclusion, particularly among underserved populations.Despite this critical role, concerns have intensified over the sector's financial resilience due to escalating levels of loan portfolio risk, persistent regulatory non-compliance, and eroding capital adequacy ratios (CAR).These vulnerabilities have been exacerbated by the absence of a lender of last resort, thereby exposing member deposits to elevated systemic risk and constraining the flow of credit to key productive sectors-including micro, small, and medium enterprises (MSMEs), agriculture, and affordable housing.Such constraints are increasingly viewed as impediments to the Bottom-Up Economic Transformation Agenda and to Kenya's broader commitments under the Sustainable Development Goals, particularly those concerning poverty eradication, decent employment, and industrial development.To investigate the interplay between loan portfolio risk and capital adequacy, a positivist research philosophy and a descriptive cross-sectional design were employed.The target population comprised all 174 licensed DT-SACCOs in Kenya.A simple random sampling technique was used, and a 96.5% response rate was achieved.Data were extracted from audited financial statements through a structured collection instrument and analysed using linear regression techniques.Empirical results indicated a statistically significant positive association between loan portfolio risk and capital adequacy ( = 0.0569, p = 0.012), suggesting that increased risk exposure may prompt DT-SACCOs to strengthen capital buffers, either through regulatory compulsion or institutional prudence.It is recommended that DT-SACCOs adopt advanced credit risk mitigation strategies, including AI-enabled credit scoring systems, predictive early warning indicators, and operational automation via chatbots to enhance real-time monitoring and reduce manual error.Emphasis is also placed on the adoption of forward-looking metrics such as expected credit losses (ECL) and scenario-based stress testing under the IFRS 9 framework.Regulatory bodies are urged to enhance supervisory guidance and support financial literacy initiatives among members.Furthermore, capacity building, the promotion of digital loan syndication models, and collaborative risk-sharing frameworks are proposed to fortify capital adequacy, enhance institutional resilience, and ensure long-term sectoral stability.