The strength of banking systems is key in the stimulation of economic growth and development, creation of employment, domestic and foreign investment and poverty reduction. The banking sector in Kenya has been earmarked as a core pillar for the realization of Vision 2030 of making Kenya a middle-income nation through the provision of financial services and promoting macro-economic stability. From 2013 to 2019, the default rate demonstrates a loan default increase in the Kenyan banking industry. The expanding level of default rate among Kenyan business banks has troubled different partners and general society generally. Increasing levels of credit default rates diminishes the liquidity of banks, their productivity and in this way their profitability. This investigation subsequently related credit data sharing contribution on default rates of credits given by banks in Kenya with reference to client credit reports sharing, client credit reports pulling and expenses of credit data sharing. The investigation is pegged on the information asymmetry hypothesis, the adverse selection hypothesis, moral hazard hypothesis lastly the hypothesis of credit information sharing. This research embraced an explanatory research plan targeting all 12 banks listed at the NSE and source data from their reports. Customer credit reports shared, customer credit reports pulled and costs incurred on credit information sharing explained 80.72% of default rates of loans issued by listed commercial banks. Panel regression of coefficients findings indicated that customer credit reports sharing is negatively and significantly related to default rates on loans (β =0.0446, p=0.000). Customer credit reports pulling and default rates of loans issued by listed commercial banks have a negative and significant relationship (β =-0.03351, p=0.008) while costs incurred on credit information sharing has a positive and significant relationship (β =0.098018, p=0.000) with default rates of loans issued by listed commercial banks. Bank size has a moderating effect of bank size on credit information sharing and default rates of loans issued by listed banks in Kenya since R2 rose from 0.8072 before moderation to 0.8615 after moderation. The study concluded that customer credit reports sharing, customer credit reports pulled and costs incurred on credit information sharing affects default rates of loans issued by commercial banks. This study recommends that commercial banks may need to adopt credit scoring methods to facilitate efficient pulling of credit information from potential loan borrowers. With the adoption of credit scoring, a bank is able to extract information from the main credit bureaus and apply a proprietary algorithm in assessing the risk profile of each applicant. Commercial banks may need to come up with an integrated information system for ensuring that customers get prompt notification on their loan status and any other information. All commercial banks management ought to put emphasis on operational efficiencies as a way of eliminating redundant operational cost and as a result improving financial performance. The study suggests the need for future studies to investigate other exogenous factors influencing default rates among borrowers in commercial banks
