Enhancing CI/CD Pipelines to Mitigate Downtime in the Banking Industry: A Case Study of GTBank and FirstBank Outages in 2024

The digital banking ecosystem has transformed financial transactions, offering customers seamless access to banking services. However, system downtimes in leading financial institutions, such as GTBank and First Bank, have raised concerns regarding customer experience, transaction failures, and financial losses. This study empirically investigates the impact of banking downtimes on customers by analyzing key factors such as failed transactions, delayed payments, customer dissatisfaction, access issues, and revenue loss. Through a combination of statistical regression analysis and exploratory data visualization with the help of python programming language statistical tools, our findings reveal that system downtime significantly affects customer trust and transaction success rates. The regression results indicate a negative relationship between downtime duration and access to banking services (β = -0.4975, p < 0.01), reinforcing the hypothesis that frequent service disruptions erode customer confidence. Furthermore, while transaction failures and revenue loss show a negative correlation with downtime, their statistical significance is weaker, suggesting that customers may adapt to short-term disruptions but lose trust over prolonged periods. The descriptive analysis of downtime frequency highlights that banking disruptions occur sporadically, with a mean downtime duration of approximately 9.12 hoursper event. However, extreme cases show downtimes lasting up to 24 hours, exacerbating customer frustration and financial uncertainty. The data visualization further supports the hypothesis that system instability leads to an increase in failed transactions and delayed payments, directly contributing to customer dissatisfaction. This study underscores the urgent need for financial institutions to enhance operational resilience through robust IT infrastructure, proactive downtime mitigation strategies, and customer communication frameworks. Banks that fail to address these systemic issues risk not only financial losses but also long-term reputational damage and regulatory scrutiny. Future research should explore machine learning-driven predictive maintenance to minimize downtime occurrences and enhance customer experience in the digital banking sector.