Background of the Study
Effective risk management is a cornerstone of sustainable banking, particularly in controlling credit risk and reducing non-performing loans (NPLs). First City Monument Bank (FCMB) has implemented an integrated risk management system that consolidates various risk assessment tools and real-time data analytics to monitor credit portfolios more effectively. This system facilitates early detection of potential defaults and enables proactive interventions to mitigate credit risk. The integration of risk management processes with automated reporting and predictive analytics has revolutionized the way FCMB manages its loan portfolio, aiming to reduce NPLs and improve overall asset quality (Uche, 2023).
Integrated risk management systems combine traditional credit analysis with modern data-driven approaches to provide a holistic view of risk exposures. By leveraging advanced algorithms and real-time monitoring, the bank can identify trends and anomalies in borrower behavior, thereby implementing timely corrective measures. Studies indicate that banks that employ integrated risk management systems experience lower levels of NPLs and improved financial stability (Ayo, 2024). FCMB’s initiative reflects a broader trend in the financial sector where technology-driven risk management is essential for competitive advantage and regulatory compliance.
Furthermore, the system enables better resource allocation by prioritizing high-risk accounts for more intensive monitoring and management. This targeted approach not only minimizes losses but also enhances the efficiency of the bank’s lending operations. However, challenges such as the integration of new risk management tools with existing legacy systems and the need for continuous data quality improvement remain critical. This study investigates the impact of integrated risk management systems on reducing NPLs at FCMB and explores strategies to overcome implementation challenges to further enhance credit portfolio performance (Chidera, 2025).
Statement of the Problem
Despite the deployment of an integrated risk management system at FCMB, several challenges persist in reducing non-performing loans. One significant issue is the difficulty in achieving seamless integration between modern risk analytics tools and legacy credit management systems, leading to data inconsistencies and delayed risk detection (Uche, 2023). Furthermore, the dynamic nature of credit markets means that risk models must be continuously updated to reflect changing borrower behavior and economic conditions. Failure to recalibrate these models in a timely manner can result in the underestimation of risk and an increase in NPLs (Ayo, 2024).
Another challenge is the resistance to adopting new risk management practices among traditional credit analysts, which may hinder the effective use of the integrated system. The reliance on historical data and conventional assessment methods can conflict with the predictive analytics offered by modern tools, thereby reducing the system’s overall efficacy. Additionally, the lack of standardized performance metrics to evaluate the success of the integrated risk management system complicates the measurement of its impact on NPL reduction (Chidera, 2025). These issues underscore the need for a comprehensive evaluation of the system’s effectiveness and the identification of strategies to enhance its performance.
Objectives of the Study
Research Questions
Research Hypotheses
Scope and Limitations of the Study
This study focuses on FCMB’s integrated risk management system and its effect on reducing non-performing loans. Limitations include data integration challenges, rapidly changing economic conditions, and resistance to change.
Definitions of Terms
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