The effect of integrated risk management systems on reducing non-performing loans in banking: a case study of First City Monument Bank
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Background of the Study
Non-performing loans (NPLs) pose a significant threat to the financial health of banking institutions. Integrated risk management systems have emerged as vital tools for monitoring, assessing, and mitigating credit risks that lead to high levels of NPLs. First City Monument Bank (FCMB) has implemented comprehensive risk management solutions that incorporate real-time data analytics, predictive modeling, and automated credit scoring to identify potential default risks early (Akinola, 2023). By integrating these systems into its credit operations, FCMB aims to streamline the loan approval process and improve the overall quality of its loan portfolio (Chukwu, 2024).
The adoption of integrated risk management systems facilitates a more accurate assessment of borrower creditworthiness. This technology-driven approach allows FCMB to capture and analyze a wide range of financial indicators and behavioral data, enabling proactive intervention measures before loans become non-performing (Ibrahim, 2025). Such systems enhance decision-making by providing actionable insights and reducing reliance on traditional, manual evaluation methods. Furthermore, the integration of risk management tools with the bank’s core systems supports a unified risk framework that aligns with global best practices and regulatory requirements.
However, the successful implementation of these systems is not without challenges. Issues such as data quality, system integration with existing legacy platforms, and the need for specialized training for credit analysts can hinder effectiveness. Moreover, external economic fluctuations can impact borrower performance in ways that are difficult to predict, even with advanced analytical tools. This study, therefore, seeks to evaluate the effect of integrated risk management systems on reducing NPLs at FCMB, examining the operational benefits, challenges, and strategic implications of deploying such technologies in a dynamic economic environment.
Statement of the Problem
Despite the adoption of integrated risk management systems at First City Monument Bank, challenges remain that affect the reduction of non-performing loans. One of the primary issues is the reliability of data inputs; inaccuracies and gaps in data can compromise the predictive accuracy of automated credit scoring models (Akinola, 2023). Additionally, integrating new risk management systems with existing legacy infrastructure poses technical challenges that may lead to delayed or erroneous risk assessments (Chukwu, 2024). These integration issues can undermine the timely identification of high-risk loans, thereby increasing the likelihood of defaults.
Another significant challenge is the need for continuous staff training to keep up with evolving risk management technologies. Without sufficient expertise, even the most advanced systems may fail to deliver accurate predictions, resulting in higher incidences of non-performing loans (Ibrahim, 2025). Furthermore, external factors such as economic downturns and market volatility may reduce the effectiveness of these systems by introducing unpredictable risk elements that are not fully captured by historical data. This scenario creates a gap between the anticipated benefits of integrated risk management and the actual reduction in NPLs observed in practice.
This study aims to explore these issues by analyzing the effectiveness of FCMB’s integrated risk management systems in reducing non-performing loans. The goal is to identify the key operational and technical challenges that hinder system performance and to propose strategies for improving data quality, system integration, and staff proficiency in risk assessment methodologies.
Objectives of the Study
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To evaluate the impact of integrated risk management systems on reducing non-performing loans at FCMB.
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To identify challenges related to data quality and system integration.
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To recommend strategies for enhancing risk management practices and reducing NPLs.
Research Questions
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How do integrated risk management systems affect the incidence of non-performing loans at FCMB?
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What data and integration challenges hinder the effectiveness of these systems?
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What measures can be implemented to improve risk assessment and reduce NPLs?
Research Hypotheses
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H₁: Integrated risk management systems significantly reduce the incidence of non-performing loans at FCMB.
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H₂: Data quality and integration challenges negatively impact the performance of risk management systems.
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H₃: Enhanced training and improved system integration lead to better credit risk assessment and lower NPL ratios.
Scope and Limitations of the Study
The study focuses on FCMB’s risk management systems and their effect on loan performance over a recent three-year period. Data is collected from internal credit reports, risk assessment outputs, and staff interviews. Limitations include the variability of external economic conditions and challenges in accessing comprehensive internal data.
Definitions of Terms
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Integrated Risk Management Systems: Technology-driven platforms that combine data analytics, predictive modeling, and real-time monitoring to assess and mitigate credit risk.
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Non-Performing Loans (NPLs): Loans in which the borrower is not making the agreed-upon payments.
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Legacy Infrastructure: Pre-existing technology systems that require integration with new risk management tools.
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