An appraisal of risk management process enhancements on reducing non-performing loans in banking: a case study of First City Monument Bank
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Background of the Study
Risk management process enhancements are critical for reducing non-performing loans (NPLs) and ensuring the financial stability of banks. First City Monument Bank (FCMB) has integrated advanced risk management strategies into its lending operations, including the use of real-time data analytics, automated credit scoring, and continuous monitoring of loan performance (Akinola, 2023). These enhancements allow the bank to better assess borrower creditworthiness and to identify early signs of default, thereby enabling timely interventions such as loan restructuring or additional collateral requirements.
FCMB’s risk management framework is built on a foundation of technology-driven processes that combine traditional credit assessment methods with modern analytics. This integration improves decision-making by providing a more accurate prediction of borrower behavior and a proactive approach to risk mitigation (Chukwu, 2024). The bank’s efforts are further supported by regular internal audits, compliance checks, and staff training programs, all aimed at ensuring that the risk management processes are robust and effective in reducing NPLs. These measures not only protect the bank’s profitability but also contribute to a healthier credit portfolio and overall financial resilience (Ibrahim, 2025).
Despite the apparent benefits, several challenges hinder the full effectiveness of risk management process enhancements. Data quality issues, integration difficulties with legacy systems, and the dynamic nature of market conditions can limit the accuracy of predictive models. Additionally, the rapid pace of technological change requires continuous updates and staff training, which may strain resources and impact operational efficiency. This study evaluates the impact of risk management process enhancements on reducing NPLs at FCMB, analyzing both the operational benefits and the challenges encountered, and offering recommendations for further improvement.
Statement of the Problem
Although FCMB has enhanced its risk management processes to reduce non-performing loans, challenges remain in achieving the desired level of loan portfolio quality. One major problem is the accuracy of predictive models, which is often compromised by data quality issues and integration challenges with legacy systems (Akinola, 2023). These issues can result in delayed or inappropriate risk assessments, leading to a higher incidence of NPLs. Additionally, the complexity of integrating advanced analytics with traditional lending processes may cause inconsistencies in credit evaluation, further exacerbating the problem (Chukwu, 2024).
Moreover, rapid changes in the economic environment, including market volatility and regulatory shifts, add layers of complexity to risk assessment processes, making it difficult to predict borrower behavior accurately. Insufficient continuous training for risk management staff also hampers the effective utilization of new technologies, which diminishes the potential benefits of process enhancements (Ibrahim, 2025). These challenges create a gap between the theoretical advantages of enhanced risk management and the practical outcomes observed in FCMB’s loan portfolio.
This study aims to identify the specific factors that impede the effectiveness of FCMB’s risk management enhancements and to propose actionable strategies for reducing NPLs. By analyzing loan performance data, conducting staff interviews, and reviewing internal risk assessments, the research will provide insights into improving risk evaluation accuracy and operational efficiency.
Objectives of the Study
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To evaluate the impact of risk management process enhancements on reducing non-performing loans at FCMB.
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To identify challenges in data quality and system integration affecting risk assessment.
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To recommend strategies for improving risk management accuracy and reducing NPLs.
Research Questions
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How do risk management enhancements affect non-performing loans at FCMB?
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What challenges hinder the effective implementation of these enhancements?
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What measures can improve risk assessment and reduce NPLs?
Research Hypotheses
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H₁: Enhanced risk management processes significantly reduce non-performing loans at FCMB.
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H₂: Data quality and integration challenges negatively affect risk assessment accuracy.
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H₃: Continuous training and system upgrades improve risk management effectiveness.
Scope and Limitations of the Study
This study focuses on FCMB’s risk management practices over the past three years, using internal loan performance reports, risk assessment data, and interviews with risk management personnel. Limitations include external economic variability and the evolving nature of credit risk.
Definitions of Terms
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Risk Management Process Enhancements: Improvements in systems and practices to assess and mitigate credit risk.
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Non-Performing Loans (NPLs): Loans that are in default or close to being in default.
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Predictive Models: Statistical tools used to forecast future borrower behavior.
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