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An evaluation of risk management practices on non-performing loan ratios in banking: a case study of First City Monument Bank

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  • NGN 5000

Background of the Study

Risk management practices are essential for maintaining a healthy loan portfolio in the banking sector. First City Monument Bank (FCMB) has implemented comprehensive risk management strategies to minimize the occurrence of non-performing loans (NPLs). These practices include rigorous credit risk assessments, continuous monitoring of borrower performance, and the integration of predictive analytics to identify potential defaults early (Okechukwu, 2023). By adopting a proactive approach, FCMB aims to maintain high asset quality, thereby protecting its financial stability and profitability. Advanced risk management frameworks enable the bank to adjust lending criteria and implement corrective measures promptly, which in turn reduces the likelihood of loan defaults (Adeniyi, 2024).

Empirical studies suggest that robust risk management practices are strongly correlated with lower NPL ratios and improved financial performance. However, challenges such as economic downturns, volatile market conditions, and borrower-specific factors can undermine even the most sophisticated risk management systems (Chinwe, 2023). This study seeks to evaluate the effectiveness of FCMB’s risk management practices on reducing non-performing loan ratios by analyzing historical loan data, risk assessment models, and qualitative feedback from risk managers. The findings will help identify best practices and areas requiring further refinement to enhance overall loan portfolio quality.

Statement of the Problem

Despite comprehensive risk management strategies, FCMB continues to face challenges in minimizing its non-performing loan ratio. One significant problem is the inherent unpredictability of borrower behavior during economic fluctuations, which can result in higher default rates despite robust risk assessment models (Emeka, 2023). In addition, integration issues between new predictive analytics tools and traditional credit evaluation methods sometimes lead to delays in identifying high-risk loans. These challenges contribute to a gap between the theoretical effectiveness of risk management practices and their practical impact on NPL ratios. The study aims to determine whether current risk management practices are effective in reducing non-performing loans and to identify the operational and economic factors that hinder their success.

Objectives of the Study

• To evaluate the impact of risk management practices on non-performing loan ratios at FCMB.

• To identify operational challenges that affect risk assessment accuracy.

• To recommend strategies for enhancing risk management to further reduce NPL ratios.

Research Questions

• How do current risk management practices affect non-performing loan ratios at FCMB?

• What operational challenges limit the effectiveness of risk assessment models?

• How can risk management practices be improved to reduce NPL ratios?

Research Hypotheses

• H1: Effective risk management practices significantly reduce non-performing loan ratios.

• H2: Integration challenges between new and traditional risk assessment tools negatively impact NPL reduction.

• H3: Enhanced predictive analytics improve overall loan portfolio performance.

Scope and Limitations of the Study

This study focuses on FCMB’s risk management practices over the past three years, using loan performance data and risk evaluation reports. Limitations include external economic factors and potential biases in risk assessment methodologies.

Definitions of Terms

• Risk Management Practices: Procedures and systems used to assess and mitigate credit risk.

• Non-Performing Loan Ratios: The proportion of loans in a bank’s portfolio that are in default or close to default.

• Predictive Analytics: The use of data and statistical algorithms to forecast future outcomes.

 





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