An evaluation of risk management system integration on improving loan performance in banking: a case study of First City Monument Bank
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Background of the Study
Effective risk management is crucial for maintaining a healthy loan portfolio and minimizing credit losses in banking. First City Monument Bank (FCMB) has enhanced its risk management processes by integrating advanced risk management systems that employ predictive analytics, real-time monitoring, and automated credit assessments. This integration allows the bank to continuously track borrower performance and identify potential risks early, enabling timely interventions to reduce loan defaults (Okeke, 2023). The system combines data from various sources to provide a holistic view of credit risk, ensuring that lending decisions are informed by comprehensive, real-time information (Adebayo, 2024). Such integration not only improves asset quality but also aligns FCMB’s risk management practices with international best practices. However, challenges such as integrating new systems with legacy infrastructure and ensuring consistent data quality can affect the overall effectiveness of these enhancements.
Statement of the Problem
Despite the integration of advanced risk management systems at FCMB, challenges persist in improving loan performance. Integration issues between new risk management tools and existing legacy systems may lead to data discrepancies and delays in risk assessment (Chukwu, 2023). These delays can result in missed opportunities for early intervention, leading to a higher incidence of non-performing loans (NPLs). Additionally, the dynamic nature of the credit market requires constant updates to risk models, and any lag in these updates can adversely affect lending decisions. Inadequate staff training on using these systems further compromises the system’s potential. Consequently, these issues undermine the bank’s ability to optimize its loan portfolio and reduce NPLs effectively.
Objectives of the Study
- To evaluate the impact of integrated risk management systems on loan performance at FCMB.
- To identify integration and data quality challenges affecting risk assessment.
- To recommend strategies for optimizing risk management to reduce non-performing loans.
Research Questions
- How does risk management system integration affect loan performance at FCMB?
- What challenges hinder the effective integration of new risk management tools?
- Which strategies can optimize risk management and reduce NPLs?
Research Hypotheses
- H₁: Integrated risk management systems significantly improve loan performance.
- H₂: Integration challenges with legacy systems negatively impact risk assessment accuracy.
- H₃: Regular updates and staff training enhance credit 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, risk reports, and interviews with risk managers. Limitations include market volatility and potential data confidentiality issues.
Definitions of Terms
- Risk Management System Integration: The consolidation of advanced risk assessment tools with existing lending operations.
- Loan Performance: The success of a bank’s loan portfolio measured by default rates and returns.
- Non-performing Loans (NPLs): Loans that are in default or close to being in default.
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