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An evaluation of digital transformation on business banking risk assessment: A case study of Wema Bank, Lagos

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Background of the Study
Digital transformation has emerged as a catalyst for improving risk assessment processes in business banking. Wema Bank in Lagos has embraced digital transformation strategies that integrate advanced analytics, machine learning, and real-time data processing into its risk assessment framework. These digital tools enhance the accuracy and timeliness of credit risk evaluations by analyzing large volumes of structured and unstructured data, thereby enabling more proactive risk mitigation strategies (Oluwaseun, 2023; Adenola, 2024). The adoption of digital transformation not only streamlines risk assessment but also improves the transparency and efficiency of decision-making processes. Enhanced digital systems allow for continuous monitoring of borrower performance, early detection of potential defaults, and more dynamic adjustments to credit policies. However, the integration of digital technologies with legacy systems, cybersecurity threats, and high implementation costs remain significant challenges. These factors may impede the full potential of digital transformation in enhancing risk assessment, thereby affecting the bank’s overall risk management and profitability (Chukwu, 2025). This study evaluates the impact of digital transformation on business banking risk assessment at Wema Bank, aiming to identify both the benefits and challenges of these technological innovations.

Statement of the Problem
Wema Bank faces challenges in effectively leveraging digital transformation to enhance its risk assessment processes. Integration issues between new digital tools and existing legacy systems often lead to data discrepancies and delayed risk evaluations, which can result in suboptimal credit decisions. Additionally, cybersecurity risks and the high costs associated with continuous technology upgrades further constrain the bank’s ability to maintain a robust digital risk assessment framework. A lack of adequately trained personnel to manage advanced analytical systems also hinders the optimization of digital transformation initiatives. These challenges collectively reduce the accuracy and timeliness of risk assessments, thereby increasing the likelihood of non-performing loans and adversely affecting the bank’s overall risk management performance. Addressing these issues is critical to ensuring that digital transformation translates into enhanced risk assessment and improved business banking outcomes.

Objectives of the Study

  1. To evaluate the impact of digital transformation on risk assessment processes in business banking at Wema Bank.
  2. To identify integration, cybersecurity, and training challenges affecting digital risk assessment.
  3. To recommend strategies for optimizing digital transformation initiatives to improve risk management.

Research Questions

  1. How does digital transformation influence risk assessment in business banking at Wema Bank?
  2. What challenges impede the integration of digital risk assessment tools with legacy systems?
  3. What measures can enhance the accuracy and efficiency of digital risk assessment?

Research Hypotheses

  1. H₁: Digital transformation significantly improves the accuracy of risk assessment in business banking.
  2. H₂: Integration challenges negatively impact the effectiveness of digital risk assessment.
  3. H₃: Continuous staff training and cybersecurity enhancements improve digital risk management outcomes.

Scope and Limitations of the Study
The study focuses on Wema Bank’s business banking division in Lagos, reviewing digital transformation initiatives related to risk assessment over recent years. Limitations include evolving technology standards and restricted access to internal risk data.

Definitions of Terms

  • Digital Transformation: The integration of digital technology into all areas of a business.
  • Risk Assessment: The process of identifying, analyzing, and managing risks.
  • Non-performing Loans: Loans that are in default or at risk of default.




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