Loan Issuance Process Optimization "To-Be" Model  (Case Study: Bank of Georgia)

Maya Gonashvili  Tamar Agladze

Journal number 2 ∘ Maya Gonashvili ∘ Tamar Agladze ∘
Loan Issuance Process Optimization "To-Be" Model (Case Study: Bank of Georgia)

journal N2 2025

Expanded Summary

The banking sector frequently faces challenges stemming from the inefficient utilization of resources during process execution, leading to a decline in both qualitative and quantitative performance indicators. This issue remains a persistent focus for Georgian banking institutions. Compounding this, the pervasive drive towards digitalization of business processes, inherent in the evolving digital economy, necessitates robust process optimization strategies.

This study aimed to address these critical issues and prevalent challenges within the Georgian banking sector. To achieve this, a comprehensive research effort was undertaken from April to May 2025. The scope of the investigation encompassed various facets of banking operations, including process analysis, optimization techniques, customer behavior research, and their collective impact on operational efficiency.

This article specifically presents an in-depth analysis of loan issuance processes within the banking sector. We examine and analyze the "To-Be" optimization model and its associated efficiency indicators. Building upon a robust research methodology, a novel "To-Be" optimization model was developed. The effectiveness of this model and the interrelationships of direct and indirect factors influencing the loan issuance process were rigorously tested using SPSS statistical software.

Our research on optimizing loan issuance processes within banking structures involved a meticulous study of existing actions, which were subsequently grouped by their inherent value. We identified that many actions, while part of the process, constituted non-value-adding waste. The primary objective at this stage was to minimize these non-value-creating actions and associated waste. This was achieved through the application of the chronometry method, involving one month of observations, conducted twice weekly at consistent times. Following the identification of process waste, we pinpointed specific non-value-creating activities, considering established sources of useless waste. The observation findings were then systematically categorized into three principal groups of waste sources.

The findings unequivocally demonstrated that these identified waste source categories contribute to significant inefficiencies, including unnecessary process waste, frequent changes, and systemic inflexibility. A key discovery was that the root causes of this inflexibility were often linked to surging loan demand and the consequent inability to fulfill customer requests within desired timeframes.

Furthermore, a crucial aspect of this study involved establishing the correlation between direct and indirect factors influencing the loan issuance process, facilitated by SPSS. This interdependency is visually represented through an infographic, with data calculated based on Pearson correlation coefficients. Notably, a negative correlation was observed between the cycle time of loan issuance processes and personnel satisfaction, an critical insight for the proposed new model.

The developed "To-Be" optimized model comprises three distinct stages: input, optimization process, and output. The anticipated outcomes of this model, as demonstrated in the output stage, include reduced processing time, decreased operational costs, increased revenue, enhanced monitoring capabilities, and continuous process improvement. The model's efficacy was empirically validated through SPSS testing, specifically designed to address the core research questions.

The effectiveness of our newly developed optimization model is quantitatively assessed across key performance indicators: reduction in cycle time, reduction in costs, and increase in revenue. To quantify these improvements, we employed specific formulas: ΔT1=Tas−is−Tto−be for time reduction, ΔC1=Cas−is−Cto−be for cost reduction, and ΔR1=Rto−be−Ras−is for revenue increase. The resultant calculations were subsequently analyzed using the Lean methodology.

When comparing these calculated indicators with the results obtained from our chronometry analysis, the application of the Lean method clearly indicates significant potential for improvement:

Operational costs can be reduced by 15-30%.
Process execution cycle time can be reduced by 20-40%, leading to faster service delivery, minimized waiting times, and greater system flexibility.
The number of procedural steps can be reduced by 25-50% through the elimination of unnecessary and inefficient operations.
Client service time can be shortened by 10-35%, directly enhancing customer satisfaction and reinforcing reliability.
Employee productivity is projected to increase by 15-25% as a direct result of automation, standardization, and process optimization efforts.

Considering these findings as achievable target benchmarks, the projected performance indicators for the loan issuance process under the Lean methodology can be outlined accordingly.

In conclusion, our research has successfully identified critical weaknesses within the Bank of Georgia's loan issuance process, which directly impact customer satisfaction and, consequently, the bank's overall revenue and brand image. The study underscores the imperative for business process reengineering and comprehensive process optimization within the Bank of Georgia's operational framework. By strategically implementing the Lean approach and systematically eliminating non-value-creating operations, we have demonstrated the tangible potential for waste minimization. This led to the successful development of the "To-Be" model for loan issuance.

Therefore, to optimize banking processes (specifically loan issuance) and enhance banking service efficiency, we recommend:

Integrating business processes into the overarching strategic plan (action plan). This will enable continuous monitoring, evaluation, and improvement based on specific indicators and predefined target benchmarks.
Adopting the Lean-Six Sigma strategy for business process optimization, along with clearly defining necessary changes for implementation.
Developing a precise change plan/schedule and fostering close communication with personnel regarding these changes, coupled with targeted personnel retraining and qualification enhancement.
Continuously refining the personnel evaluation and incentive system. This comprehensive approach will mitigate change-related risks (e.g., stress, tension, low morale, reduced productivity) and, ultimately, ensure the successful implementation of optimization processes and the "To-Be" model.

Keywords: Business Processes, Banking Sector, Optimization Model "To-Be", Efficiency Indicators, Research.

EKONOMISTI The international scientific and analytical, reviewed, printing and electronic journal of Paata Gugushvili Institute of Economics of Ivane Javakhishvili Tbilisi State University

DOI: 10.36172/EKONOMISTI DOI: 10.52340/EKONOMISTI E ISSN 2346-8432 Print ISSN 1987-6890	Journal number 2 ∘ Maya Gonashvili ∘ Tamar Agladze ∘ Loan Issuance Process Optimization "To-Be" Model (Case Study: Bank of Georgia) journal N2 2025 Expanded Summary The banking sector frequently faces challenges stemming from the inefficient utilization of resources during process execution, leading to a decline in both qualitative and quantitative performance indicators. This issue remains a persistent focus for Georgian banking institutions. Compounding this, the pervasive drive towards digitalization of business processes, inherent in the evolving digital economy, necessitates robust process optimization strategies. This study aimed to address these critical issues and prevalent challenges within the Georgian banking sector. To achieve this, a comprehensive research effort was undertaken from April to May 2025. The scope of the investigation encompassed various facets of banking operations, including process analysis, optimization techniques, customer behavior research, and their collective impact on operational efficiency. This article specifically presents an in-depth analysis of loan issuance processes within the banking sector. We examine and analyze the "To-Be" optimization model and its associated efficiency indicators. Building upon a robust research methodology, a novel "To-Be" optimization model was developed. The effectiveness of this model and the interrelationships of direct and indirect factors influencing the loan issuance process were rigorously tested using SPSS statistical software. Our research on optimizing loan issuance processes within banking structures involved a meticulous study of existing actions, which were subsequently grouped by their inherent value. We identified that many actions, while part of the process, constituted non-value-adding waste. The primary objective at this stage was to minimize these non-value-creating actions and associated waste. This was achieved through the application of the chronometry method, involving one month of observations, conducted twice weekly at consistent times. Following the identification of process waste, we pinpointed specific non-value-creating activities, considering established sources of useless waste. The observation findings were then systematically categorized into three principal groups of waste sources. The findings unequivocally demonstrated that these identified waste source categories contribute to significant inefficiencies, including unnecessary process waste, frequent changes, and systemic inflexibility. A key discovery was that the root causes of this inflexibility were often linked to surging loan demand and the consequent inability to fulfill customer requests within desired timeframes. Furthermore, a crucial aspect of this study involved establishing the correlation between direct and indirect factors influencing the loan issuance process, facilitated by SPSS. This interdependency is visually represented through an infographic, with data calculated based on Pearson correlation coefficients. Notably, a negative correlation was observed between the cycle time of loan issuance processes and personnel satisfaction, an critical insight for the proposed new model. The developed "To-Be" optimized model comprises three distinct stages: input, optimization process, and output. The anticipated outcomes of this model, as demonstrated in the output stage, include reduced processing time, decreased operational costs, increased revenue, enhanced monitoring capabilities, and continuous process improvement. The model's efficacy was empirically validated through SPSS testing, specifically designed to address the core research questions. The effectiveness of our newly developed optimization model is quantitatively assessed across key performance indicators: reduction in cycle time, reduction in costs, and increase in revenue. To quantify these improvements, we employed specific formulas: ΔT1=Tas−is−Tto−be for time reduction, ΔC1=Cas−is−Cto−be for cost reduction, and ΔR1=Rto−be−Ras−is for revenue increase. The resultant calculations were subsequently analyzed using the Lean methodology. When comparing these calculated indicators with the results obtained from our chronometry analysis, the application of the Lean method clearly indicates significant potential for improvement: Operational costs can be reduced by 15-30%. Process execution cycle time can be reduced by 20-40%, leading to faster service delivery, minimized waiting times, and greater system flexibility. The number of procedural steps can be reduced by 25-50% through the elimination of unnecessary and inefficient operations. Client service time can be shortened by 10-35%, directly enhancing customer satisfaction and reinforcing reliability. Employee productivity is projected to increase by 15-25% as a direct result of automation, standardization, and process optimization efforts. Considering these findings as achievable target benchmarks, the projected performance indicators for the loan issuance process under the Lean methodology can be outlined accordingly. In conclusion, our research has successfully identified critical weaknesses within the Bank of Georgia's loan issuance process, which directly impact customer satisfaction and, consequently, the bank's overall revenue and brand image. The study underscores the imperative for business process reengineering and comprehensive process optimization within the Bank of Georgia's operational framework. By strategically implementing the Lean approach and systematically eliminating non-value-creating operations, we have demonstrated the tangible potential for waste minimization. This led to the successful development of the "To-Be" model for loan issuance. Therefore, to optimize banking processes (specifically loan issuance) and enhance banking service efficiency, we recommend: Integrating business processes into the overarching strategic plan (action plan). This will enable continuous monitoring, evaluation, and improvement based on specific indicators and predefined target benchmarks. Adopting the Lean-Six Sigma strategy for business process optimization, along with clearly defining necessary changes for implementation. Developing a precise change plan/schedule and fostering close communication with personnel regarding these changes, coupled with targeted personnel retraining and qualification enhancement. Continuously refining the personnel evaluation and incentive system. This comprehensive approach will mitigate change-related risks (e.g., stress, tension, low morale, reduced productivity) and, ultimately, ensure the successful implementation of optimization processes and the "To-Be" model. Keywords: Business Processes, Banking Sector, Optimization Model "To-Be", Efficiency Indicators, Research.