A Case Study Research: Reducing the Lead Time of the Bank Reconciliation Process in the Treasury Division at Abu Dhabi Ports

Abstract

The maritime industry is the cornerstone of the world economy and global trade, hence financial operations within the industry are crucial to its success. The diverse and complicated activities of the industry are essential to its growth, but they also produce complex transactions that pose significant challenges for companies. As a result, it is important to properly handle and efficiently process complex accounting transactions to produce reliable information that is useful for making financial decisions. Bank reconciliation is one of the fundamental accounting processes for tracking irregular transactions, rectifying errors, and identifying fraud to reveal the accurate financial situation of the company. Therefore, regular and quick reconciliation can help in gaining greater knowledge of the financial functions of the company to ensure its financial stability and achieve overall success.

This study presents a case study utilizing the Lean Six Sigma methodology. The methodology is used to show its applicability in enhancing maritime finance by reducing the lead time of the bank reconciliation procedure at one of the biggest maritime companies in the United Arab Emirates. Moreover, this research will fill the gap in applying process improvement methodologies to improve aspects of maritime finance, since further research is required to tackle particular problems in maritime financing using Six Sigma and Lean methodologies. This will ultimately add to the level of knowledge and experience in the application of Six Sigma and Lean in maritime finance.

DMAIC has been used as a data-driven approach to improve existing processes. The DMAIC phases act as a framework to solve problems and improve processes, with each phase having specific objectives to achieve and tools to employ. In this case study, the phases of Define, Measure, Analyze, and Improve have been executed; however, Control has not been implemented due to time and managerial restrictions.

Date of Award	Aug 2023
Original language	American English
Supervisor	Maher Maalouf (Supervisor)