Development of a Financial Data Reconciliation Model for Night Audits to Improve Financial Report Accuracy in Four-Star Hotels in Medan

Abstract

This study aims to develop a more effective financial data reconciliation model to support night audit processes in four-star hotels in Medan. Financial data reconciliation is crucial to ensure accurate transaction records, thereby enhancing the transparency and integrity of financial reports. However, four-star hotels, with high transaction volumes, often face challenges in maintaining accurate data matching, which can stem from technological limitations and a lack of standardized recording procedures. This study uses a SWOT analysis approach to identify strengths, weaknesses, opportunities, and threats in the reconciliation process. Through in-depth interviews and documentation studies, the research develops a reconciliation model that considers the role of technology, staff training, and inter-departmental procedures. Findings show that applying anomaly detection technology and standardizing SOPs can improve efficiency and accuracy in night audit processes. This proposed model is expected to guide hotel management in enhancing financial report quality and supporting better decision-making. The study also provides both practical and theoretical contributions to developing financial reconciliation methods in the hospitality industry.