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“看不懂”的跨国报销单:中企出海差旅费控如何破局
经济观察报· 2025-11-04 14:35
Core Viewpoint - The article highlights the challenges faced by Chinese companies in managing cross-border travel expenses, emphasizing the need for effective cost control and compliance with local regulations in overseas markets [1][4][10]. Group 1: Challenges in Cross-Border Travel Expense Management - Companies are struggling with the verification of cross-border travel expense receipts due to language barriers and varying formats, leading to increased operational costs [2][3][6]. - The proportion of pre-market research and business negotiation expenses in overall operational costs has exceeded 20%, prompting companies to reassess their investment returns in overseas ventures [4][10]. - Many companies face compliance risks due to misunderstandings or lack of attention to local regulations, which complicates financial management [10][11]. Group 2: Current Solutions and Strategies - Companies are implementing two main strategies: employing trusted local staff for financial management and setting fixed annual expense limits for overseas travel [7][8]. - Despite these measures, issues persist, such as local financial staff potentially engaging in fraudulent activities and departments exhausting their travel budgets too quickly [8][12]. - To further control expenses, some companies are linking financial department bonuses to the effectiveness of travel expense management [11][12]. Group 3: Technological Solutions and Future Directions - The introduction of SaaS solutions for travel management is seen as a potential way to enhance compliance and cost control, although challenges remain regarding user experience and cost-effectiveness [15][16]. - AI and data-driven approaches are suggested to improve the efficiency of expense verification and compliance management, moving away from traditional reliance on individual judgment [17][18]. - The successful implementation of these technologies will depend on companies' ability to adapt their financial management philosophies to incorporate AI and data analytics [16][18].