1. Report Industry Investment Rating No relevant content provided. 2. Core Viewpoints of the Report - The report explores the application of Generative AI (GenAI) in tax and customs management for compliance risk analysis, aiming to enhance understanding of GenAI and provide guidelines for its implementation [13]. - GenAI has transformative potential for risk functions in tax and customs management, with the ability to revolutionize the relationship between analysts and technology [14]. - The future of GenAI likely involves integration into digital tools and management agent environments, with custom - tailored solutions emerging for professional fields [78]. 3. Summary by Relevant Catalogs II. Understanding Generative AI - GenAI is a type of AI that generates human - like content based on patterns learned from large amounts of data, using advanced machine - learning techniques [18]. - GenAI works by combining technologies for data processing and accessing pre - trained foundation models. It can be conceptually understood through input and parameters, foundation models, capabilities, and interactions [26]. III. Using GenAI for Compliance Risk Analysis Generalization and Understanding of Use Cases - GenAI use cases can be generalized beyond tax and customs administration, divided into four types based on subject - area expertise and autonomy: assistant AI, consultant AI, collaborative AI, and autonomous agent AI [30]. How AI Supports Compliance Risk Analysis - Deployment options for GenAI include commercial clouds, local deployments, and offline open - source options, accessible through APIs and SDKs [38]. - Analysts can access GenAI through tools like chatbots, virtual assistants, configurable agents, and it can be embedded in or replace traditional risk - analysis tools [39]. - GenAI can support risk analysis in four application scenarios: assistance, consultation, collaboration, and autonomous agent (replacement), consistent with compliance risk - management frameworks [40]. IV. Demonstration Using Managed Services - Three demonstrations are provided: natural - language research on the impact of a 25% currency devaluation on tax revenue and compliance; natural - language analysis of a large taxpayer's risk review; and natural - language analysis of distinguishing taxpayer risks [43]. V. Towards Local Applications - Most management agencies may choose local deployment configurations for GenAI to balance cost and security. An example of GenAI integration with the ASYCUDA system is presented, including interactions between AI agents [51]. VI. Operational Use Recommendation Guidelines - Understand when to use GenAI, considering its advantages and limitations, such as supporting open - ended research, using non - structured data, and enabling natural - language interaction [65]. - Clearly define human accountability for AI results, ensuring responsibility throughout the AI development and use process [69]. - Anticipate changes and prioritize employee training, including aspects like AI ethics, information security, and specific AI - tool usage [70]. - Build and protect a compliance information repository, which can enhance GenAI services through RAGs and fine - tuning [71]. - Adopt GenAI gradually and cautiously, starting with risk - assessed use cases and expanding for operational purposes while ensuring compliance with policies [77]. VII. Conclusion - GenAI can play multiple roles in compliance risk analysis, but human responsibility for its responsible use remains crucial. Its impact may be unbalanced globally, and future development will involve integration and customization [78].