AI Application in Anti-Money Laundering for Sustainable and Transparent Financial Systems

• URL: http://arxiv.org/abs/2512.06240v1
• Date: Sat, 06 Dec 2025 01:37:24 GMT
• Title: AI Application in Anti-Money Laundering for Sustainable and Transparent Financial Systems
• Authors: Chuanhao Nie, Yunbo Liu, Chao Wang,
• Abstract summary: Money laundering and financial fraud remain major threats to global financial stability, costing trillions annually and challenging regulatory oversight.<n>This paper reviews how artificial intelligence (AI) applications can modernize Anti-Money Laundering (AML) by improving detection accuracy, lowering false-positive rates, and reducing the operational burden of manual investigations.
• Score: 1.9426782472131299
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Money laundering and financial fraud remain major threats to global financial stability, costing trillions annually and challenging regulatory oversight. This paper reviews how artificial intelligence (AI) applications can modernize Anti-Money Laundering (AML) workflows by improving detection accuracy, lowering false-positive rates, and reducing the operational burden of manual investigations, thereby supporting more sustainable development. It further highlights future research directions including federated learning for privacy-preserving collaboration, fairness-aware and interpretable AI, reinforcement learning for adaptive defenses, and human-in-the-loop visualization systems to ensure that next-generation AML architectures remain transparent, accountable, and robust. In the final part, the paper proposes an AI-driven KYC application that integrates graph-based retrieval-augmented generation (RAG Graph) with generative models to enhance efficiency, transparency, and decision support in KYC processes related to money-laundering detection. Experimental results show that the RAG-Graph architecture delivers high faithfulness and strong answer relevancy across diverse evaluation settings, thereby enhancing the efficiency and transparency of KYC CDD/EDD workflows and contributing to more sustainable, resource-optimized compliance practices.

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