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Sanction Scanner:2023-2024年金融犯罪合规报告:全球反洗钱(AML)与欺诈治理(英文版)(72页).pdf

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1、2023-2024F?nanc?al Cr?me&Compl?ance Report CONTENTSAbout Us01.02Execut?ve Summary03.0404.AML Regulat?on&Compl?ance 08EU AML Regulat?on Changes for 2023 09US AML Regulat?ons?n 2023 12As?an AML Regulat?on?n 2023 15Survey Results 1705.Technology and AML Tools 19Effect?veness of Ex?st?ng AML Tools 21How

2、 to Leverage Technology:AI and Automat?on?n AML 22Pos?t?ve Impacts of AML Tools 23Survey Results 2506.The Sh?ft?ng Landscape of F?nanc?al Fraud 27Trends and Vulnerab?l?t?es?n 2023 29Technologys Impact on Fraud 30Sector-Spec?f?c Vulnerab?l?t?es 32Future Strateg?es and Technolog?es?n Combat?ng F?nanc?

3、al Fraud 34Survey Results 36Cryptocurrenc?es07.39Connect?on Between Cryptocurrenc?esand Money Launder?ng 41Cryptocurrency R?sks 43AML&KYC Regulat?ons?n the Crypto Industry 45The Future of Cryptocurrency?n 2024 50Survey Results 5308.Reg?onal Trends on F?nCr?me,AML&Fraud 55As?a-Pas?f?c 56Europe and Un

4、?ted K?ngdom 58Amer?ca 62M?ddle East and North Afr?ca(MENA)64Survey Results 6602.03ForewordSanction Scanner is an Anti-Money Laundering and Risk solutions providerestablished in 2019.It screens customers and transactions in a comprehensivedata of 220+countries.It also provides a transaction monitori

5、ng solution,andwith this,every transaction can be monitored in real-time and be identifiedwhich one is suspicious.Besides,it offers an all-in-one compliance approachwith 360 risk assessment by analyzing these data instantly and presenting it asa report to its users.Sanction Scanner aims to minimize

6、financial risks in accordance with thechanging regulations of each country.It serves customers from variousindustries,such as banking,investment,finance,insurance,payment andfintech,crypto,money transfer,leasing,and factoring.ABOUT USForewordForewordIn an era marked by ever-evolving complexities in

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1. **全球AML合规挑战**:2023年全球金融犯罪案件激增,美国欺诈案件达40.9万例(同比增14%),身份盗窃报告570万例(同比增23%),加密货币被盗30亿美元。 2. **监管升级**:欧盟推出MiCA框架监管加密货币,美国FinCEN实施最终受益人信息报告规则;76%受访者支持AI/自动化应用于AML,但40%对现有工具仅“ somewhat satisfied”。 3. **技术赋能**:机器学习工具可提升28%检测准确率,减少67%人工工作;但虚假警报仍是痛点,需优化算法。 4. **行业风险差异**:电商领域欺诈威胁感知最高,金融业受洗钱风险冲击大;教育、医疗、政府机构成网络攻击重灾区(如教育机构每周遭2000次攻击)。 5. **区域动态**:新加坡强化跨部门协作,香港推广AML技术,中国启动三年反洗钱行动计划。
**合规新规?** **科技防诈?** **加密风险?**
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