Financial crimes like money laundering and terrorism financing can have significant impacts on society, including loss of trust in the integrity of the financial system, misuse and mismanagement of public funds, increase in societal problems like drug trafficking and illicit gambling, and loss of innocent lives due to terrorism activities. Effective detection of complex financial crimes remains a formidable challenge for regulators and financial institutions because the critical data needed to establish patterns and criminality are often dispersed across multiple organisations and cannot be linked due to privacy constraints around large-scale data matching. Recent advances in privacy and confidential computing technologies, which enable private and secure data analysis across organisations, offer a promising opportunity for regulators and the financial industry to come together to enhance their collaborative risk detection while maintaining privacy standards. This paper, through a survey of the financial intelligence ecosystem, seeks to identify opportunities for the utilisation of privacy technologies to improve the state-of-the-art in financial-crime detection.

翻译：洗钱和恐怖主义融资等金融犯罪对社会具有重大影响，包括损害金融体系完整性的公信力、导致公共资金的滥用与管理不善、加剧毒品贩运和非法赌博等社会问题，以及因恐怖活动造成无辜生命的丧失。对于监管机构和金融机构而言，有效检测复杂的金融犯罪仍然是一项艰巨的挑战，因为建立犯罪模式和认定罪行所需的关键数据通常分散在多个组织中，且由于大规模数据匹配的隐私限制而无法进行关联。近年来，隐私和机密计算技术的最新进展使得跨组织的私有和安全数据分析成为可能，这为监管机构和金融行业提供了一个重要的合作机遇，使其能够在维护隐私标准的同时，加强协同风险检测。本文通过对金融情报生态系统的调研，旨在探索利用隐私技术提升金融犯罪检测前沿水平的潜在路径。