这是一场与非法人工智能的长期攻防拉锯战。当不法分子的攻 击升级至新的层级，金融机构的反击必须同步攀升至更高维 度，二者在攻防博弈中形成持续循环。 作者： 老盈盈 封图：图虫创意 王阿姨收到了一条来自银行客服的短信，提示她的账户存在安全风险，需点击链接完成实名认证更新。想着自己下午刚转账了一笔养老钱，她没多想就 点击了短信链接，按照页面提示填写姓名、身份证号，输入手机收到的验证码，最后还提交了支付密码。 她并不知道，这一步操作，让不法分子拿到了她账户的"全套钥匙"。就在王阿姨关掉网页后，不法分子已经用这些信息登录了她的手机银行，他们还在 手机上找到王阿姨的照片，用AI（人工智能）技术生成了和她本人一模一样的动态视频。 同时，不法分子还通过恶意代码劫持了她的手机摄像头。手机银行的活体检测环节启动时，本应调用真实摄像头的验证界面，却被不法分子替换成了上 述预录的AI伪造动态视频。银行系统没能识别出破绽，顺利通过了身份验证。接下来，王阿姨的账户资金被分批转走，甚至还用她的信息申请了一笔 小额贷款。 在11月3日至4日的香港金融科技周上，蚂蚁数字科技（下称"蚂蚁数科"）的产品技术人士对经济观察报记者讲述了上述案例，通过 ...

Core Insights - The rapid development of AI technology has led to the emergence of deepfake fraud techniques, posing significant risks to individuals and financial institutions [2][3] - Ant Group's digital technology team has identified new fraudulent methods involving phishing attacks that exploit personal information to bypass security measures [2][5] - Financial institutions are engaged in a continuous "AI vs. AI" battle, developing advanced algorithms to counteract increasingly sophisticated fraud techniques [3][6] Fraud Techniques - Fraudsters use phishing traps to impersonate banks, tricking victims into providing sensitive information [2][5] - New injection attacks allow criminals to hijack mobile devices and use deepfake images or videos to bypass identity verification [2][5] - Traditional fraud methods have evolved from simple presentations to more complex AI-generated manipulations [5][7] Defense Mechanisms - Financial technology companies are implementing defensive strategies by simulating fraud techniques to better understand and counteract them [6][7] - Algorithms are being developed to detect AI-generated images and assess their authenticity based on technical traces left by AI tools [7][8] - Multi-dimensional defense strategies are necessary, combining image recognition with system-level checks to prevent injection attacks [7][8] Application Scenarios - AI anti-fraud technologies are being integrated into various sectors requiring electronic identity verification, including banking, insurance, and e-commerce [8][9] - The Hong Kong Monetary Authority is facilitating AI fraud testing programs to help banks combat deepfake scams [8][9] - AI models are being trained using historical transaction data to enhance real-time fraud detection capabilities [12][13] Industry Collaboration - Financial institutions are collaborating with regulatory bodies to create a cross-bank fraud data exchange platform to share information on fraudulent activities [10][12] - The integration of AI in identity verification processes is being expanded to government services, enhancing security for public applications [11][12] - Companies like Dyna.AI are focusing on refining their models through compliance-driven data analysis to improve fraud detection accuracy [13]