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利用人工智能领先于支付欺诈

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当消费者点击支付按钮、进行在线购物或转账时,他们都期望交易过程是安全的。随着越来越多的支付行为转向线上,维护消费者的信任对企业来说变得愈发重要。根据 Visa 委托进行的一项调查,近七成的新加坡居民信任数字支付方式;不过也有 42% 的受访者遭遇过诈骗,其中 8% 的人因此蒙受了经济损失。

When consumers tap a card, shop online or transfer money, they expect the transaction to be secure. As more payments move online, maintaining that trust is increasingly important for businesses. A Visa-commissioned study found that close to seven in 10 Singapore residents trusted digital payments, while 42 per cent had encountered a scam and 8 per cent had lost money to one.

诈骗手段也在不断变化:诈骗者不再仅仅拦截交易,而是利用人工智能(AI)、自动化技术以及社会工程学手段,诱使受害者自行授权支付。这给企业带来了困境——那些原本用于优化购物推荐和加快支付处理速度的 AI 技术,也可能被犯罪分子利用。对于银行、商家、金融科技公司以及其他支付服务提供商来说,他们的挑战在于如何在不干扰合法交易的情况下迅速识别可疑行为。

Fraud tactics are changing, too. Rather than only intercepting transactions, scammers are increasingly persuading victims to authorise payments themselves, using artificial intelligence (AI), automation and social engineering. This puts businesses in a bind. The same AI that helps them personalise shopping recommendations and speed up payment processing can also be used by fraudsters. For banks, merchants, fintech companies and other payment providers, the challenge is to spot suspicious activity quickly without slowing legitimate transactions.

Visa 亚太地区的金融科技业务发展负责人 Varun Mahindru 先生与 Featurespace 公司亚太地区总经理 Phillip Finnegan 先生共同讨论了如何利用 AI 技术来检测欺诈行为。

Mr Varun Mahindru (left), Visa Asia Pacific’s fintech business development lead, and Mr Phillip Finnegan, Featurespace’s general manager for Asia Pacific, discuss AI fraud detection. (Video: Visa) WHY TRADITIONAL FRAUD CHECKS ARE FALLING BEHIND Fraud prevention has long relied on fixed rules that flag or block risky transactions. These checks remain important but can struggle to keep pace with new fraud tactics and digital channels. Increasingly, criminals are not just intercepting payments but impersonating the people making them.

为什么传统的欺诈检测方法已经过时?长期以来,欺诈预防主要依赖于固定的规则来识别或阻止高风险交易。虽然这些规则仍然有效,但它们难以跟上新型诈骗手段和数字化支付渠道的发展速度。如今,犯罪分子不仅会拦截交易,还会冒充交易发起者进行欺诈。

Mr Varun Mahindru (left), Visa Asia Pacific’s fintech business development lead, and Mr Phillip Finnegan, Featurespace’s general manager for Asia Pacific, discuss AI fraud detection. (Video: Visa) WHY TRADITIONAL FRAUD CHECKS ARE FALLING BEHIND Fraud prevention has long relied on fixed rules that flag or block risky transactions. These checks remain important but can struggle to keep pace with new fraud tactics and digital channels. Increasingly, criminals are not just intercepting payments but impersonating the people making them.

Visa 亚太地区东南亚区域国家经理、同时也是全球客户高级副总裁的 Adeline Kim 女士指出:“欺诈行为和诈骗手段正在从单纯的交易层面扩展到个人身份信息层面。诈骗者能够精确地选择攻击的时间和方式,从而让他们的攻击显得更加“真实”。”未被发现的欺诈行为不仅会为企业带来经济损失、扰乱正常运营,还会损害企业的声誉。然而,过于严格的欺诈检测机制反而可能误判合法交易,从而惹恼客户,甚至导致客户转向其他支付服务提供商。金女士表示,诈骗者也在利用技术更迅速地攻击薄弱环节。

“Fraudulent activities and scams are moving from transaction to identity,” said Ms Adeline Kim, Visa’s group country manager for regional Southeast Asia and senior vice president for global clients in Asia Pacific. “Scammers can now tailor exactly how and when they strike to make it convincing.” Undetected fraud can cost businesses money, disrupt operations and damage reputations. But overly strict checks can block legitimate transactions – frustrating customers and potentially sending them elsewhere. Ms Kim said fraudsters were also using technology to target weak points more quickly.

“对于银行、商户和金融科技公司而言,担忧的不再仅仅是欺诈的数量,而是其攻击的速度和规模,”她补充道。“应对措施必须同样迅速、智能且协调一致。”抵御更快速的威胁在过去五年中,Visa 在技术领域投入了超过 130 亿美元(约 168 亿新元),其中包括欺诈预防技术。Visa 利用人工智能打击欺诈已有三十多年历史,每年基于每笔交易约 500 个数据点分析超过 2500 亿笔交易。

“For banks, merchants and fintechs, the concern is no longer just how much fraud there is, but the speed and scale at which it can strike,” she added. “The response has to be just as fast, intelligent and coordinated.” DEFENDING AGAINST FASTER THREATS Visa has invested more than US$13 billion (S$16.8 billion) in technology over the past five years, including fraud prevention. It has used AI to fight fraud for more than three decades, analysing more than 250 billion transactions each year based on about 500 data points per transaction.

Visa Protect* 将这些能力整合为一个人工智能驱动的欺诈预防解决方案组合,服务于发卡机构、商户、收单机构和金融科技公司。其工具可实时评估交易,并将其与 Visa 全球网络中的模式进行比对,帮助企业决定如何应对不同的预警信号。

Visa Protect* brings these capabilities together in a portfolio of AI-driven fraud prevention solutions for issuers, merchants, acquirers and fintech companies. Its tools assess transactions in real time and compare them with patterns across Visa’s global network, helping businesses decide how to respond to different warning signs.

该组合包括 Visa 于 2024 年收购的 Featurespace 公司的技术。该技术能够学习每位客户的典型行为,并标记出偏离这些模式的活动。这些模型会随着时间的推移不断学习,从而有助于识别传统规则可能遗漏的欺诈手段。

The portfolio includes technology from Featurespace, which Visa acquired in 2024. The technology learns each customer’s typical behaviour and flags activity outside those patterns. The models continue learning over time, helping identify fraud techniques that traditional rules may miss.

基于人工智能的欺诈工具可以将交易与更广泛的行为和网络模式进行比对,从而帮助发现可疑活动。

AI-based fraud tools can compare transactions with broader behavioural and network patterns to help spot suspicious activity.

“在当前环境下,数百条规则既昂贵又无效,”Featurespace 亚太区总经理菲利普·芬尼根(Phillip Finnegan)先生表示。他补充说,企业应转向基于机器学习和人工智能的欺诈防范能力。

“Hundreds of rules are costly and ineffective in the current environment,” said Mr Phillip Finnegan, Featurespace’s general manager for Asia Pacific. He added that businesses should move towards machine learning and AI-based fraud capabilities.

Visa 最近更新了其于 2019 年首次推出的新加坡安全路线图,重点包括加强身份验证、令牌化,以及在打击涉及人工智能的欺诈和诈骗方面加强行业协作。更安全且无摩擦的支付体验欺诈检测需要在捕捉可疑活动的同时,避免拦截正常支付。然而,当客户在旅行或进行重要消费时,合法交易仍可能被拒绝,而企业又需要更强的管控措施来应对日益复杂的诈骗手段。

Visa recently updated its Singapore Security Roadmap first launched in 2019, with priorities including stronger authentication, tokenisation and closer industry collaboration against fraud and scams involving AI. SAFER PAYMENTS WITHOUT ADDED FRICTION Fraud checks need to catch suspicious activity without blocking genuine payments. Yet legitimate transactions can still be declined when customers are travelling or making important purchases, even as businesses need stronger controls against increasingly sophisticated scams.

传统系统可能会将任何异常行为标记为可疑。基于人工智能的系统则能在更广泛的背景下评估交易,包括客户的消费模式以及在支付网络中的活动情况。这有助于区分真实购买与欺诈尝试,减少误拒,并使反欺诈团队能够专注于高风险案例。

Traditional systems may flag anything unusual as suspicious. AI-based systems can assess a transaction in a broader context, including a customer’s spending patterns and activity across the payments network. This can help distinguish genuine purchases from fraud attempts, reduce false declines and allow fraud teams to focus on higher-risk cases.

金女士表示:“我们的目标从来不是将客户排除在支付流程之外,而是在保护客户安全的同时,消除不必要的摩擦。”随着数字商务的扩张,维持这种平衡变得愈发重要。

“The goal is never to take customers out of the payment process. It is to remove unnecessary friction while keeping them protected,” said Ms Kim.

她补充道:“支付归根结底关乎买卖双方之间的信任,即使他们可能从未谋面。做好安全与信任,不仅在于阻止欺诈,更在于让客户有信心持续进行交易。”了解Visa Protect如何帮助支付生态系统中的企业实时管理欺诈风险。

As digital commerce expands, maintaining that balance becomes increasingly important.

  • Visa Protect包含用于实时交易风险评估的Visa高级授权(Visa Advanced Authorisation)、用于发卡行欺诈管控的Visa风险管理器(Visa Risk Manager)、用于数字商务中基于人工智能的欺诈检测的决策管理器(Decision Manager),以及用于标记可疑活动的行为分析工具Featurespace。

“Payments are ultimately about trust between buyers and sellers who may never meet,” she added. “Getting security and trust right is not only about stopping fraud. It is about giving customers the confidence to keep transacting.” Learn how Visa Protect helps businesses across the payments ecosystem manage fraud risk in real time. * Visa Protect includes Visa Advanced Authorisation for real-time transaction risk assessment, Visa Risk Manager for issuer fraud controls, Decision Manager for AI-based fraud detection in digital commerce and Featurespace for behavioural analytics that flags suspicious activity.