?? This month marks a year since we launched Sift’s Fraud Industry Benchmarking Resource, FIBR, and we’re excited to share the latest updates, including brand new data and metrics, as well as a fresh new look. What’s FIBR? FIBR is a free online tool powered by Sift that allows anyone to access key fraud metrics across industries, geographies, and time. What’s new? - New fraudulent payment data: You can now see which payment methods are preferred by fraudsters, as well as the fraud rates for common payment methods across Sift’s Global Network. - Redesigned user experience: Navigate FIBR more intuitively, with clearer metric definitions and helpful tooltips to add context. What’s interesting? - Credit and debit cards account for the vast majority of fraudulent transactions, but for high-stakes industries like iGaming & Online Gambling, electronic fund transfers and digital wallets are on the rise. - This could indicate that fraudsters may be trying to leverage electronic fund transfers to launder money, and using these payments to access instant cash. ?? Read more about the new updates here: https://buff.ly/4fIPxmS ?? Access FIBR yourself to explore the new metrics: https://buff.ly/3K7l9ES #FraudPrevention #FraudTrends #FraudRates #AIPowered #GrowFearlessly
Sift
计算机和网络安全
San Francisco,California 21,279 位关注者
Sift is the AI-powered fraud platform securing digital trust for leading global businesses.
关于我们
Sift is the AI-powered fraud platform securing digital trust for leading global businesses. Our deep investments in machine learning and user identity, a data network scoring 1 trillion events per year, and a commitment to long-term customer success empower more than 700 customers to grow fearlessly. Brands including DoorDash, Yelp, and Poshmark rely on Sift to unlock growth and deliver seamless consumer experiences. Visit us at sift.com.
- 网站
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https://sift.com
Sift的外部链接
- 所属行业
- 计算机和网络安全
- 规模
- 201-500 人
- 总部
- San Francisco,California
- 类型
- 私人持股
- 创立
- 2011
- 领域
- Machine Learning、Software as a Service (SaaS)、Fraud Detection、Predictive Analytics、Big Data、Data Visualization、Digital Trust、Digital Trust & Safety、Risk management、Payment Fraud、Fraud Detection Software、Revenue Growth、Artificial Intelligence、Fraud Expertise和Fraud Prevention & Protection
产品
The Sift Platform
防欺诈保护软件
AI-fueled fraud tools are the key to enabling next-level consumer experiences. Sift’s AI-powered platform transforms fraud prevention into a competitive advantage for you, your team, and your consumers.
地点
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主要
525 Market St
US,California,San Francisco,94105
Sift员工
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Richard Helliar
VP EMEA - Sift | Hypergrowth Sales and Marketing Leader committed to accelerating business success
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Liz Kao
Principal B2B SaaS PM | Customer Lifecycle Process Optimizer & Customer-facing Reporting Champion | Dummies author
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Albert Wenger
Managing Partner at Union Square Ventures
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Ryan Heavner
动态
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“AI is going to evolve to better recognize and adapt to new fraud patterns in real time. This is something that rules and more static solutions cannot achieve.” - Kevin Lee, SVP of Customer Experience Trust and Safety at Sift At the recent MRC | Merchant Risk Council Virtual Summit, Sift joined industry leaders, including Jacob Sanchez, Director of Fraud Operations at FanDuel and Oxana Korzun, Fraud Intelligence at Upwork, to explore how businesses can fight AI-driven fraud. From leveraging AI to build trust to tackling evolving fraud patterns, here are the must-know takeaways from the summit: https://buff.ly/3OgvjoO #FraudPrevention #DigitalTrust #AIFraud #AIPowered
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?? Get to know the new team members who joined Sift this fall! Meg Stephens, MA, Director, Deal Desk and Renewal Operations Kristin Hart, Field Enablement Experience Specialist Brandon Phillips, Sales Development Representative Stacy Bricker, Accounting Manager Ryan Hikins, Sales Development Representative Kai Edson, Senior Deal Desk Analyst #NewHires #TeamGrowth
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?? Travel fraud is taking off — What can businesses do about it? The travel industry is a prime target for fraudsters, with online travel and lodging facing the highest fraud attack rates across all sectors, according to Sift's Fraud Industry Benchmarking Resource (FIBR). That’s why Alaska Airlines, a leader in customer experience and WalletHub’s #1 airline of 2024, partnered with Sift. With AI-powered technology, they're able to tackle fraud effectively while maintaining smooth (and safe) customer experiences. Kevin Lee, SVP of Customer Experience, Trust and Safety at Sift shares how we work with Alaksa Airlines and others in the industry to turn fraud prevention into an opportunity for growth: https://buff.ly/3zYlkRE #FraudPrevention #TravelIndustry #CustomerExperience
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Thank you for the kind words Becca Roach, we’re lucky to work with such a great team at Hertz!
Working with Sift has enhanced how we protect our customers and our assets at Hertz. Sift embraces our unique business challenges and works with us to adapt to the continually evolving fraud threats we face. Not only have we improved efficiency and reduced theft and fraud by partnering with Sift, but we are also able to offer a better, frictionless experience to our trusted customers. #hertz #letsgo #sift #fraudprevention
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?? Be sure to check out our first newsletter for the latest insights and findings in digital trust. #FraudPrevention #Newsletter
New ATO Data, Upgraded Benchmarking Resource, and Exclusive Insights for Finance Leaders
Sift,发布于领英
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Online fraud isn’t just a digital problem—it has real-world consequences. Businesses like Hertz, the leader in car rentals, that prioritize customer experience, have to consider the broader impact of the fraud they face. And because Hertz is unique among hybrid online/offline businesses—with each asset in their inventory of rental vehicles worth tens of thousands of dollars—defending against fraud is mission-critical at both the payment and account level. That's why Hertz has partnered with Sift to tackle fraud head-on. Read our latest article by Sift CMO Armen Najarian to learn how Hertz is driving digital trust and preventing fraud while putting customers first: https://buff.ly/3AP7kde #FraudPrevention #DigitalTrust #CustomerExperience #GrowFearlessly
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?? Join Us for Risk Revenue Day London! ?? ??? When: December 4, 2024 ?? Where: Holborn, London ? Time: 16:30 GMT We’re back with another Risk Revenue Forum, for a day of insightful discussions, networking, and panel sessions focused on the intersection of fraud prevention, security, and identity. Why Attend? ?? Learn how fraud intersects with security and identity. ?? Discover dark web strategies used by bad actors. ?? Engage with other fraud prevention experts. If interested, comment below or send us a message for registration information. Spots are limited. #FraudPrevention #Networking #CyberSecurity #RiskRevenueDay
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?? $2 billion – that’s how much subscription fraud costs businesses each year. Subscription fraud is a “thriving criminal ecosystem” that focuses on accounts rather than payment manipulation or one-time purchase scams. These cybercriminals take advantage of stolen credentials, synthetic identities, or trial offers to gain unauthorized access to services. In our latest article, our Trust and Safety team takes a closer look at subscription fraud and its impact on businesses -- and how to combat it: https://buff.ly/4fDIqfR #FraudPrevention #DigitalGoods #InternetSoftware #SaaS #SubscriptionFraud
How to Prevent Subscription Fraud - Sift
sift.com
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?? This week, we have a *special* edition of #FIBRFriday, our weekly series where we share insights from our Fraud Industry Benchmarking Resource, FIBR. In case you missed yesterday's announcement, we're celebrating FIBR's 1-year anniversary this month with with brand new metrics (payment method data) and a refreshed look. Specifically, you can now see the frequency of fraudulent payment methods used across industries, as well as the fraud rates for common payment methods -- all with improved user experience and more intuitive navigation. ?? Check out the new and improved FIBR to explore this data yourself: https://buff.ly/3K7l9ES #FraudPrevention #FraudTrends #FraudRates #Payments #PaymentFraud