As fraud continues to rise around the world, what are the key anti-fraud trends merchants should focus on in 2023? Is machine learning gaining momentum? If so, explain its importance Can you do it?
A worrying trend is the commercialization of fraud. This means that anyone, even those who previously did not have the skills or resources to do so, will now be able to commit fraud. The dark and deep webs are filled with easily accessible fraud forums and marketplaces, tutorials that allow bad actors to commit fraud or engage third parties in “fraud-as-a-service” and tools are sold. And many of these forums, especially on apps like his Telegram, openly market their services to the general public.
New rules have been enacted accordingly, such as Visa’s Compelling Evidence 3.0 (CE 3.0). Visa CE 3.0 updates the process for online merchants to contest chargeback fraud with an expanded list of evidence such as her IP address and device ID, shipping address and user account. As a baseline, online merchants need an online payment fraud prevention solution that can continuously monitor and collect these important analytics.
As fraud becomes more prevalent and easier to execute, businesses that want to stay secure and protect their bottom line must invest in technology that relies on machine learning (ML).
Organized fraudsters are already leveraging automated tools to accelerate their attacks, so traditional services simply can’t keep up, especially if they rely on manual reviews. ML, combined with the right data, is the foundation for building anti-fraud programs that put user experience first.
A final consideration is that economic uncertainty is the driving force behind rising fraud rates. Unfortunately, this economic uncertainty is also putting pressure on corporate budgets and creating talent shortages. Overall, organizations are being asked to do more with reduced resources. Machine learning is therefore non-negotiable for businesses that want to accurately and efficiently combat fraud while simultaneously achieving growth through revenue protection and customer retention.
The global anti-fraud solution provider continues to innovate with new approaches to better mitigate digital risk and help businesses grow securely. What do you think are the main differences between the different types of anti-fraud platforms on the market?
There are currently three main types of anti-fraud strategies that businesses can choose from: built models, insurance models, and comprehensive digital trust and safety platforms.
When choosing from these options, businesses should keep the following important considerations or characteristics in mind.
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Does this solution match your business incentives?
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What is the judgment accuracy?
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How much visibility and control does the risk team have?
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What capital and people efficiencies will it bring?
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What is the time to value of the solution?
The first option, an internal fraud decision-making strategy, requires significant investment and commitment to succeed. Companies opting for this anti-fraud method will need to commit significant amounts of capital and supporting personnel, and will likely take longer to see the return on investment.
Anti-fraud providers that fit the insurance model are initially appealing as they offer chargeback guarantees and virtual outsourcing of the entire function. However, this guarantee also means that you are more likely to reject a disproportionate number of overall transactions, including many legitimate transactions, which can actually negatively impact user experience and customer retention. there is.
Digital trust and safety platforms, on the other hand, leverage the wisdom of machine learning to provide nuanced and accurate fraud risk scoring, capital and people efficiency, and real-time responsiveness to optimize across all of the above attributes. provides a good balance. is based on a global data network and management structure that emphasizes transparency and control.
How important is the focus on fraud transparency and control when choosing an anti-fraud solution provider?
Transparency and control are two key factors to consider when evaluating anti-fraud solutions (other factors are automation, investigation, and scalability). These two factors are important because online sellers need to make informed decisions and apply them to their business, and they need to do it quickly.
Transparency is the ability to visualize fraud risk in context to analyze patterns of both red flags and positive signals. For example, online merchants may be able to determine whether certain customer segments are at risk of fraud.
Control is the ability to apply appropriate decisions to transactions and change risk thresholds based on your unique business needs. For example, an online seller may decide that the risk of his shopping cart being abandoned is not worth the potential risk of fraud, so he does not want to challenge low-value sales. Solutions like Sift allow merchants to apply dynamic friction to assess risk her score for each trade on a case-by-case basis.
Finally, we need both humans and machines to fight the network. That means solution providers, merchants and end-users all need to work together to stay one step ahead of scammers. How will Sift’s new customer community portal help reduce the gap in this area?
Sift’s new customer community, Sifters, is one of many ways to level the playing field for fighting fraud. Underground cybercriminals in the dark and deep web are well-networked, nimble, and readily share the latest fraudulent techniques and security flaws with their communities. Sift builds a community for “good people”.
Called Sifters, this community allows you to connect and collaborate with fellow customers and trust and safety architects to share best practices and information on emerging fraud threats. Sifters is the human layer of our digital network, a partnership of digital risk professionals on a mission to fight fraud and grow securely.
About Armen Najarian
Armen Najarian is Sift’s Chief Marketing Officer. He has extensive strategic experience as his CMO at fast-growing fraud, identity and cybersecurity companies such as Outseer, Agari and ThreatMetrix.
About shift
Sift is the leader in digital trust and safety, helping digital disruptors of Fortune 500 companies capture new revenue without risk. Sift dynamically prevents fraud and fraud through industry-leading technology and expertise, an unmatched global data network of 70 billion monthly events, and a commitment to long-term customer partnerships. Global brands like DoorDash, Twitter and Wayfair rely on Sift to gain a competitive edge in their markets.
