According to this year’s Gartner Market Guide for Online Fraud Detection, “By 2025, the primary role of 60% of fraud leaders will shift focus from simply adhering to governance, risk, and compliance toward creating an environment of trust and safety where customers can transact, interact and communicate, up from less than 5% today.*”
At Sift, we believe this statement is an indication that to scale and succeed, businesses can no longer think of fraud reduction and revenue growth as two separate goals but one goal focused on providing the best possible customer experience.
Unfortunately, many legacy companies are reluctant to embrace the need to move beyond simply managing risk. As a byproduct of that mindset, businesses that drag their feet and continue to focus solely on reacting to bad actors will see their good customers walk away.
Here are five definitive signs from Gartner that signal the need for forward-thinking businesses to adopt a more holistic, flexible approach to not only combating fraud but driving growth.
1. As fraudsters change their tactics, fraud fighters need to take a holistic approach
The fraud landscape is perpetually evolving, with new channels and methods of attack developing at a frightening pace. Fraud affects much more than payments and online e-commerce but account takeover, content integrity, and more. While the tactics of bad actors are becoming increasingly sophisticated, the advent of online fraud detection solutions (OFDs) that combine and orchestrate new analytics and data sets (e.g. machine learning, behavioral analytics, and biometrics), and that take into account all types of online fraud and abuse, allows fraud leaders to take a holistic approach to reducing risk instead of relying on a shortlist of fraud indicators. As Gartner points out, “New challenges will arise as new threats occur, and it is therefore imperative that the solution be extensible and agile with respect to accommodating new channels.” Utilizing analytics and data sets that address these new challenges specifically will become more important as a “one size fits all” methodology to reducing risk becomes less effective in an increasingly complex fraud landscape.
2. Machine learning continues to drive innovation in the OFD space
Rule-based online fraud detection, while effective at preventing some loss, is static and inflexible. In fact, rules work backwards, can only be introduced after an attack happens, and can take hours to implement.
Furthermore, rules can inadvertently block trustworthy transactions from going through. This is understandable because rules that were created to address one attack often have unforeseen impacts on future transactions. This is only compounded the longer you keep existing rules in place. As you add more rules (to block new threats), you can end up with rules that clash with the logic of others, resulting in unintended outcomes and false positives. Some customers will interpret those false positives as insults, eroding your brand reputation and chipping away at your bottom line. “To this end, there is an ongoing transition underway from primarily rule-based systems to those that primarily rely on machine learning,” Gartner notes.
The graphic below illustrates where rule-based risk assessments fall in the hierarchy of fraud protection capabilities.
This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request.
A solution like Sift uses real-time machine learning, allowing businesses to reduce fraud, reduce manual review, and increase conversion.
3. The amount of data available to make fraud decisions is increasing – it should be funneled into a single solution
As more and more data points and attributes become available for fraud managers to base their decisions on, that significant volume of information should be easily accessible in one location. A single, comprehensive solution where data and signals are aggregated speeds up the analysis decision-making process. As Gartner points out, “This will avoid the creation of both data and decision silos, the formation of which creates opportunities for fraudsters.”
4. New channels provide new vectors for fraudsters
Fraudsters are utilizing all digital channels, including the internet, mobile, and phones. To combat this, we believe the report recommends security and risk management leaders develop an omnichannel fraud detection strategy. “This will minimize the risk of a fraudster simply migrating to one channel after being blocked on another,” according to the research and advisory company.
This is especially true for the mobile channel. Mobile devices account for 19% of all US retail e-commerce sales, and that number is expected to grow even more this year. This brings an increased need for companies to add a mobile fraud strategy to their existing online fraud detection team to keep legitimate customers happy while stopping unsavory activity on their sites and apps. To do so, businesses looking to monitor multiple fraud vectors (including mobile) should invest in a unified solution that can analyze risk across the entire user journey. The Sift Digital Trust & Safety Suite can adapt to a company’s unique fraud patterns across multiple channels and deliver accurate results with our global network of data, so a business can focus on growing without worrying about bad actors.
5. Examine the entire customer journey – not just the point of payment
Determining whether a customer is a fraud risk isn’t black and white. Fraud managers who look at a small set of attributes – or even a single action like the point of payment – run the risk of false positives for legitimate customers or letting bad actors through.
We believe the report recommends decision making regarding risk level be pushed upstream. “Security and risk management leaders must create a fraud detection regimen that begins to assess risk from when the customer arrives on their digital premises.” Sift makes this possible by scoring a customer in real time, from the moment they arrive on site to every subsequent action they take, including the point of payment. The Sift engine can detect new fraud patterns and signals as they happen, and take appropriate action based on those indicators at the time of detection, not just point of payment. As Gartner points out, “This includes assessing behavior, evaluating the likelihood of bots or scripts being used, monitoring account login or creation, and defining the risk of the action being carried out.”
To learn more about the new trends affecting Online Fraud Detection, download the Gartner Market Guide for Online Fraud Detection, and then reach out to Sift to learn how Digital Trust & Safety can help you stay ahead of fraudsters and unlock more revenue for your business.
*Gartner, Market Guide for Online Fraud Detection, Jonathan Care, Akif Khan, 30 April 2019
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