Key Takeaways from our First DEFEND Webinar of 2023

Early in the new year, many of us are filling out plans for the months ahead. How will we budget for necessary new tools? What do we need to invest in to grow? And, for any business or institution dealing with the financials of customers or other businesses, how can we stay ahead of fraudsters and the scams they’re scheming up this year?

The answer to all these questions comes down to having the right information at your disposal before you make those decisions. At our recent DEFEND webinar, the Needle in the Fraud Tech Stack, DataVisor’s VP of Product, Steve Knopf, was joined by Bill.com’s VP of Risk Strategy, Krithika Ramadoss, and Galileo’s Sr. Director of Global Payments Risk Management, Maxim Spivakovsky for a discussion packed with insightful guidance on rising fraud trends and how to build the tech stack your team needs to fight them.

Download the full webinar to hear every insight our expert panel offered.

Fraud in 2023: Rising trends and the tools to fight back

The biggest trends in fraud in 2023, according to our panel, actually tended not to be wholly new methods of fraud, but rather more sophisticated methods of existing schemes.

One major area that saw a huge increase during economic uncertainty was first-party or “friendly” fraud. This involved real accounts working together to commit fraud, like buyer-seller collusion and users being tricked into making legitimate real-time transactions at the direction of fraudsters pretending to be bank workers or government relief workers. These real-time payment gateways provide a major challenge not just for customers, but for businesses as well.

As Krithika says, “⅓ of all B2B payments are happening in real-time. Money is moving internationally in a matter of seconds. That poses completely new fraud challenges because bad actors know once they run a scam they can take payments in real-time.”

While fraudsters have been abusing real-time payment systems for new sophisticated fraud schemes, they’ve also relied on traditional tactics like synthetic IDs, while making them harder to detect. Scammers use bots to make an army of fraudulent accounts to hide behind, and stopping them can only be done by finding them when they sign up.

Learn about account protection solutions and the ways you can spot fake accounts early.

How can you do it? While the panel advises there’s no exact science or silver bullet. it can be done with a combination of tools. Real-time detection, supervised and unsupervised machine learning models, and decisioning platforms can leverage models and data attributes at the right point at the right time to catch scammers as soon as they make an account.

The panel says you should have as many tools in your toolbox as you can get and design a fraud prevention system that is ready for 5-10x the fraud you expect to see. Fraudsters will figure out models eventually and find ways to trick them, so it’s all about staying ahead and using tools that adapt to new fraud types before fraudsters adapt themselves.

Controlling costs for fraud prevention

When doing a cost-benefit analysis of your fraud-fighting tools, remember, there’s no silver bullet—you can’t just pick one tool and solve for fraud across the board.

You need to build a platform that is ready for the marathon fraud fight, our panel says. Getting buy-in from company leaders and convincing them to appreciate the ongoing investment in fraud detection will allow you to continue to stay ahead of fraudsters in the long term. “Make fraud risk assessment a competitive advantage,” Krithika says.

Jonathan Care makes another important point: “Fraud fighters are coming out of the backroom now because they are not only governing the customer friction, they’re governing the risk appetite of the entire organization. They’re controlling how entrepreneurial you can be while still protecting from fraud.”

Everyone’s risk appetite is different. Steve Knopf says if you want to save money on resources, try multiple strategies on the same fraud vector and see which works the best then move the majority of the budget there. “When managing the cost of fraud prevention, remember—fraud fighters aren’t the only ones financially constrained. The fraudsters are too. They want to make money as cheaply as possible off the good guys. If you focus on just implementing fraud strategies that raise the cost of doing scams against your business, then you’ll push fraudsters to stop attacking you and go somewhere else,” Steve says.

As a DEFENDER, make it uneconomical for fraudsters to attack you and you’ll get the most from your tech.

Picking the right fraud tech stack for YOU

Perhaps the toughest question our panelists faced is how to build the ideal custom fraud stack for an organization’s specific needs. Of course, as you might already expect if you’ve been around fraud fighting, the answer comes down to collecting and utilizing the right data.

“Have the right dataset, include third-party data, have the right systems to analyze those data points, and find where you can catch fraud and slow it down,” Steve says. “Make sure you have features in your models and stack that can massage and build that data into other elements and features—say behavioral, geolocation, etc—and you’ll be able to track down more fraud.”

One solution that each panelist mentioned was machine learning models. “If you’re looking at the transactional piece of building a fraud stack, I would say start investing in the machine learning models first,” said Max. “The moment I have proper and robust monitoring controls, investigating what happened becomes much easier.”

Learn more about DataVisor’s machine learning solution and how leading fintech, banking, and finanical institutions implement it to fight fraud.

What you can do now to better find and fight fraud

The panelists’ insights on building the best, most affordable, and most effective fraud tech stack—or finding that needle—are a great guide on how you can identify gaps in your current platform and patch them.

If you’re serious about finding fraudsters before they act and staying one step ahead of their methods, then as our panelists recommend, you’ll want to explore adding machine learning to your arsenal. DataVisor’s cloud-based machine learning fraud prevention tool is the fastest on the market, allowing you to sniff out and eliminate fraudsters in less than 20 milliseconds. It’s built to detect the most prevalent and rising types of fraud, from real-time payments to account takeovers and synthetic IDs.

If you want to know the true scope of machine learning and add this powerful fraud-fighting technology to your tech stack, reserve a time to chat with our team and get a plan to add DataVisor to your specific stack.