Fraud Prevention: Best Tips & Tools for Your Company
Curious about fraud prevention? We discuss common fraudulent activity and give a complete explanation of how fraud prevention keeps fraudsters from succeeding.
What Is Fraud Prevention?
Fraud prevention is the strategy of detecting attempted fraudulent activity as it happens. With real-time monitoring and machine learning techniques, companies can stop fraudulent transactions before they occur.
Benefits of Fraud Prevention
Fraud can manifest in many ways, from fraudulent payments to brand impersonation, and it can be overwhelming to identify these attacks—let alone stop them. A fraud protection system identifies, classifies, and prevents fraud in all of its forms.
Fraud protection does more than just prevent financial loss: It builds confidence throughout an organization. It also helps shareholders rest easy knowing their investment is safe; many fraud protection systems feature auditing to demonstrate compliance and proactiveness against fraud.
Beyond financial loss, fraud can erode customer trust. Impersonation attacks launched through phishing scams, rogue apps, or fraudulent social media pages can do serious reputational damage. Leveraging fraud protection can help keep customer trust intact by protecting customer’s data and transactions.
How Fraud Prevention Works
In the past, fraud protection was a cumbersome process that required investigators to comb over transactions one by one to identify fraud and then take measures to stop it from happening again. As a result, fraud teams are stuck perpetually fighting yesterday’s war, tackling known threats while those not yet recognized wreak havoc.
But today, machine learning is changing all that. By leveraging device, contextual and relationship data, it’s possible to create models of what fraudulent activity looks like rather than fingerprinting every threat. These models are then used in authentication processes that factor in thousands of data points to distinguish criminal activity from legitimate transactions.
Many fraud protection systems then generate a risk score associated with a given transaction so that organizations can strike the right balance between fraud prevention and user experience.
Fraud Prevention in Action
Phishing attacks mimic trusted brands to commit fraud and spread malware. Consumers lost at least $43 billion last year through robocalls, text, and email scams that led to the theft of login credentials or payment fraud, according to the 2021 Identity Fraud Study from Javelin Strategy and Research. And the FBI reports that businesses lost another $55 billion through phishing and business email compromise (BEC) scams.
Outseer FraudAction provides 24/7 fraud protection across all channels by working to take down phishing sites, fraudulent social media accounts, and rogue mobile apps used in these attacks—before they cause harm to your customers.
CNP Payment Fraud
Card Not Present (CNP) fraud occurs when stolen credit card information is used to make a purchase. Requiring the three-digit CW security code can help prevent this, but only if the security code wasn’t also stolen.
Outseer 3-D Secure secures transactions by using behavioral analysis combined with insights from a global network of identity and transaction data. These tools allow you to reduce chargebacks and provide an uninterrupted shopping experience to legitimate customers.
How do you distinguish a real user from an intruder? With so many stolen credentials online it can seem impossible to tell the difference. Fraud protection systems can tell the difference by analyzing the behavior of each account to discover abnormalities that signal fraud.
Outseer Fraud Manager uses data science and machine learning to defeat fraudulent account access across all channels. We take the complexity out of fraud protection through our complete ecosystem approach and out-of-the-box authentication and step-up options.
Fraud Prevention Challenges
The business of preventing fraud can be enormously complex, so it’s not surprising that we’re seeing a steady rise in the number of businesses choosing managed-service fraud prevention over on-premise solutions.
The first step in fraud protection is fraud detection. This involves baselining user transaction behavior, building and optimizing statistical models, and aggregating the resulting threat intelligence. These tasks require skilled data scientists and access to machine-learning platforms.
Once fraudulent activity is discovered, its risk needs to be classified. Misclassification of fraud can leave systems vulnerable and produce erroneous audits and reports. Risk classification requires a combination of industry knowledge and data science expertise to properly implement.
Lastly, fraud prevention solutions must work seamlessly without impacting the customer experience. Machine learning algorithms must be thoughtfully trained to identify new threats while engineers build and continuously refine the management front-end. Many organizations simply lack the expertise, funding, or access to intelligence networks to build this kind of anti-fraud platform on their own.
Outseer provides seamless fraud protection that defeats both fraud and user friction at the same time. Through machine learning, data science, and advanced risk scoring, Outseer prevents 95% of all fraudulent transactions, with intervention rates as low as 5%. That’s the best performance in the industry. By seeing what others can’t, we stop fraud long before a transaction ever occurs. To learn how you can protect your customers through the power of frictionless fraud prevention, request a free demo today.