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The trend toward digitization has been building momentum over the past few years. Since the onset of the Covid-19 pandemic, it’s even faster, especially in the payment industry. Cash apps, digital wallets and card-not-present (CNP) transactions are replacing cash, checks and physical credit cards. Meanwhile, fraudulent activity across digital channels is ramping up. Merchants are proactively fighting digital payment fraud in 2021 and risk is high, as many consumers choose to shop online and use contactless payment methods to avoid unnecessary exposure to the virus.

Unfortunately, fraud and risk teams lack experience and historical data around emerging digital payment options — two of the key factors that traditional rules-based fraud solutions use to fight fraud. To make matters worse, Covid-19 restrictions have financial institutions understaffed and unable to handle the high volume of cases in need of review. That’s the perfect storm for payment fraud.

Reactive approaches to detecting payment fraud no longer work. Financial institutions must adopt a proactive, holistic approach that leverages customer account life cycle data and advanced algorithms to identify both known and unknown fraud patterns in real time.

Digital PaymentWith stay-at-home orders reinstated in various regions across the U.S., Card-Not-Present transactions are becoming the norm. And while credit card fraud is skyrocketing, Card-Not-Present fraud is 81% more prevalent than point-of-sale fraud. Why? Because when a person pays with a physical card in the store, employees can check photo IDs or verify signatures. But in Card-Not-Present transactions, such manual safeguards are missing.

Peer-to-peer (P2P) payments are also much more common today. In fact, 1 billion people use services like Paypal, Venmo, Apple Pay and other cash apps globally. These digital payment apps are easy targets for fraudsters who know that financial institutions often lack the data and insights to detect new fraud patterns. Scams occur frequently, a fraudster might sell goods over an online marketplace requiring payment via Paypal, for example, and never deliver the goods. Fraudsters may also use stolen credit card information to create P2P accounts and purchase goods and services for themselves.

The problem is legacy fraud solutions often rely on rules and historical data to understand fraud and can’t keep pace with the rate of innovation in the payment space. They also tend to focus on individual use cases rather than look at data from multiple interactions holistically. Machine learning algorithms based on limited, historical data miss new fraud patterns, and threats go undetected until it’s too late.

While digital payment options and the fraud associated with them will likely continue to plague financial institutions and consumers, here are four best practices to follow:

1. Leverage digital intelligence.
IP address and device intelligence signals help create a digital fingerprint that provides clues about a user’s network origins and can be used to determine whether an attempted transaction is legitimate or coming from a device emulator or a hijacked device. Device intelligence can also help determine the level of risk when authenticating the login or a transaction.

2. Protect the entire account life cycle.
Choose a fraud solution that provides proactive, continuous protection — not a point solution that only offers one-off risk assessments at a single point of entry. A solution that collects, centralizes and analyzes comprehensive data signals across all customer touch points and activities can deliver insights that enable rapid decision making and effective fraud prevention.

3. Automate feature engineering.
When features are generated automatically based on domain expertise and centralized intelligence, fraud detection is efficient and effective. Advanced feature engineering enables teams to generate derived features instead of relying on raw data attributes to provide critical insights. When paired with sophisticated machine learning algorithms, it can deliver exceptional model accuracy.

4. Implement real-time detection.
Digital payment methods occur rapidly and settle fast without human involvement. Real-time detection and prevention are critical, but it must happen without impacting the customer experience. Look for advanced solutions that can combine multiple technologies and correlate and analyze suspicious patterns — both known and unknown — in real time, providing high detection accuracy.

Not long ago, digital payment platforms didn’t exist. We can only hypothesize what kind of fraud will emerge as the technology evolves. Proactive fraud solutions that provide a holistic view of the account life cycle can learn and adapt at the pace of modern innovations and rapidly shifting fraud patterns to protect consumers and financial institutions, regardless of what payment methods and processes are used.

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