Combining Custom Risk Checks and Block Lists to Combat Gift Card Misuse
Payment fraud is a significant concern for businesses, resulting in substantial financial losses, increased chargeback fees, reputational damage, and legal challenges. To effectively detect and prevent fraud, companies are turning to innovative solutions that combine custom risk checks with block lists.
Traditional Approach: Legacy Technology
Traditionally, payment processing systems have relied on legacy technology that prioritizes security over customer experience, leading to false positives and legitimate transactions being blocked. This approach not only results in lost revenue but also leaves customers unhappy with the buying experience.
Combining Custom Risk Checks and Machine Learning
To combat this issue, businesses are adopting a more nuanced approach to fraud detection, leveraging machine learning, pattern recognition, and data analysis to identify behavioral abnormalities and determine whether customers are genuine or fraudsters. One effective strategy is to combine custom risk rules with machine learning models. This allows businesses to:
- Create risk profiles tailored to their unique needs
- Optimize underperforming risk profiles
- Monitor the impact of changes
Manual Review: A Key Tactic
Another key tactic is manual review, which involves reviewing high-risk transactions before they’re completed to prevent fraudulent activity. This approach ensures that legitimate customers can still complete their purchases while keeping fraudsters at bay.
Optimizing Risk Settings
To optimize risk settings, businesses should:
- Test and experiment with different configurations
- A/B test to determine what works best for their specific needs
- Define success
- Decide on key performance indicators (KPIs)
- Measure fraud
- Benchmark against industry standards
Industry-Specific Solutions
Industry-specific solutions are also available to combat payment fraud. For example:
- Hospitality: Tokenization can be used to safeguard guest information and ensure compliance with regulations.
- Digital businesses in mobility, gaming, or software sectors: Machine learning can be used to automate complex decisioning and focus on improving customer experiences.
- Retail: A unified fraud solution can help respond to fraud with customizable risk rules across all brands and channels.
Adyen’s RevenueProtect
Adyen’s RevenueProtect is a unique risk management product that assesses thousands of transaction characteristics to determine the likelihood of fraud and either block or direct it to additional risk checks. With a global, cross-industry data network, Adyen ensures that businesses continually optimize for conversion and squeeze more revenue out of every transaction.
Combining Custom Risk Checks and Block Lists
By combining custom risk checks with block lists, businesses can effectively detect and prevent gift card misuse, protecting their customers and revenue streams from the negative impact of payment fraud.