Is Your Fraud Detection Strategy Plagued by These Challenges?
Improve accuracy, reduce false positives, and streamline compliance with a unified approach to fraud detection for issuers.
Siloed Data Limits Accuracy
Issuer risk teams juggle card, device, and merchant feeds that never fully align, making AI models brittle and prone to blind spots when fraudsters switch channels.
High False-Positive Rates
Overly cautious scores block good cardholders, driving call-center volume, churn, and interchange loss—hurting both customer experience and portfolio growth.
Manual Model Maintenance
Data-science staff must constantly rebuild features, retrain models, and redeploy code to keep pace with evolving fraud patterns, stretching budgets and timelines.
Mounting Compliance Pressure
Regulators demand explainable AI, audit trails, and rapid dispute resolution. Meeting these rules with legacy tools is costly and risks fines.
FraudNet Solutions: Revolutionize Fraud Detection and Compliance
FraudNet empowers issuers with seamless fraud detection, reducing costs and enhancing customer trust effortlessly.
Real-Time Transaction Scoring
Scores every transaction in real time, slashing manual reviews and false positives.
360° Data Fusion
Combines issuer, device, and network data into one profile for sharper risk insight.
Self-Optimizing Models
Automates rule tuning with ML, so models stay accurate without extra analyst hours.
Streamline Compliance Reporting
Access audit-ready transaction histories, easing PCI & regulatory compliance burdens.
AI-Native Adaptive Scoring
FraudNet intelligently adapts with every authorization and chargeback, dynamically adjusting risk thresholds to effectively block emerging fraud while approving legitimate transactions. This ensures you maintain security without compromising on customer experience, driving trust and boosting your portfolio's growth potential.
Unified Case Management
Streamline your fraud investigations with our unified dashboard, linking transaction evidence, workflows, and recovery actions. Cut investigation time by up to 50%, empowering your analysts to focus on strategic initiatives and drive higher-value outcomes for your issuing business.
Built-In Regulatory Alignment
Stay audit-ready effortlessly with our pre-configured rules and transparent model explanations. Meet PCI DSS, PSD2 SCA, and regional mandates without the need for additional compliance staff, ensuring peace of mind and cost efficiency as you navigate the regulatory landscape seamlessly.
Impact & Results
Delivering Results that Matter
We don’t just promise better fraud control—we deliver tangible improvements that protect your business.
97%
Fewer False Positives
Approve more valid transactions confidently.
88%
Fraud Reduction
Experience double-digit reductions in fraud-related chargebacks
60%
Cost Savings
Save time and resources while securing your revenue.
Why FraudNet
Future-Proof Your Fraud & Risk Program
With an integrated platform designed for precision, agility, and impactful results, enabling your team to make smarter decisions, improve operational efficiency, and fuel your business growth.
Customizable & Scalable
No-code rules engine, flexible dashboards, and tailor-made machine learning models that are designed to adapt seamlessly and scale alongside your business.
End-to-End Platform
Unify fraud detection, compliance, and risk management into one powerful solution, saving valuable time and streamlining your operations.
AI Precision You Can Rely On
Reduce false positives, detect and prevent more fraud, and mitigate risk with highly accurate, real-time risk scoring and anomaly detection you can trust.
Real-Time Fraud Intelligence
Leverage advanced analytics, comprehensive reporting, and our Global Anti-Fraud Network to make faster, smarter decisions on the spot.
Testimonials
Real Success From Real Teams
Fraud.net’s flexibility has helped our AfterPay business grow by allowing us to meet our increasingly complex customer and country requirements. Their platform has enabled Arvato to increase our agility and significantly reduce fraud attacks.
Director Risk & Fraud, Arvato
FraudNet's combination of customized machine learning and flexible rules management has been transformative. We've achieved dramatic efficiency gains while maintaining robust fraud protection - a game-changer as we navigate evolving regulatory requirements.
Head of Financial Crime, Countingup
The great usability of Fraud.net is night and day when comparing it to our prior risk prevention platform. Reporting is also faster, more straightforward, and more impactful. With Fraud.net, we can easily visualize and share findings, providing our leadership with a clear understanding of the return-on-investment for our activities in real-time.
Fraud Manager, Global Financial Institution
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FAQs
What is Issuer AI risk scoring?
Issuer AI risk scoring is a method used by financial institutions to assess the risk associated with issuing credit or debit cards to customers. By leveraging artificial intelligence, issuers can analyze large datasets to predict the likelihood of fraudulent activities or defaults. This approach helps in making informed decisions about approving, declining, or reviewing transactions, ultimately improving the security and efficiency of payment processing.
How does AI improve risk scoring for issuers?
AI enhances risk scoring by analyzing vast amounts of data in real time, identifying patterns and anomalies that human analysts might miss. Machine learning algorithms can continuously learn from new data, improving their predictive accuracy over time. This allows issuers to better detect potential fraud, reduce false positives, and make quicker, more accurate decisions about credit risk and transaction approvals.
What data is used in AI risk scoring models?
AI risk scoring models utilize a variety of data sources, including transaction history, customer behavior, credit scores, payment patterns, and even social media activity. By integrating diverse data points, these models can create a comprehensive profile of each customer, helping issuers to more accurately assess risk levels. The use of big data analytics allows for more nuanced insights into potential fraud and creditworthiness.
What are the benefits of using AI for risk scoring?
The benefits of using AI for risk scoring include increased accuracy in fraud detection, reduced operational costs, and faster decision-making processes. AI models can process and analyze data much more quickly than traditional methods, allowing issuers to respond to potential threats in real time. Additionally, the use of AI can enhance customer experience by minimizing false positives and ensuring legitimate transactions are processed without delay.
Are there any challenges associated with AI risk scoring?
Yes, there are challenges, such as ensuring data privacy and security, managing the complexity of AI models, and addressing potential biases in data. It is essential for issuers to maintain transparency in how AI models make decisions, as well as ensure that they comply with regulatory standards. Continuous monitoring and updating of models are necessary to adapt to new fraud patterns and evolving market conditions.
How do issuers ensure the ethical use of AI in risk scoring?
Issuers ensure the ethical use of AI in risk scoring by implementing robust governance frameworks, establishing clear guidelines for AI usage, and conducting regular audits. They focus on maintaining transparency in decision-making processes and actively work to eliminate biases in AI models. Collaboration with regulators and industry stakeholders is also crucial to ensure compliance with ethical standards and to develop algorithms that are fair and unbiased.