Enhance fraud detection, streamline compliance, and boost operational efficiency with unified cross-network risk intelligence for seamless transactions.
Unify your data, streamline compliance, and boost fraud detection efficiency to reduce losses and improve customer satisfaction.
Issuer, acquirer, and network data live in separate systems, making it hard to see complete customer behavior and slowing fraud investigations.
Limited context forces rigid rules that flag legitimate payments, driving unnecessary declines, chargebacks, and unhappy merchants.
PSD2, PCI DSS, and regional mandates vary by rail; reconciling multiple reporting formats strains compliance teams.
Analysts jump between tools to validate alerts, inflating headcount and delaying decisions during peak transaction loads.
Streamline fraud detection and compliance, empowering payment companies with seamless data integration and smarter decisions.
We don’t just promise better fraud control—we deliver tangible improvements that protect your business.
Approve more valid transactions confidently.
Experience double-digit reductions in fraud-related chargebacks
Save time and resources while securing your revenue.
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.
No-code rules engine, flexible dashboards, and tailor-made machine learning models that are designed to adapt seamlessly and scale alongside your business.
Unify fraud detection, compliance, and risk management into one powerful solution, saving valuable time and streamlining your operations.
Reduce false positives, detect and prevent more fraud, and mitigate risk with highly accurate, real-time risk scoring and anomaly detection you can trust.
Leverage advanced analytics, comprehensive reporting, and our Global Anti-Fraud Network to make faster, smarter decisions on the spot.
Cross-network risk in payment companies refers to the potential threats and vulnerabilities that arise when transactions are processed across multiple payment networks. These risks can include data breaches, fraudulent transactions, and operational disruptions that may occur due to differences in the security standards, protocols, and technologies used by different networks.
Payment companies can mitigate cross-network risk by implementing robust security measures such as encryption, tokenization, and multi-factor authentication. Additionally, they can conduct regular risk assessments, establish strong partnerships with network providers, and ensure compliance with industry standards like PCI DSS. Continuous monitoring and analysis of transactions across different networks also help in identifying and addressing potential threats early.
Data analytics plays a crucial role in managing cross-network risk by enabling payment companies to detect and analyze patterns and anomalies in transaction data. By leveraging advanced analytics tools, companies can identify potential fraud, assess risk levels, and make informed decisions to enhance security measures. Predictive analytics can also help in anticipating future risks and devising strategies to mitigate them effectively.
Compliance is essential in managing cross-network risk because it ensures that payment companies adhere to established security standards and regulations. Compliance with standards like PCI DSS helps in safeguarding sensitive data and maintaining the integrity of payment networks. It also reduces the likelihood of legal liabilities and enhances customer trust by demonstrating a commitment to protecting their financial information.
Ignoring cross-network risk in payment processing can lead to severe consequences such as data breaches, financial losses, reputational damage, and regulatory penalties. Failure to address these risks may result in unauthorized access to sensitive information, fraudulent transactions, and operational disruptions. In the long term, it can erode customer trust and negatively impact a company's market position and profitability.
Emerging technologies like artificial intelligence, blockchain, and machine learning are transforming cross-network risk management by providing advanced tools for detecting and preventing fraud. AI and machine learning enable real-time monitoring and analysis of vast amounts of transaction data to identify anomalies. Blockchain offers enhanced security through decentralized and tamper-proof ledgers. These technologies help payment companies improve their risk management strategies and respond more effectively to evolving threats.