Gain real-time insights, enhance fraud detection, streamline compliance, and improve customer experience seamlessly with AI-Native analytics.
Protect your business by addressing critical challenges, reducing fraud losses, enhancing customer satisfaction, and ensuring regulatory compliance effortlessly.
Phishing, credential stuffing, and SIM-swap attacks let criminals hijack cardholder logins, forcing issuers to absorb unauthorized spend, chargebacks, and reputation damage.
Fraudsters stitch real and fake data to open new card accounts, creating hard-to-collect balances that distort credit models and inflate provisioning costs for issuers.
Legacy rule sets often flag legitimate spend as suspicious. Issuers lose interchange, anger cardholders, and watch active card rates slip to competitors.
Mandates such as PSD2, AML, and CFPB demand granular audit trails and instant reporting, stretching issuer resources and risking costly fines.
FraudNet empowers issuers to fight fraud, enhance customer trust, and streamline compliance with ease.
Shares cross-issuer insights to stop emerging fraud without overblocking.
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.
Issuer real-time analytics refers to the immediate analysis of transaction data by financial institutions that issue credit or debit cards. This process helps issuers monitor and evaluate transaction patterns, detect potential fraud, enhance customer experiences, and make informed decisions instantly. By leveraging real-time analytics, issuers can respond quickly to emerging trends and threats, ensuring secure and efficient transaction processes for their customers.
Real-time analytics provides several benefits to issuers, including the ability to detect and prevent fraudulent transactions instantly, optimize authorization processes, and improve risk management. Additionally, it enhances customer satisfaction by reducing false declines and ensuring seamless transaction experiences. By leveraging real-time insights, issuers can also tailor marketing strategies to individual customer preferences, ultimately leading to increased customer loyalty and revenue growth.
Issuer real-time analytics typically utilizes advanced technologies such as machine learning, artificial intelligence, and big data analytics. These technologies enable issuers to process vast amounts of transaction data swiftly and accurately. Machine learning algorithms can identify patterns and anomalies in real time, while AI can automate decision-making processes. Additionally, cloud computing is often employed to store and manage data efficiently, ensuring scalability and flexibility in handling fluctuating transaction volumes.
To ensure data privacy in real-time analytics, issuers implement robust security measures, such as encryption, tokenization, and secure data storage solutions. They also adhere to strict regulatory standards like GDPR and PCI DSS to protect customer information. Additionally, issuers utilize anonymization techniques to process data without exposing personal identifiers and regularly conduct security audits to identify vulnerabilities. By prioritizing data privacy, issuers build trust with customers and maintain compliance with legal requirements.
Yes, real-time analytics can significantly reduce chargebacks for issuers by detecting potential fraudulent transactions before they are processed. By analyzing transaction data instantaneously, issuers can identify suspicious activities and take preventive measures, such as declining the transaction or flagging it for further investigation. This proactive approach helps minimize the likelihood of chargebacks, which are often costly and time-consuming for issuers to manage. Additionally, real-time analytics can enhance dispute resolution processes by providing accurate and timely transaction insights.
Issuers face several challenges with real-time analytics, including the need for substantial computational resources to process large volumes of data swiftly. Integrating analytics systems with existing infrastructure can be complex and costly. Additionally, ensuring data accuracy and consistency across various touchpoints is crucial to avoid erroneous insights. Real-time analytics also requires continuous monitoring and maintenance to adapt to evolving fraud tactics and regulatory changes. Despite these challenges, effective implementation can lead to significant operational and security benefits.