Nia Fraud Detection for Credit Cards is an AI/ML based business application, which can non-intrusively supplement a credit card issuer’s existing systems to accurately prioritize alerts for fraudulent transactions. It reduces false positives and accurately detects fraud in credit card transactions, thereby reducing cardholder churn, revenue leakage and operational costs.
While the major credit card issuers adopt a plethora of fraud detection solutions, not enough attention is paid to the consequences of false positives (alerts resulting in genuine transactions being denied) and emerging fraud patterns.
As a result, the opportunity cost of preventing fraud often works out to be more than the fraud losses itself.
With the rapid increase in business and transactions moving online, fraudsters are devising more sophisticated means of committing credit card fraud. What if there a solution that can enrich the fraud detection solutions to help keep pace with this? And how about them leveraging advances in AI/ML and make sense of the tons of internal and external data available without having to deal with the complexity that comes along?
By leveraging Infosys Nia™ the purposeful AI and automation platform, the application promptly ingests and transforms credit card alerts and transactions data, builds models, predicts fraudulent transactions thereby enabling automation-led decision-making in credit-card fraud detection. It implements adaptive self-learning to automatically learn from historical and ongoing transactions, data patterns and investigator’s feedback. It then automatically updates the models in near real-time in sharp contrast to conventional rule-based systems. The following are the features of the Nia Fraud Detection for Credit Cards application.
Fraud Alert Prioritization
Visualizations and Reports
Infosys Nia Platform
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