The rise of the e-commerce industry has brought immense convenience and opportunities for businesses and consumers alike. However, this growth has been met with an increase in fraudulent activity, causing significant financial losses for companies. Merchant losses related to online payment fraud are expected to exceed $343 billion by 2027. To combat this persistent threat, the e-commerce industry can harness the power of artificial intelligence (AI), machine learning (ML), and robotic process automation (RPA) to help mitigate these losses, prepare for new fraud attempts and ensure that the customer experience remains intact.
Utilizing AI-enabled, automated financial operations (FinOps) solutions allows for continuous real-time transaction monitoring. These technologies can effectively bolster security measures by enabling vendors to monitor transactions in real-time, compare them to historical data and safeguard against fraudulent activities by identifying suspicious activity that deviates from normal behavior. Moreover, the adaptive nature of AI empowers it to continually learn and adapt to emerging dishonest tactics, making it an indispensable asset in the relentless battle against illicit activities.
Early Fraud Detection and Prevention
97 percent of global fraud prevention decision-makers at e-commerce companies experienced fraud in the past 24 months. To decrease this problem, many are turning to AI and ML to solve the growing issue. AI and ML algorithms have proven to be highly effective in identifying patterns and anomalies in large datasets. These technologies can detect fraudulent activities early and prevent financial losses by analyzing historical transactional data and user behavior. Machine learning models can learn from patterns of fraudulent behavior and continuously evolve to detect new types of fraud. To flag susp ..
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