Proactive Threat Detection in CRM: Applying Salesforce Einstein AI and Event Monitoring to anomaly detection and fraud prevention
DOI:
https://doi.org/10.63397/ISCSITR-IJSRAIML_04_01_002Keywords:
CRM Security, Salesforce Einstein, Event Monitoring, Anomaly Detection, Fraud Prevention, Predictive Analytics, AI in CRM, User Behavior Analytics, Cybersecurity, Threat IntelligenceAbstract
In the digital era, the integrity of customer relationship management (CRM) platforms is paramount, particularly when they form the nexus of customer data, financial transactions, and service delivery. This research explores the integration of Salesforce Einstein AI and Event Monitoring as a dual framework to proactively detect threats and anomalies within CRM systems. By leveraging artificial intelligence-driven insights and real-time event tracking, organizations can not only automate fraud prevention mechanisms but also identify patterns that signal impending threats. The study evaluates AI algorithms used in anomaly detection, behavioral biometrics, and predictive modeling. Furthermore, it presents a reference architecture, use-case scenarios, and practical implementation metrics across industries including finance, healthcare, and retail.
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