AI-Driven Fraud Detection in Banking: The Convergence of Predictive Analytics and Salesforce CRM Automation
DOI:
https://doi.org/10.63282/pe18mm54Keywords:
Predictive analytics, Salesforce CRM automation, Machine learning, BankingAbstract
The detection of fraud in banking operations experienced significant advancement through the integration of Artificial Intelligence (AI). This research examines the performance benefits of integrating predictive analytics solutions within Salesforce Customer Relationship Management (CRM) automated systems for fraud detection procedures. A system using artificial intelligence models, including Machine Learning (ML) and Deep Learning (DL), has been established to examine financial patterns and customer activity. Additionally, this paper examines how Salesforce CRM automation functions in fraud detection operations. These technologies combine to support on-time fraud discovery, which reduces spurious alerts and boosts banking safety levels. AI-driven technology shows its efficacy through multiple case research and experimental findings. System efficiency is evaluated through the assessment of precision together with recall and accuracy performance indicators. This paper enhances existing research through empirical findings and offers a model structure that integrates predictive analytics using AI with CRM automation systems
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