Securing Cloud-Based Financial Systems with AI-Powered Predictive Analytics

Abstract

This research aims to discover the impact that incorporates predictive analytics technology that delivers an AI concept in secure cloud financial systems. These systems use machine learning algorithms, behavioural analytics and neural networks to detect threats, provide faster response and control frauds. This study shows that threat detection has increased in accuracy, false positives have decreased, and reaction time has improved along with qualitative cost savings recognized in the compliance and fraud prevention activities. AI brings value to cybersecurity; it has some drawbacks, which encompasses; data privacy and ethical issues, as well as algorithm explainability. The study calls for increased partnership between stakeholders to find ways of addressing these problems and to develop sound policies. Furthermore, there is the future use of natural language processing and quantum computing in expanding the current predicting analytical technique regarding cybersecurity. Therefore, the study found out that the use of the predictive analytics through artificial intelligence is an essential tool in protecting cloud based financial systems. These new and advanced technological frameworks will act as indispensable security that is agile, elastic, and responsive to the needs of the learner financial institutions while building customer loyalty and confidence as a result of the constantly evolving digital environment.