Converging Robotics, NLP, and Insurance via Deep Neural Networks on Sustainable Cloud with Optimized Quality Assurance Resource Allocation
DOI:
https://doi.org/10.15662/IJARCST.2025.0805008Keywords:
Robotics, Natural Language Processing, Insurance Technology, Deep Neural Networks, Sustainable Cloud Computing, Quality Assurance, Resource Allocation, Digital Transformation, Financial Technology, Service OptimizationAbstract
The convergence of robotics, natural language processing (NLP), and insurance services on sustainable cloud infrastructures presents new opportunities for digital transformation in the financial sector. This paper proposes a deep neural network (DNN)-based framework that integrates robotics-driven process automation with NLP-powered customer interaction systems to enhance efficiency and decision-making within insurance workflows. By deploying the framework on sustainable cloud platforms, the system ensures scalability, energy efficiency, and environmental responsibility. Furthermore, optimized quality assurance (QA) resource allocation mechanisms are embedded to balance computational workloads, minimize operational costs, and maintain service reliability. The results highlight how the integration of DNNs with robotics and NLP can drive innovation in insurance while aligning with sustainable development goals and ensuring high-quality service delivery.
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