The insurance space is fraught with inherent barriers that prevent any sweeping, rapid change. In particular, health-claims processing involves a slow decision-making process that is costly and frustrating for insurers.
However, change is inevitable. Propelled by advanced analytics, the Internet of Things, artificial intelligence (AI) and deep learning technologies, the insurance industry is on the threshold of an extremely disruptive phase. This new era is bound to improve consumer experience and satisfaction, reduce claims-processing and operational costs, and increase underwriting profits.
Ushering in this transformation is Arya.ai, a member of the Intel® AI Builders partner program. Arya’s insurance claim workload automation software alleviates inefficiencies in the system by automating the entire process in near real time, from initial assessment and validation of a claim through the end decision and adjudication. This AI-based application leverages the Intel® Optimized TensorFlow* framework running on the latest Intel® Xeon® Scalable processors, to secure performance boosts in inference workloads. Insurers can now promise faster claims settlements to users in near real time compared to current fragmented process with long turnaround times.
Come see how at the AI Conference in London, which will be presented by O’Reilly and Intel® AI from October 8-11, 2018. Visit the Arya booth (#107) and see the demo in action!
Additionally, demo attendees will learn about:
- Automating the entire health insurance-claims process
- Autonomous learning in production for improved adaptability
- Building, managing and scaling complex Deep Learning applications
Learn more about deep learning in the insurance sector with Arya.ai’s white paper.
Arya.ai is an end-to-end deep learning platform enabling businesses to build, train, manage and scale deep learning solutions. The company has built an eco-system of standalone deep learning apps on the VEGA platform for financial services – Insurance, Banking and Lending. Arya.ai makes it easier and quicker for businesses using Deep Learning by automating complex data science tasks such that business can quickly deploy deep learning for multiple complex problems within resource limitations. Vega – the workbench, eases the process of building complex neural networks and automates mid-level tasks driven by deep learning for optimized resource allocations.