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Deep Learning in Insurance: The Path to Adoption


Emerging technologies are enabling companies across verticals to transform their processes and bring about a paradigm shift in the global business landscape. Even the traditionally slow-to-adopt-technology insurance sector has not been not untouched by this drive to disrupt and become more competitive. While the insurance space is fraught with inherent barriers that prevent any sweeping, rapid change — like tight regulatory and compliance requirements — the change is inevitable. Propelled by concepts of advanced analytics, robotics, the Internet of Things, artificial intelligence (AI) and deep learning (DL), the insurance space is on the threshold of perhaps, its most disruptive phase ever.

Inusrance Whitepaper

This whitepaper highlights few insights on :

  • Potential applications of deep learning in insurance.
  • What are the key steps to adopt deep learning?
  • Why investing in smart tools is essential?

arya iconAbout Arya


Arya.ai is a platform to manage deep learning applications from build to production deployment. Vega - the workbench, eases the process of building complex neural networks and automates mid-level tasks driven by deep learning for optimized resource allocations. With 'Vega' - Enterprise and 'Vega' - Cloud, developers can either leverage the cloud or deploy the workbench on premise and scale Deep learning solutions. The platform has an eco-system of micro-apps like Neural Networks, trained models and vertical apps in Insurance such as Claims Process Automation, Underwriting Automation, and Predictive Modelling for Risk Analysis.