Visual Intelligence for InsurTech

ranjeetthakur


Description:

The insurance industry was once a laggard when it came to adopting cutting-edge technologies like deep learning and blockchain. But after the banks in major countries started using technology like cloud and AI, the business benefit became quite evident. The insurance industry then started thinking along the same lines. Business leaders at insurance companies began asking questions like: Can the process for claims settlement be automated? How can technology be used to detect fraud? Today, there are insurance companies doing a proof of concepts with cutting-edge technology like artificial intelligence and machine learning, to address such requirements. Recent advances in Deep Learning have made Computer Vision way powerful than it was in the 90s. Computer vision in a few domains has surpassed human level accuracy. Computer vision now is capable of solving many challenges in Insurance landscape ranging from claims processing, damage estimation to visual inspection.

Outline -

  1. Introduction
  2. Classical claims and inspection pipelines
  3. What is InsurTech?
  4. Introduction to Visual Intelligence Intelligent claims to process with Computer Vision
  5. Property inspection with visual intelligence
  6. AI-based Smart driving assistance
  7. Consuming modern AI research
  8. Challenges

Challenges

Key takeaways of the talk- In this digital era, It requires analyzing the customer needs and catering to it through redefined customer service propositions and improved products. The story of the digital transformation of insurance companies is now about connecting the dots- between data, devices and business processes.

Prerequisites:

NA

Content URLs:

Slides initial draft - https://drive.google.com/file/d/1j7K8cOQAP5uXzNdDjaaCQTpcKtbkFp00/view?usp=sharing

Speaker Info:

Ranjeet is a Data Scientist at Roadzen, a multinational InsurTech startup and a Researcher at MIDAS Lab, IIIT Delhi.

Speaker Links:

https://www.linkedin.com/in/ranjeet-singh-332b2310a/

Id: 1124
Section: Data Science, Machine Learning and AI
Type: Talks
Target Audience: Advanced
Last Updated: