Smart Identification™
For fast and accurate insurance premium calculation
The Challenge.
Insurance companies in India and worldwide find it very challenging to calculate premiums with precision. Premiums are usually based on the risk profile of a property. Risk profiling requires thorough inspection by brokers or field-officers and can usually take more than one visit. Not only is this process challenging but also time-consuming, costly and prone to mis-calculations.
At AIndra Labs, we have a built a solution to automate this process for insurance companies using Artificial Intelligence.
The Solution.
SmartIdentification™ is an AI-powered risk inspection solution for Insurance companies. It uses Computer Vision and Machine Learning algorithms to automate property risk profiling and valuation reporting. SmartIdentification™ is currently used by ICICI Lombard, a leading insurance company in India.

How it Works.
Click pictures of the property using any camera-enabled device. Smart Identification will process the pictures, identify the objects and it will generate the risk profile of the property.
Input
Capture photo of the building
space and upload
AIndra Engine
Output
Process the pictures and identify the objects
Improve Business Operations.
Hardware agnostics
Helps process images captured from any camera-enabled device such as smartphones, Cameras, Drones and Surveillance cams
AI-based
Foolproof and self adaptive intelligent solution
Portability
Risk assessment inside property and on-site venues
Personalization
Geolocation and time tagging for on-site property specific information
Cloud-based
Zero capex cost and high on adaptability
Runs on DNN based CV and ML platform
Highly scalable and contextualized risk inspection based on visual, contextual and historical data
The Impact.
Saves cost
Almost 45% less on cost than on-site risk inspection
Saves time
Automated claim settlement takes 75% less time than traditional claim settlement
Detects fraudulent claims
Poolproof claim settlement reducing fraudulent claims by almost 28%