WNS Triange Hackquest

WNS Triange Hackquest

Datasets

WNS Triange Hackquest

File

WNS Triange Hackquest

Use Case

Computer Vision

Description

This poses a formidable challenge to insurance companies as they strive to differentiate between legitimate and deceitful claims.

WNS Triange Hackquest

About Dataset

Problem Statement

In the world of insurance, one big job is handling claims for vehicle damage. It’s important but happens a lot. But there’s a problem: figuring out which claims are real and which ones are fake. This can cost insurance companies a lot of money. With the rise of Generative AI and other advanced models, more people are making fake claims. They use fake pictures to try to get money from insurance companies.

This is a big problem for insurance companies. They need to figure out which claims are real and which ones are fake. Fake claims usually involve saying the damage is worse than it really is or making up things that didn’t happen at all. To stop losing money and keep their business honest, insurance companies have to come up with good ways to spot fake claims quickly and accurately.

In this hackathon, the WNS team is asking people to come up with a strong and efficient computer program that can look at pictures and tell if they’re real or fake in insurance claims. If we can spot fake pictures accurately, insurance companies can check if a claim is real and decide if they should pay out money or not.

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quality dataset

Quality Data Creation

Guaranteed TAT​

Guaranteed TAT

ISO 9001:2015, ISO/IEC 27001:2013 Certified​

ISO 9001:2015, ISO/IEC 27001:2013 Certified

HIPAA Compliance​

HIPAA Compliance

GDPR Compliance​

GDPR Compliance

Compliance and Security​

Compliance and Security

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