A2019 – Fraud Detection Bots

QualityArc
April 14, 2020
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How many times have insurance companies encountered fraudulent claims? Here are some statistics as per fortunly.com.

  • Fraudulent claims total at least $80 billion per year in the United States.
  • Insurers pay out up to 10% of their claims cost on fraudulent claims annually.
  • At least 1 in 10 small business owners worry that their employees will fake work-related injuries.
  • All of this happens even though 95% of insurance companies use anti-fraud technology.

The above statistics encompasses all insurance types however numbers around auto insurance are also not uncommon which may make insurers uncomfortable.

A mechanism is much needed which uses advanced intelligence to analyze claims, damage images in order to produce confidence levels on the claim.

This bot analyzes and extracts unstructured data from documents and images and uses Artificial Intelligence subfields such as Natural Language Processing, computer vision to analyze car damages and estimates damages.

The bot then analyzes the claim details, images, sends it to the Google AutoMl package to detect fraud and estimate to predict claim risk and determine confidence. On getting a satisfactory score, the bot then automatically emails the claim for approval/further processing.

The bot’s benefits are:

  • Industry-leading accuracy for image understanding
  • Detect and classify auto images for further downstream automation
  • Seamlessly integrates with RPA to use in your bot workflows
  • Engaging mobile experience to enable customers upload auto images

All you need is a CSV file with insurance details, google cloud credentials and AAE control room access. If you do not have an AAE control room or have not onboarded the RPA journey, QualityArc with its RPA excellence and experience, can help establish the required infrastructure for running the bot and the bot itself.