How AI is Revolutionizing Claims Management and Personalized Auto Insurance

Managing insurance claims is seen as a complicated and lengthy process. Insurance companies receive numerous claims daily, from vehicle accidents and medical expenses to property damage. Manually handling these claims can result in delays, errors, and fraud. We can use Artificial intelligence to simplify the process.

The Problem with Traditional Claims Management

When you make an insurance claim, here’s what usually happens:

  1. You submit your documents (medical bills, photos of damage, etc.).
  2. The insurance company reviews everything manually—a process that can take weeks.
  3. They assess your claim to determine if it’s valid and how much money should be paid.
  4. The claim is either approved or rejected.

While this process sounds straightforward, it’s full of challenges, such as:

  1. It’s Slow: Manually going through forms, photos, and receipts takes much time.
  2. It’s Expensive: Insurance companies need big teams to process claims.
  3. It’s Prone to Errors: Humans can make mistakes when reviewing claims.
  4. It’s Vulnerable to Fraud: Detecting fake claims is difficult without proper tools.

All these issues make it clear that insurance companies need smarter solutions—and that’s where AI comes into the picture.

How AI is Solving These Challenges

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How to run object detection on CCTV feed

In this blog we explore how to run a very popular computer vision algorithm YOLO on a CCTV live feed.

In this blog we explore how to run a very popular computer vision algorithm YOLO on a CCTV live feed. YOLO (You Only Look Once) is a very popular object detection, remarkably fast and efficient. There is a lot of documentation on running YOLO on video from files, USB or raspberry pi cameras. This series of blogs, describes in details how to setup a generic CCTV camera and run YOLO object detection on the live feed. In case you are interested in finding more about YOLO, I have listed out a few articles for your perusal at the end of this blog.

Setup a CCTV with RTSP

This blog lists out in details methods to setup a generic CCTV camera with a live RTSP feed. Note the RTSP url, as we will need it in the later stages. The RTSP (

CCTV camera with RTSP
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Use-cases of Machine Learning in E-Commerce

What computing did to the usual industry earlier, Machine Learning is doing the same to usual rule-based computing now. It is eating the market of the same. Earlier, in organizations, there used to be separate groups for Image Processing, Audio Processing, Analytics and Predictions. Now, these groups are merged because machine learning is basically overlapping with every domain of computing. Let us discuss how machine learning is impacting e-commerce in particular.

The first use case of Machine Learning that became really popular was Amazon Recommendations. Afterwards, the Netflix launched a challenge of Movie Recommendations which gave birth to Kaggle, now an online platform of various machine learning challenges.

Before I dive deep into the details further, lets quickly brief the terms that are found often confusing. AI stands for Artificial Intelligence which means being able to display human-like intelligence. AI is basically an objective. Machine learning is making computers learn based on historical or empirical data instead of explicitly writing the rules. Artificial Neural networks are the computing constructs designed on a similar structure like the animal brain. Deep Learning is a branch of machine learning where we use a complex Artificial Neural network for predictions.

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