The Role of AI in Car Insurance Claim Approvals

Understanding AI in Car Insurance Claims

AI is an advanced computer system that mimics human intelligence. Hence, insurance companies have begun to use AI to automate and enhance multiple stages of the claim approval workflow, which previously required human resources.

Steps such as accepting claim documentation and vehicle photos of damage, checking policy coverage, identifying unusual patterns, estimating repair costs, etc., are now handled by AI. Previously, human claims officers performed these steps manually, extending into several days and even weeks in complex cases. 

However, it has changed today. Now, AI conducts the initial inspection instead of a surveyor. AI analyses images of your damaged vehicle to assess the extent of the damage and determine whether the claim is genuine or staged. It can also estimate repair costs to improve the accuracy and speed of the claim approval process.
 

How AI Accelerates Claim Approvals?

Using AI in car insurance processes can reduce the average claim processing time to approximately 36 hours , down from the traditional 10-day period. AI relies on the following three key mechanisms to speed up claim approvals.

• Image Recognition

AI models can effortlessly analyse pictures of the damaged car uploaded by the policyholders and identify damaged areas, such as dented bumpers or cracked windshields. 

They then classify the severity of damage and even spot whether an image has been manipulated or reused. It reduces reliance on the surveyors’ initial physical inspections, leading to faster and automated claims approval.  

• Predictive Analytics

Insurers can feed historical data, such as claim data, vehicle types, accident types, repair cost outcomes, etc., to their machine learning models. Training AI on company-specific data like this can help insurers get likely payout amounts for claims. 

It can also equip AI models to decide claim approval and flag cases that need a deeper human review. If a claim is genuine, AI may approve it almost instantly. 

• Instant Data Integration

AI-powered systems pull data from multiple sources. Data sourcing points, such as policy records, vehicle registration databases, and workshop invoices, are common. They use this data to validate coverage, ownership, and claim authenticity in real time. This integrated data enables claim approval decisions to be made in minutes, rather than hours or days.
 

Enhancing Fraud Detection with AI

Insurance fraud is more common than one may expect. Thanks to the integration of AI in car insurance claims processes, the system has helped the global insurance industry save more than $2.6 billion in fraud prevention. 

AI systems continuously analyse incoming claim data. It also evaluates the policyholder’s policy history, vehicle metadata, and other contextual details to identify patterns that human examiners may overlook. 

For instance, if a policyholder files a car insurance claim soon after their policy activates or the same repair shop appears in multiple high-risk claims, AI can flag the claim as suspicious or ‘high risk,’ passing it further for deeper human investigation.

AI is way more accurate than traditional fraud detection methods because it operates on the following three-fold aspects:

• Real-time Anomaly Detection

AI begins processing a claim as soon as someone files it, instead of waiting days to initiate the approval process. This real-time work approach helps the system conduct early intervention. 

• Multidimensional Pattern Analysis

Unlike rule-based checks, AI can evaluate multiple variables to calculate a fraud risk score. It typically reviews variables such as vehicle age, accident location, and claim history to provide a more accurate evaluation.

• Adaptive Learning

Fraudsters have always created newer, more sophisticated methods to file multiple fraudulent claims. Thankfully, machine learning models continue to adapt to these newer methods, detecting fraud with greater accuracy.
 

Improving Customer Experience

No one likes the lengthy process for approving car insurance claims. Hence, insurers have begun using an automated claims approval process to address this concern. Here’s how it works

• AI-Powered Chatbots

AI-powered chatbots have replaced traditional customer support to handle routine claim-related queries. It also guides policyholders through the step-by-step claim-filing process and provides real-time status updates on their filed claims. 

These automations help policyholders by keeping them informed and patient until the final decision is made. Since chatbots are available 24*7, policyholders don’t have to wait for regular working hours to get their queries answered.

• Personalised Claim Handling

AI can personalise claim handling by analysing the policyholder’s key details. It includes the policyholder’s profile, driving history, vehicle type, and past interactions for extreme personalisation. 

Low-severity claims are generally fast-tracked by AI, while complex ones get routed to dedicated insurance claims professionals. This level of personalisation was impossible with older, one-size-fits-all workflows.  

• Real Time Updates

As AI systems get integrated into claims approval workflows, policyholders can receive real-time notifications on their registered contact number. Notifications about claim registration, damage assessment completion, approval sent, etc., are all delivered instantly. 

It helps policyholders remain informed about the exact status of their claim approval request. 

Collectively, these features transform the customer experience. In 2025, customer satisfaction rose by 63%, thanks to AI-powered personalised claims assistance.
 

Challenges and Ethical Considerations

While AI has several benefits, it isn’t without its challenges. Everyone should be aware of the following challenges and ethical considerations:

• Algorithm Fairness

The output of any AI system depends on the data it was trained on. Hence, if an AI system was trained on biased data, it will lead to unfair results/actions. For instance, AI may unfairly flag specific customers or locations as ‘high-risk,’ even when they’re the least risky. 

The only way to prevent it is by regularly auditing datasets and testing AI systems for any biases. The models should be retrained after every audit to avoid making unfair decisions. 

• Data Privacy

AI systems require sensitive information from policyholders to make any claim-related decision. Information, including the vehicle’s images, telematics, and repair history, is generally required during claim submission. 

If this data is mishandled, it can lead to potential data leaks or data misuse. Insurers can address such data privacy challenges by implementing stronger encryption and adhering to strict regulatory compliance.

• Need for Human Oversight

While AI has its benefits, it lacks the 'human touch' policyholders need while having claim-related conversations after a road accident. For instance, AI can detect visible damages on the car, but it cannot assess the internal damage. Hence, insurers should have human oversight in all cases.
 

Conclusion

The adoption of AI in the car insurance industry has benefited both policyholders and insurers. As AI systems automate damage assessment, estimate repair costs, and more, policyholders can expect faster claim approvals.

If faster claim approvals and payouts matter to you, then buy Car Insurance from insurers with the fastest claim approval rates. Shriram Car Insurance policy is an excellent choice for individuals who prioritise affordable premiums and want superfast claim approvals. Shriram General Insurance also offers easy personalisation of coverage through add-on covers.
 

FAQs

1. How does AI improve car insurance claim approvals?

AI accelerates claim processing and improves damage assessment accuracy through multiple mechanisms. It also identifies whether a claim is staged or genuine, speeding up the claim approval process.
 

2. Can AI detect insurance fraud effectively?

Yes, it can. AI can analyse multiple variables and behavioural patterns to flag suspicious claims. Its accuracy is much higher than most traditional rule-based methods.
 

3. Will AI replace human claims adjusters?

No, AI systems cannot replace human claims adjusters. While AI can handle simpler claim settlement cases, it will always require a human claims adjuster for complex or suspicious claim handling.
 

4. How does AI personalise the claims experience?

AI analyses the details, such as the policyholder’s profile, vehicle details, and past behaviour to have customised communication for greater customer satisfaction.
 

5. Are AI-driven claim approvals secure and fair?

Yes, AI-driven claim approvals are both secure and fair, provided they’re trained on authentic, non-biased data.