How AI automates the claims process for faster payouts

The claims process for auto insurance has traditionally been a manual process with multiple steps of documentation, reporting, verification, and approval, with some human intervention needed at every step.

This has caused the entire process to always be tiring, cumbersome, and annoyingly time-consuming, leaving the customer with an overall bad experience.

However, given how smart Artificial Intelligence is today, many of the steps in the claims process can very easily be automated, reducing the need for human intervention and hence, cutting down on the time and effort taken to process claims from start to end.

In this blog, we talk about the steps involved in the claims process and how AI can help automate some of these processes for faster payouts.

(Also read: 6 advantages of Insurance Claims Automation)

Understanding the claims process

Before we dive into how AI can automate the claims process for faster payouts, let's first understand the different steps involved in this process, from raising a claim to the payout.

This process usually involves eight steps which includes claim reporting, acknowledgement, investigation, estimate generation, approval or denial of claim, settlement process, closure, and post-claim analysis.

Raising a claim

This is the first step of the claims settlement process, where a policyholder reports an incident to the insurance company with a valid reason to raise a claim. In this step, the policyholder is required to share details like

• The policy number
• Date, time, and location of the incident
• Description of the incident (eg- accident, theft, natural disaster etc.)
• Photos of the image (if applicable)
• Police report (if required)

These details are then passed on to the insurance officer whose job is to verify or reject the reasons presented for raising a claim.

Acknowledgement of the claim

Once a policyholder shares the details mentioned above, an insurance officer validates the details shared, and issues an acknowledgement to confirm the receipt of the policyholder's request.

This acknowledgement includes assigning a claims handler to the case, a claims reference number for the policyholder to refer to in the future, and information regarding any additional documentation needed from the policyholder's end.

Investigation

Once the policyholder's request has a claims reference number and a handler assigned to it, the next step is to verify different aspects on the policyholder's side, such as

• Policy validity and coverage details
• Damage extent via a physical inspection
• Liability determination (who is at fault? Or is any third party involved? etc.)
• Fraud check to ensure that the policyholder's claim is genuine and not exaggerated.

(Also read: Everything you need to know about Motor Insurance Inspection)

Estimate generation

Once the investigation is completed from the insurer's end, the next step is to generate an estimation on how much of the damage the insurance company can cover based on the details from the inspection, current market rates for repairing/replacing the said damage, and how much of the damage the policyholder's insurance plan covers.

Approval or denial of claim

Once the estimates are generated, they are then shared with the policyholder. In a lot of cases, if the repair/replacement evaluation matches the value of what the policyholder's plan covers, then the estimate is marked approved.

However, in case of any discrepancies, the insurance company will share the reason for denial with the policyholder with possible next steps.

Settlement process

Assuming that the claim has been approved by both the insurance company and the policyholder, the next step would be the settlement process. This process could either be a -

• Cashless process where the insurer directly pays the repair shop for covered expenses (often happens when the policyholder uses the insurer's repair network)
• Reimbursement where the policyholder can visit a repair shop of their choice and pay for repairs upfront, while the insurer promises to reimburse them later.
• Total loss/write-off where the repair cost exceeds the car's insured value, in which case the insurer offers the insured declared value (IDV) of the vehicle.

Closure

This is the last but final step in the claims settlement process where the insurer closes the claim request after the repairs and payment for repairs have been completed for the vehicle.

In this step, the policyholder also receives documentation regarding the settlement process which confirms the closure of the claim.

Post-claim analysis

Finally, the last step is on the insurer's end, where they feed all the necessary data (reason and extent of damage, payouts made, time taken for settlement etc.) into their system.

This data can is used to improve the claims process, influence future premium prices, and also improve fraud detection for future cases.

How can AI be used to improve the claims settlement process?

Based on what we've covered so far, it is clear that the current claims process requires a lot of human intervention at different steps for documenting, reporting, analysing, and approving the claim request by a policyholder, making it very inefficient and inconvenient.

However, with the right AI tools to support different steps in the claims process, this can very easily be automated to improve speed and efficiency, and require minimal human interaction throughout the process.

There are two methods through which we can improve the claims process using AI - STP (Straight Through Processing) and Fast Track Claims.

What is Straight Through Processing?

Straight Through Processing (or STP) is when a claim process is fully automated from start to finish without the need of any human intervention. It is often used for simple, low-risk claims that are based on some pre-defined criteria, and don't have a lot of variability.

Here's how it works

1. Raising a claim
   - Here, the policyholder can raise a claim using an existing app or website provided by the insurance company.
   - In this step, the policyholder will have to share images/videos of the damage, incident description, and other important information.
   
2. Validation
   - Once this is done, an AI model will then analyse the policyholder's claim and verify the incident details, policy coverage etc.
   - After this, the AI model will decide the policyholder's eligibility based on some pre-defined rules (eg: low claim amount, no third-party liability etc.)
   
3. Damage assessment
   - This is one of the key steps where AI can help remove human intervention.
   - In this step, the AI model is capable enough to detect damage based on the images uploaded and can generate a detailed report about the extent of damage within a few seconds to a few minutes.
   
   (Also read: How can AI-based solutions automate Repair Estimation for insurers)
   
4. Approval of claim
   - Based on the previous steps, if the claim case is simple and follows a known pattern, the AI model will immediately approve the request and the payout process will begin.
   - However, if there are any discrepancies (or scenarios that the AI model can't understand), it'll highlight the claim request seeking a manual review.
   
5. Payout
   - This is the final step in the process where the payment is directly initiated to the policyholder or repair shop once the claim is approved.

Straight Through Processing works great for minor/physical damage, glass damage, thefts etc. by improving the speed and efficiency of the entire process, and increasing customer satisfaction.

However, it isn't 100% fool-proof and comes with its own set of challenges such as

• The automated system might struggle to identify sophisticated fraud attempts and get tricked into paying more than necessary.
• It struggles with cases that have complex damage cases such as existing damage, internal damage, third-party involvement etc.
• Using an inefficient AI model that isn't smart enough to understand nuances might cause a ton of false reports, resulting in losses in the long run.

What are Fast Track Claims?

Fast Track Claims are similar to STP claims in a lot of ways. The biggest difference between the both is that, unlike STPs, Fast Track Claims use a combination of AI and streamlined human processes to ensure faster and more efficient claim settlements. Here's how they work

1. Raising a claim
   - Policyholders can raise a claim for damage from an app/website provided by the insurance company.
   - These apps/websites are plugged with an AI model that is trained to pre-qualify claims based on the input.
   
2. AI-powered Damage assessment
   - Similar to STPs, Fast Track Claims also use AI models to detect external damage on a vehicle.
   - In case of internal excessive damage, the model will flag the claim asking for human intervention.
   - In this case, a human will validate the reports of the AI model and also run an assessment manually to ensure a thorough damage check on the vehicle.
   
3. Simplified approval
   - Once all the necessary data is collected during the damage assessment process, claims are approved without the need of multiple inspector visits or a prolonged verification process.
   
4. Cashless settlement
   - After the claim is approved, the insurer can directly settle repair costs with their network garages, or reimburse the policyholder almost immediately.

Key differences between STPs and Fast Track Claims

How does Inspektlabs automate the claims process?

Now that you have a better understanding of how the claims process works, let's talk about how Inspektlabs is trying to automate this porcess by building an end-to-end solution that works great for claims settlement for insurance companies.

Here are a few reasons why Inspektlabs would be a great fit to automate your insurance business

• Our AI-driven solution uses a proprietary algorithm trained on 10M+ images/videos of different damages on vehicles that allows a model to fully understand the extent of the damage on a vehicle.
  
• With our product, you can cut down on the time taken on generating damage reports, and analysing them, allowing you to fast-track the validation and approval process, saving you both time and effort.
  
• Along with this, we also enable you to give your customers a novel experience by allowing them to scan the damages on their vehicle themselves (by capturing a 360° view of the vehicle using their smartphone), thereby removing the need for a physical inspector, and also giving them more transparency in the process.
  
• However, giving your customers control comes with the challenge of increased fraud, right? Wrong!
  Our proprietary AI model is also trained to detect all sorts of fraud to make sure that your customers don't cheat you and try to make some extra money in the process.
  
• Additionally, you can also easily generate and share estimates for repair or replacements for different vehicle parts, thanks to our Estimatics partners who can connect you with the right repair networks.

Overall, with Inspektlabs' AI-powered solution by your side, you not only save time, but also increase money, and reduce costs for your claims settlement process, and give your customers an experience like never before.

If you're interested in checking out more about how Inspektlabs can help automate your Insurance business' claims process, reach out to us here.

Conclusion

By the end of this blog, we hope you have a better understanding of the different steps taken during a claim settlement process, and why it often gets delayed causing a hassle to all parties involved in the process.

Additionally, we also covered the different steps that can be automated in the claims process, making it a lot more efficient and saving time for everyone.

Also remember, if you're looking for help in this field (automating your claims process), make sure to reach out to the pioneers in the industry i.e. Inspektlabs. Check out more details here.