Waiting for your health insurance claim to get approved after hospitalisation is an anxious period. If you have ever waited in the hospital for your insurer to approve your cashless claim request, you would know how long every hour feels at that time. Unfortunately, most people accept it as part of the claim settlement process.
But with the integration of Artificial Intelligence (AI) in health insurance claims processing in India, things have started to change. AI has helped insurers transform the way they manage claims, leading to faster processing, fraud detection, fewer errors and less paperwork.
However, using AI to decide whether your claim is accepted raises questions about fairness and accountability. Let’s understand how AI is helping in claims processing, how it benefits policyholders, what are the hidden risks and what you can do as a policyholder.
Buying health insurance plans is the easy part. Insurers answer your questions and follow up as they want you as customer. Besides, premium payment is a one-time decision each year. The real test comes when you actually need the coverage.
Most people complain about the same few things. Cashless approvals take hours, reimbursement claims bounce back and forth over missing documents and claims get rejected over terms and conditions that nobody explained at the time of policy purchase. Getting a lower claim amount due to consumables or room rent limits the deductions, which also surprises several families during discharge.
One of the reasons for this delay in claim processing is the amount of documents the insurer’s claims team reviews manually. A single claim can involve a pre-authorisation form, doctor notes, test reports, bills, and discharge summaries, often in different formats and sometimes in handwriting. Reviewing all of that manually can be time-consuming and can cause human errors. Moreover, they review hundreds of claims every day.
This is exactly the kind of bulky, repetitive work that AI is good at.
During health insurance claims processing, AI can help with the following activities:
AI can help read multiple documents like policy wordings, scanned bills, prescriptions and discharge summaries. It can pull out essential information from these documents and fill in details on diagnosis, procedure, dates and amounts automatically, thereby saving time.
Many insurers use AI to sort claims based on complexity. A simple claim with a low amount for a common procedure with clean paperwork can be fast-tracked. A complicated or unusual claim gets routed to a human reviewer. This helps speed up the processing time.
AI models trained on past claims can compare a hospital’s bills against typical costs for a given procedure in a given city. If a charge looks extremely expensive, it gets flagged for a closer look by a human reviewer.
Health insurance fraud, such as inflated bills, fake hospitalisations and duplicate claims, is quite common in India. AI can help spot suspicious claims, such as the same patient getting admitted at two hospitals on overlapping dates or a hospital that consistently bills much higher than others. Knowing how AI is enhancing fraud detection in health insurance is a boon for insurers.
Some of the major benefits of AI in health insurance claims for policyholders are as follows:
The biggest benefit of AI in health insurance claims for policyholders is faster claim approvals. The IRDAI’s 2024 health insurance guidelines have also directed insurance companies to decide on cashless authorisation requests within 1 hour and to give final approval at hospital discharge within 3 hours. AI helps to meet these timelines at a large scale.
Quite often, medical insurance claims get delayed or denied due to a missing document or a misspelled name. AI document checks can help identify these gaps early, sometimes even before the patient leaves the hospital.
Two similar claims should ideally be treated the same way. AI helps to reduce random treatment of similar claims as different reviewers apply policy terms differently. It identifies discrepancies and reduces human error, thereby bringing consistency in claims.
With AI-led fraud detection, genuine policyholders are less likely to be impacted by higher premiums resulting from a blanket rule meant for people filing fraudulent claims. It also lowers administrative costs of the insurer, further reducing premiums.
Medical emergencies come at any time. AI helps process claim requests even in the middle of the night just as easily as during office hours. This helps to build customer trust and real-time claim tracking improves transparency.
Government initiatives like the Ayushman Bharat Digital Mission aim to create a common structure so that hospitals, insurers and patients can share data more smoothly. As the data gets more structured with the help of AI, it can be as easy as ordering prescription medicines on medicine delivery apps in India.
Risks of AI in Health Insurance Claim Decisions
AI can give health insurance companies speed, but they can make mistakes. Take a look at some of the risks of using AI for making health insurance claim decisions:
If the AI flags your claim and a human reviewer simply agrees without checking, your claim may get rejected without a proper explanation. With the use of AI, it is easier to deny claims at scale without anyone taking real ownership of the decision.
Handwritten prescriptions, regional language notes and poor-quality scans are common in India. AI tools can sometimes misinterpret them. One wrong identification of a diagnosis in such documents can lead to a mismatch and delay your claim with no fault of yours.
AI often use data from past claim decisions to process a claim. If a hospital was unfairly penalised in the past, AI may quietly repeat the same. Patients in smaller towns or those treated at smaller hospitals more often bear the brunt of this simply because their documents look different.
AI may flag a claim as fraud even when it is genuine. A genuine claim that happens to look unusual due to a rare condition or an expensive but justified treatment can lead to a manual review and delays.
The use of AI in reading health data threatens data privacy. The more it goes through AI and automated systems, the higher is the risk of misuse or leakage.
Even if your insurer’s AI tool rejects your health insurance claim, they still owe you an explanation. Here is what you can do:
You are entitled to a clear written reason why your claim is rejected or partly paid.
You can send a letter of appeal to your insurance company to reconsider your rejected claim.
If unsatisfied, you can escalate the issue to the insurer’s grievance officer, or even to the IRDAI’s Grievance Cell of Consumer Affairs.
You can also reach out to the Insurance Ombudsman for claim assistance if your insurer rejects your appeal.
Here are a few ways to get your health insurance claim approved faster:
Be Honest During Policy Purchase: Disclose all pre-existing conditions at the time of policy purchase. Non-disclosure can be easily detected through AI, leading to rejection of claims.
Read the Policy Documents Carefully Before Buying: Before buying your policy, check your policy document for room rent limits, disease-wise sub-limits, exclusions, co-payment clauses, waiting periods and other terms and conditions. Doing so can help prevent claim rejections.
Keep a Soft Copy of Your Claim Documents: Store scanned copies of claim documents, including test reports, doctor prescriptions and bills. Ask your doctor to write clearly or provide typed summaries to help AI read easily and avoid errors.
Prefer Network Hospitals: Cashless claims at network hospitals are more streamlined than at non-network hospitals, leading to faster processing.
Ask for Reasons for Claim Rejection: If your claim is rejected or your claim amount is reduced, request the insurer for the exact reason or specific clause for the decision. You can also insist on a human review if something looks wrong.
As the use of AI becomes more structured and more hospitals go digital, there is a high chance of a larger number of routine claims getting approved with little or no human involvement. This can lead to faster cashless approvals, smarter claim status updates and easier fraud detection. The claim processing will become more transparent and premiums may decrease.
However, questions about accountability for claim rejections may rise more often. People may question who is responsible when an AI decision is wrong. After all, it is a tool.
As a customer, you can only try to make the right decision while buying medical insurance. Make sure to compare different health insurance plans online at insurance broker websites to find the best plan as per your health needs and budget. Also, make sure to read the policy terms carefully before buying and declare any pre-existing diseases truthfully on the proposal form.
The integration of AI into health insurance has led to faster claim approvals, greater transparency and easier fraud detection. However, it is not as simple as it sounds. Delays in processing complex or unusual claims, rejecting claims based on past claim decision bias, errors in reading documents, lack of ownership and risks to data privacy are major challenges posed by AI.
Hence, policyholders need to be prepared to ask questions without hesitation and, if needed, escalate the matter if they feel their claim has been wrongfully rejected or the claim amount has been unfairly low.