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How can Artificial Intelligence settle Insurance Claims in five minutes?

Originally published on medium.com

If you’ve ever been in the position of having to file an insurance claim, you would agree that it isn’t the most pleasant experience that you’ve likely ever encountered.

In fact, according to J.D. Power’s 2018 Insurance Customer Satisfaction Studymanaging time expectations is the key driver of satisfaction — meaning, a prompt claim settlement is still the best advertisable punch line for insurance firms. Time-to-settle satisfaction ratings were found to be 1.9 points lower even when the time frame was relatively short and insurers still missed customer timing expectations.

So what should an established insurance company do, to be at par with the customer’s desires of modern service standards? The question becomes even more pertinent when the insurance sector is still lagging behind consumer internet giants like Amazon, Uber who are creating newer levels of customer expectation. Lemonade, MetroMile and others are already taking significant market share away from traditional insurance carriers by facilitating experiences that were previously unheard of in the insurance trade.

Today, Lemonade contends that with AI, it has settled a claim in just 3 seconds! While a new era of claims settlement benchmarks are being set with AI, the industry is shifting their attitude towards embracing the real potential of intelligent technologies that can shave-off valuable time and money from the firm’s bottom-line.

How AI integrates across the Insurance Claims Life Cycle

For this entire process to materialize — from the customer filling out the claim information online, to receiving the amount in a bank account within a short amount of time, and have the entire process be completely automated without any interference, bias, or the whims of human prejudice.

How does this come about? How does a system understand large volumes of information that requires subjective, human-like interpretation?

The answer lies within the cognitive abilities of AI systems.

For some insurers the thought that readily comes to mind is — Surely, it must be quite difficult to achieve this in real-world scenarios. Well, the answer is — NO, it isn’t!

Indeed, there are numerous examples of real-world cases that have already been implemented or are presently in use. To understand how these systems work, we need to break down the entire process into multiple steps, and see how each step is using AI and then passing over the control to the next step for further processing.

How It Works
For the AI-enabled health insurance claims cycle, there are a few distinct steps in the entire process.

Analysis and abstraction

The following information is first extracted from medical documents (diagnosis reports, admission & discharge summaries etc.)

  1. Cause, manifestation, location, severity, encounter, and type of injury or disease — along with & related ICD Codes for injury or disease in textual format.
  2. CPT Codes — procedures or service performed on a patient, are also extracted.

There are in essence two different systems. The first one (described above) processes the information that is presented to it, while the other looks from the angle of genuineness of the information. The latter is the fraud detection system (Fraud, Abuse & Wastage Analyzer) that goes into critical examination of claim documents from the fraud, abuse and wastage perspective.

Fraud, Abuse & Wastage Analyzer

Insurance companies audit about 10% of their total claims. Out of which around 4–5% are found to be illegitimate. But the problem is that the results of these audit findings are available much after the claim has been settled, following which recovering back the money already paid for unsustainable claims is not that easy.

This means that companies are losing big sums on fraudulent claims. But is there a way by which insurers can sniff out fraud in real time while the claim is under processing?

With Cognitive AI technologies available today, this is achievable. All you need is a system that analyses hundreds and thousands of combinations of symptoms, diagnoses and comes up with possible suggested treatments. The suggestions are based on the learnings from past instances of cases that has been exposed to the AI system.

The suggested treatments’ tentative cost — based on the location, hospital, etc., is compared with the actual cost of the treatment. If the difference suggests an anomaly, then the case is flagged for review.

Automated processing of medical invoices

Now if your Fraud Analyzer finds no problem with a claim, how can you expedite its processing? Processing requires gathering information from all medical invoices, categorizing them into benefit buckets, and then finalizing the amount allowed under each head. Advanced systems can automate this entire process, ruling out manual intervention in most of these cases.

Recent AI systems have the capability of extracting line items from a scanned medical invoice image. This is achieved through a multistep process, outlined below.

  1. Localizing text on the medical invoice. This gives the bounding boxes around all texts.
  2. Running all localized boxes against a Scene Text Decoder trained using a LSTM and a Sequence Neural network.
  3. Applying Levenshtein Distance Correction for better accuracy.
  4. Mapping each line item against an insurer specific category.

Each line item is iterated over and looked up against the policy limits to get its upper limit. Each line item amount is aggregated to finally get the final settlement amount.

If the final settlement amount is within the limits set for straight through processing and no flags are raised by the Fraud, Abuse & Wastage Analyzer, then the claim is sent to billing for processing.

Moving Ahead With AI Enabled Claims
Today, AI transforms the insurance claims cycle with greater accuracy, speed and productivity, at a fraction of the cost (in the long run) — while delivering enhanced decision making capabilities and a superior experience in customer service. While, in the past, these innovations were overlooked and undervalued for the impact they produced — the insurers of today need to identify the proper use cases that match their organization’s needs and the significant value they can deliver to the customers of tomorrow. The cardinal rule is to — start small through feasible pilots, that will first bring lost dividends back into the organization.


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NPS in Insurance Claims: What Insurance Leaders Are Doing Differently

Claims are the moment of truth. Are you turning them into moments of loyalty?

In insurance, your app interface might win you downloads. Your pricing might drive conversions.
But it’s the claims experience that decides whether a customer stays—or leaves for good.

According to a survey by NPS Prism, promoters are 2.3 times more likely to renew their insurance policies than passives or detractors—highlighting the strong link between customer advocacy and retention.

NPS in insurance industry is a strong predictor of customer retention. Many insurers are now prioritizing NPS to improve their claims experience.

So, what are today’s high-NPS insurers doing differently? Spoiler: it’s not just about faster payouts.

We’ve worked with claims teams that had best-in-class automation—but still had low NPS. Why? Because the process felt like a black box.
Customers didn’t know where their claim stood. They weren’t sure what to do next. And when money was at stake, silence created anxiety and dissatisfaction.

Great customer experience (CX) in claims isn’t just about speed—it’s about giving customers a sense of control through clear communication and clarity.

The Traditional Claims Journey

  • Forms → Uploads → Phone calls → Waiting
  • No real-time updates
  • No guidance after claim initiation
  • Paper documents and email ping-pong

The result? Frustrated customers and overwhelmed call centers.

The CX Gap: It’s Not Just Speed—It’s Transparency

Customers don’t always expect instant decisions. What they want:

  • To know what’s happening with their claim
  • To understand what’s expected of them
  • To feel heard and supported during the process

How NPS Leaders Are Winning Loyalty with CX-Driven Claims and High NPS

Image Source: NPS Prism

1. Real-Time Status Updates

Transparency to the customer via mobile app, email, or WhatsApp—keeping them in the loop with clear milestones. 

2. Proactive Nudges

Auto-reminders, such as “upload your medical bill” or “submit police report,” help close matters much faster and avoid back-and-forth.

3. AI-Powered Document Uploads

Single-click scans with OCR + AI pull data instantly—no typing, no errors.

4. In-the-Moment Feedback Loops

Simple post-resolution surveys collect sentiment and alert on issues in real time.

For e.g., Lemonade uses emotional AI to detect customer sentiment during the claims process, enabling empathetic responses that boost satisfaction and trust.

Smart Nudges from Real-Time Journey Tracking

For a leading insurance firm, we mapped the entire in-app user journey—from buying or renewing a policy to initiating a claim or checking discounts. This helped identify exactly where users dropped off. Based on real-time activity, we triggered personalized notifications and offers—driving better engagement and claim completion rates.

Tech Enablement

  • Claims Orchestration Layer: Incorporates legacy systems, third-party tools, and front-end apps for a unified experience.
  • AI & ML Models: For document validation, fraud detection, and claim routing, sentiment analysis is used. Businesses utilizing emotional AI report a 25% increase in customer satisfaction and a 30% decrease in complaints, resulting in more personalized and empathetic interactions.
  • Self-Service Portals: Customers can check their status, update documents, and track payouts—all without making a phone call.

Business Impact

What do insurers gain from investing in CX?

A faster claim is good. But a fair, clear, and human one wins loyalty.

And companies that consistently track and act on CX metrics are better positioned to retain customers and build long-term loyalty.

At Mantra Labs, we help insurers build end-to-end, tech-enabled claims journeys that delight customers and drive operational efficiency.
From intelligent document processing to AI-led nudges, we design for empathy at scale.

Want a faster and more transparent claims experience?

Let’s design it together.
Talk to our insurance transformation team today.

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