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Blog | May 3, 2024

How To Apply Generative AI in Insurance Claims Processing

AI in Insurance Claims Processing
Table of Contents

A Walkthrough for Streamlining Claims Intelligently

We’re going to walk you through streamlining insurance claims processing with artificial intelligence (AI) and intelligent automation (IA) working together. We’re also going to explore the potential of leveraging generative AI in the insurance space. Specifically, we’ll look at how SS&C Blue Prism’s IA works with gen AI to speed up claims management processes while ensuring the right security guardrails are in place.

Below, we’ll take you through the steps of automating the claims experience.

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How Do You Use AI in Insurance Claims?

IA combines AI with robotic process automation (RPA), machine learning (ML) and business process management (BPM) to automate end-to-end business processes. You can add generative AI, which acts as a further enabler to get work done faster and smarter.

Let’s start with the challenge: How can we process faster claims while maintaining accuracy?

Firstly, IA automates repetitive, manual tasks so your agents don’t have to sift through mountains of paperwork; they can focus on serving your customers and providing them with personalized offerings. Claims process automation reduces the risk of errors. It also reduces bottlenecks and inefficiencies because IA can handle large volumes of data across various sources, bringing it into a single source of truth.

What can be automated with AI in claims?

In traditional manual processing, when a claim is filed, the system creates a mountain of tasks for adjusters to review. Adjusters then need to manually search for missing information across different systems, tediously reviewing long accident declarations for key details. They then have to manually summarize and enter those declarations into a claims management application. This is incredibly time-consuming and mistakes are easy to miss. That leads to more delays, creates unhappy customers and it’s a poor experience for your adjusters.

But we have some good news: This can all be automated. Let’s fix it with intelligent automation and generative AI.

What can Automated with AI in Claims

How is AI used in claims management?

IA gives you a tireless digital worker, available 24/7. The digital worker can save your adjusters valuable time by automatically accessing government applications to find missing information. This is all done securely and within your compliance requirements, providing a detailed audit trail of all activity along with fully encrypted login credentials.

AI Used in Claims Management

Now, gen AI steps in as your intelligent reading machine. It can:

  1. Review lengthy accident declarations in seconds.
  2. Extract key details with incredible accuracy.
  3. Summarize the information.
  4. Populate the data directly into your claims management system.

An automated claims management system speeds up the first notice of loss (FNOL) data input and communications process compared with doing the same manually. It enables your digital worker to automate the most manual elements in the process of creating a new claim, including:

  • Inputting customer policy and claim data.
  • Extracting documents and images from communications channels (e.g., email, SMS, etc.)
  • Inputting documents and images into the system.
  • Checking and confirming data accuracy.
  • Notifying customers of their claim status.
AI in Insurance Claims

How AI Helps in Claims

By integrating gen AI into your IA processes, you can further streamline the processing of your insurance claims. As the insurance industry continues to evolve, embracing AI-based solutions with your IA can help you achieve better outcomes for your insurance company, your policyholders and your adjusters.

Right away, you can see the benefits of connecting IA with gen AI:

  • Faster processing: Reducing 20 minutes from each claim processing time.
  • Accurate claims: Eliminating manual errors and ensuring consistency across all claims.
  • Decision-making insights: Providing real-time insights into claims data for better tracking and visibility.
  • Happier customers: Resolving claims faster to improve customer satisfaction.
  • Empowered adjusters: Freeing your people from repetitive claims handling tasks so they can focus on complex cases and customer service.

How Is AI Used in the Insurance Industry?

This powerful combination of IA and generative AI is the future of insurance automation. Let’s look at some specific use cases in insurance where you can apply IA with other AI technologies for better results.

Claims management

For a customer who has just been in a car accident or whose home has been damaged, the initial process of filing an insurance claim is a huge deal for their relationship with the insurance provider. Getting the claim sorted quickly and accurately is key to keeping the customer happy. But here’s the problem: The traditional way of handling claims can be slow and confusing, leaving the customer frustrated and waiting.

IA can handle these repetitive tasks and speed up processing by rating claims for potential issues like fraud, so low-risk claims can sail through automatically while the tricky ones get flagged for a closer look. AI models can even give reasons why a claim was denied, making it easier for analysts to resolve issues quickly or for investigators to know what to focus on. This isn’t just good for the company; customers benefit too, because they get feedback on what’s wrong with their claim and how to fix it so they can get paid faster.


FNOL documents are varied and often unstructured. Tools like intelligent document processing (IDP) or document automation can read these unstructured documents, whether handwritten, images, receipts, etc., collate that data into a centralized space and route it to the appropriate individuals. This allows you to process complex data faster, which empowers your people with easier decision-making.

You can also integrate internet of things (IoT) or telematics functionalities to notify insurers right away of a possible property or auto claim. Adding AI chatbots into the mix can cut down on the boring administrative work, making it easier to report and gather the first bit of information needed. And with mobile apps and texting, you can set up automated chats with both claimants and insured individuals, making it more convenient for them to ask simple, routine questions and get an immediate response.

Investigation and coverage

When it comes to checking out claims and figuring out what’s covered, AI should speed things up. With optical character recognition (OCR), handwritten documents like those from the police or the doctor’s office can be auto-read and sorted, leaving the claims handler with more time to focus on figuring out damages, who’s at fault and what’s covered.

AI can also be used to verify images of car damage, as an example, to ensure the photos have not been altered or doctored to create a false claim.

With further technologies like computer vision and smart drones, looking at pictures and videos can help speed up investigations by giving damage estimates in a more organized way. Plus, detailed analytics and predictions make it easier to catch fraudsters faster and more effectively by spotting suspicious activity sooner. Humans might overlook a flaw, but digital workers can meticulously pinpoint issues and mark it as a red flag.

Valuation and payment

Insurers are often sharing data to tackle fraud. AI can be used to analyze large amounts of data and derive insights to inform premiums, claim payouts, etc. It keeps track of transactions as they happen and automates things when certain situations pop up, giving your people quick estimates without having to lift a finger.

Plus, it’s handy for sorting out payment preferences. If you need to make payment arrangements, chatbots and texting can lend a hand while advanced analytics help by matching up policy checks and working out payment amounts.

Fraud detection

Gen AI can analyze large volumes of data from various sources to identify patterns and anomalies that might indicate fraud. IA processes can then sift through this data efficiently, flagging suspicious claims for further investigation.

Gen AI can also generate predictive models to forecast the likelihood of fraud based on historical data and trends. When integrated with IA, these models can help insurers make informed decisions about which claims to investigate and prioritize those with the highest likelihood of fraud.

Are There Any Risks?

IA acts as a process wrapper for your gen AI, setting the guardrails to keep it running securely and within your predetermined compliance rules. Without IA’s protection, you can run into risks with your artificial intelligence endeavors.

When it comes to AI, there are a few risks you should plan for.

First off, you’ve got your security risks, which stem from the nature of AI systems collecting and processing sensitive personal data. There’s a chance of data leaks and compromising data integrity. And if someone gets their hands on the algorithms behind the AI, they could copy the whole system and compromise your data. Without IA backing it, your AI might not have the right controls, running risks that regulated sectors like insurance don’t want to deal with.

Then, there are the usage risks, which can come down to human error if you’re not verifying the output. Plus, if the training data fed into AI is incorrect or biased, you’re going to get bad results. Using AI without setting up a human in the loop (HITL) to verify the output – especially for critical processes – can result in unexpected and adverse outcomes. But if you set up these guardrails then AI, and gen AI specifically, can do a lot of good.

If you put solid governance in place, you can keep these risks in check. The key is aligning your tracking and assessing with your business objectives and being ready to make tweaks when needed. Testing out those changes is also important, so you know they’re doing what they’re supposed to.

How Can AI Transform Insurance Claims?

AI applies advanced analysis and logic-based techniques to interpret events, automate decisions and prompt actions – made possible with ML. The ML creates algorithms or statistical AI models to convert a series of data points into a single result. ML algorithms identify patterns in data through training and use those points to provide insights and predictions without being explicitly programmed to do so.

Your Takeaway

Claims automation with AI and gen AI can be a total game-changer, making the whole claims process better for customers and claimants. It speeds things up and sorts claims quickly and accurately.

Someone can file a claim online, and the system jumps in to figure out if it’s legitimate – without having to bring in a staff member, who’s already busy with other tasks. This means claims get processed faster and with fewer mistakes. Plus, because so much is automated, adjusters have more time to talk to people and understand what they’re going through, and that makes the customer’s experience more personal and empathy-driven.

Behind the scenes, AI-powered claims automation can spot patterns in how adjusters handle things and where they might need some help. By looking at what customers are saying, AI tools can help companies figure out any outstanding customer concerns and fix them before they escalate.

So, what’ve we learned? With claims automation AI, everyone's happier – customers stick around, your adjusters get to do more interesting work and your insurance company saves some cash. It’s a win all around!

Find out how SS&C Blue Prism intelligent automation and generative AI can take your insurance claims processes above, beyond and better than ever.

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