Illustration of an insurance service screen showing claim information, including incident type, steps, date and location of occurrence, and incident description.

What Is Insurance Claims Automation?

Insurance claims automation uses technology to expedite the claims process from submission to settlement, reducing processing times and errors.

Insurance claims automation makes the entire claims process faster and simpler. From start to finish, it handles claim intake, assessment, and payment. This results in shorter processing times and fewer errors.

Insurance claims processing through property and casualty insurance software can be time-consuming and repetitive. This is where intelligent automation (IA) comes in. IA streamlines the review process to save your company time and money. It also improves customer satisfaction by providing a seamless, transparent experience.

First Notice of Loss (FNOL) automation

This is when the policyholder or claimant files a claim with their insurer. Automating this process and data pre-filling data makes it possible for policyholders or claimants to complete FNOL online or through a convenient mobile app. This helps policyholders provide claim details soon after the incident occurs. FNOL automation significantly reduces manual data entry and processing time, ‌improving the customer experience and reducing the burden of administrative work on employees.

Automated data collection and validation

To handle claims, insurance companies need specific information. This includes images of damages, repair estimates, and medical records. With automation, insurance firms can quickly gather this data from trusted sources. However, it’s important to have safeguards in place to protect this data during the claims process.

Fraud detection and risk assessment

Insurance companies can automate the process of gathering data from across the web and insurance databases to help identify potential fraud. Claim representatives and adjusters can also use claims automation to track claims processing over time, and use insights to identify red flags for potential fraud or unusual claims patterns. For example, the system might flag a suspicious bill from a provider based on similar damages or injuries seen in the history of previous bills. This would trigger an alert and a potential assignment to a special investigative unit (SIU) team member to dig deeper. ‌By tracking and staying ahead of potential fraud, insurance companies can lower their exposure to risk. Predictive analytics in insurance helps to identify potential fraud.

It's also important to note that approximately 10% of property and casualty claims are fraudulentOpens in a new window. With claims automation, insurance firms can better triage the 90% of “good” claims for fast-track settlement or “white-glove” treatment as needed.

Claims adjudication and settlement

Automation can quickly settle and pay simple claims, keeping customers satisfied and freeing up your employees to focus on other tasks. The system automatically reviews and processes insurance claims, determines their validity, and calculates the appropriate payout amount. This streamlined process reduces manual intervention and speeds up the entire claims process, from submission to payout.

A retail banking dashboard showing a customer's profile with financial goals and upcoming tasks.

Engage your customers and employees with Financial Services Cloud.

Accelerate digital process innovation across the front, middle, and back office and put your customer at the center of everything. Unlock data and insights to build customer trust and increase employee productivity with Financial Services Cloud – a single, connected financial services AI CRM.

Automating your claims process has a multitude of benefits, including:

  • Improved accuracy: Automated data pre-fill and reduced manual work lead to fewer errors, saving your company money and resources over time.
  • Increased efficiency and productivity: Associates often feel unproductive when they’re doing the same tasks every day. Automation can free up more of your associates’ time so they can focus on more complex claims or handle customer service needs. In the insurance claims process, time is often money. The longer a claim stays open, the more expenses an insurance firm can incur. Claims automation can help shorten the claims lifecycle, which lowers costs.
  • Boosted customer satisfaction: Your customers will appreciate quicker claims processing and payout timeframes. Learn more about improving customer experience in the insurance industry.
  • Improved risk mitigation and fraud detection: Automated claims review uses machine learning (ML) to continually review patterns and flag potential issues. This allows your company to address concerns quickly before they become bigger problems. The more data the automated claims system receives, the smarter it becomes and the better it supports your business
  • Streamlined systems: Handling an insurance claim requires using many systems, especially for auto claims. For example, you need one tool to review the validity of the claim details, another to estimate vehicle damages, and yet to calculate medical bills. Automating your insurance claims management process can help connect these disparate systems, making your employees’ jobs easier and more efficient.

It’s important to understand the technology involved in insurance claims automation:

  • Robotic process automation (RPA): The system deploys system robots (bots) that handle routine, repetitive tasks within a process. For example, in the insurance industry, bots can handle tasks like filling in forms, extracting specific pieces of data, and moving files.
  • Artificial intelligence (AI): AI mimics human thinking to complete more complex tasks than RPA. Plus, AI for Financial Services can analyze vast amounts of data for improved decision-making and create personalized financial recommendations for customers.
    • Machine learning (ML): As a subtype of AI, this technology learns from previous actions and uses that knowledge to complete new tasks. Insurance companies can use ML to review claims history to identify patterns that could indicate potential fraud or process improvements.
    • Natural language processing (NLP): Another subtype of AI, this technology gives computers the power to read and understand human language. NLP can be used to adjust complex insurance claims language for different audience types. This makes insurance documents easier to understand, which can save time and money for both insurers and policyholders.
  • Optical character recognition (OCR): This technology converts documents like receipts, web pages, or handwritten notes into text that a computer can understand and use. For example, an insurance company can use OCR technology to change handwritten notes from a doctor’s visit into a text document can be used by their claims processing software.
  • Internet of Things (IoT): These are physical devices that are connected through technology. Smartwatches, which collect health data, are examples of IoT devices. This health data might be used to process medical insurance claims.

If you decide to implement automation into your claims processing, look for the following key features:

  • First Notice of Loss (FNOL): Supports claims notification and intake
  • Claim validation: Reviews the elements of the claim to ensure completeness and accuracy
  • Claim decisioning: Determines whether to approve or deny the claim
  • Claim triaging: Sorts claims by urgency, monetary value, or other factors
  • Damage estimation: Uses estimation tools or on-the-ground experts to determine the approximate cost of a repair or service
  • Claim-settlement automation: Sorts simple or straightforward claims through processing with minimal human oversight
  • Task-management automation: Moves claims processing through a specified workflow, from person to person and system to system
  • Analytics and reporting: Analyzes data to show trends over time, including claims processing timeframes, common claims types, high-touch claims, and more
  • Security and compliance: The system complies with national and federal insurance regulations, including protecting your policyholders’’ sensitive data.

With any new technology, you might run into some challenges. Automating insurance claims is no different. Here are a few challenges to consider as you explore automation options.

Fragmented data and legacy systems

Legacy systems often pull data from many different places, which can create bottlenecks in claims processing. Before you automate, check your systems for possible roadblocks. This will save you time and effort later on.

Potential legal issues

Insurance companies are subject to many federal regulations. When choosing a claims automation solution, you need to be sure it will help you meet data security, customer privacy, and data governance requirements. Research the solutions you’re considering and ask pointed questions during demo sessions. You need to feel confident that any solution you choose will help you stay compliant with regulations.

Investment and resource requirements

Implementing new technology requires ‌significant investment. You may need to hire new employees or contractors to help train your team on the new systems. Existing employees who will be using the new tools should receive comprehensive, hands-on training. In the long run, the benefits of implementing insurance claims automation will be significant. If you're seeking outside funding, be sure to have a solid business plan that demonstrates the long-term benefits of using automation.

When you're ready to dive into insurance claims automation, follow these steps:

  1. Identify strategic goals. Determine why you want to use claims automation and what you expect it to do for your business. Define measurable goals — for example, decreasing claims processing time by 20% or delivering personalized experiences to improve customer service scores by 15%.
  2. Select the right processes and workflows. Collaborate with your team to analyze your processing workflow. Find tasks that are repeatable and routine. Consider which processes could benefit from automation.
  3. Determine functional and technical requirements. Work with your IT team to figure out what software, hardware, storage, and cloud resources you need to meet your automation goals.
  4. Ensure human oversight. Understand your human-resource needs to deploy and maintain automation technologies.
  5. Choose the right software. Do your homework and shop around for the best vendor. Make sure to sit through vendor demos, such as the demo for Salesforce Financial Services Cloud, and come prepared with specific questions about your workflows‌.
  6. Start with a pilot project. Start small with a pilot project to see what works for you. You’ll have time to make adjustments along the way, and it’s the best way to avoid getting stuck in a long-term commitment that doesn’t meet your needs.
  7. Track progress. Partner with your automation systems vendor to continuously measure your progress and improve your claims processes. Keep the strategies that work, and tweak the ones that don’t.

How can my company automate insurance claims?

Insurance companies can use cutting-edge technology like artificial intelligence (AI) and machine learning (ML) to collect important data, evaluate claims, and issue payments. Automation is particularly useful for straightforward claims with frequently recurring elements. By automating claims, human employees have more time to focus on complex claims and provide outstanding customer service.

Will AI replace insurance claims processing?

Although AI isn’t ready to handle insurance claims processing all on its own, it can still help companies process claims faster, improve customer satisfaction, and reduce errors. When AI and traditional claims processing methods work together, companies can speed up the process, keep customers happy, and make fewer mistakes.

Which technologies are companies using to process insurance claims?

Companies use a multitude of technologies to process insurance claims, including:

  • Robotic process automation (RPA) deploys robots to complete predefined and repetitive tasks within a certain process, such as filling in forms, extracting specific pieces of data, or moving files.
  • Artificial intelligence (AI) mimics human thinking to complete more complicated tasks.
  • Insurance companies use machine learning (ML) to review claims patterns over time, which helps them identify needed process improvements or potential fraud.
  • Insurance companies can use natural language processing (NLP) to adjust complex claims language for various audience types.
  • An insurance company can use optical character recognition (OCR) to convert handwritten provider visit notes into a text document that their claims processing software can use.
  • In healthcare claims processing, the Internet of Things (IoT) can compile data from swartwatches, connected blood-pressure monitors, and other health-related devices.

What types of software do auto claims adjusters use?

Auto claim adjusters currently use a variety of different software to process claims. They might use one software to assess auto damage, another to collect details related to bodily injury and medical claims, and yet another to pay out claims. This can be time-consuming and frustrating for employees as they navigate multiple systems. Insurance claims automation can help connect these systems and simplify the process, saving your employees time and frustration. If you need a platform that works for insurance companies, banks, and wealth managers alike, consider Salesforce Financial Services Cloud.