Between Microsoft’s ChatGPT and Tesla’s self-driving technology, AI is beginning to capture the public imagination with its advanced capabilities. As a result, AI innovation is transforming industries everywhere — including claims and insurance. While claims automation AI can’t parallel park for you, it can streamline existing claims processes and reduce the time it takes to validate, adjudicate, and subrogate claims.

What Does Claims Automation Software Do?

Claims automation refers to the process of automating manual tasks involved in processing claims. This often includes things like data entry, document processing, and communication. Claims automation software can be programmed to handle these tasks automatically, freeing up adjusters to focus on more complex tasks and projects.

Moving Toward Artificial Intelligence in Claims Automation

Claims automation AI takes this process up a notch. It integrates artificial intelligence and machine learning algorithms to automate and accelerate the claims management process. Innovation in this field means AI can now analyze and interpret data and identify patterns. It can even make decisions based on predefined rules and criteria.

AI-based or AI-enabled systems can process and analyze large volumes of data much faster and more accurately than humans. And many insurance companies, TPAs, big businesses, and healthcare organizations are choosing to lean into the trend toward AI. Some examples of how AI is being integrated into claims automation right now include:

  • Predictive analytics. Predictive analytics uses advanced statistical algorithms to make accurate predictions about future events or behaviors by analyzing massive quantities of data.
  • Chatbots and virtual assistants. Chatbots and virtual assistants provide users with engaging and interactive experiences by simulating human-like conversations.
  • Image and video-recognition technology. This technology analyzes visual data to identify patterns and detect anomalies, helping companies provide a more seamless experience for claimants. For example, this means that people can upload images or videos relating to their claim, and they don’t have to sit for long periods while waiting for an adjuster to make contact.
  • Natural language processing. NLP allows machines to interpret and generate human language. Insurers already use this technology to automate tasks like claims processing and underwriting.
  • Fraud detection technology. Fraud detection uses machine learning to help insurers and TPAs quickly identify and prevent fraudulent claims.

Seven Benefits of Claims Automation AI

AI algorithms offer speed and accuracy, which can improve reporting, prevent losses, and even enhance claimant satisfaction. Here are seven specific benefits you can expect from integrating AI in claims automation:

  1. Enhanced speed. AI automates time-consuming manual tasks, which allows companies to process claims faster. Faster claims processing often means improved customer satisfaction, reduced costs, and a better bottom line — all of which can lead to a competitive advantage in the industry.
  2. Claims validation. By analyzing large amounts of data and identifying patterns associated with fraud or errors, AI leads to a more accurate and efficient process to validate claims. This can result in cost savings for both the insured and the insurer – and better outcomes for claimants.
  3. Reporting assistance. AI can generate accurate and timely reports on claims data with insights into adjuster performance and the claims lifecycle. This helps companies make fast, data-driven decisions to improve their claims process.
  4. Advanced fraud detection. Claims automation AI can analyze various data sources — including claimant information, historical claims data, and external sources — to identify patterns and abnormalities that could indicate fraud. By leveraging AI, companies can quickly flag suspicious behavior and assign employees to investigate.
  5. Accurate prioritization. AI uses algorithms to assess the severity and complexity of each claim. By quickly prioritizing and categorizing claims, AI can route complex claims to experienced adjusters. It also can quickly identify potential problems that require immediate attention or action. This can increase productivity, reduce workloads, and increase customer satisfaction.
  6. Enhanced subrogation of claims. AI quickly identifies liable parties and starts facilitating the recovery of losses. This improves the accuracy and speed of the overall subrogation process and frees adjusters to focus on other areas of their jobs.
  7. Fast adjudication. Claims automation AI can enhance the adjudication process of evaluating a claim, determining its eligibility, and resolving any issues by quickly analyzing data to ensure that payments are made accurately and efficiently.

Understanding When AI in Claims Automation is Appropriate

AI is a powerful tool for claims automation, but it isn’t suitable for every situation. It is particularly useful for automating routine or repetitive tasks like data entry and claims processing. AI can quickly and accurately analyze large data sets to identify patterns and irregularities.

However, the claims process may involve multiple complex decisions requiring human judgment and influence — in these cases, AI is inappropriate. AI also isn’t appropriate for situations when empathy and sympathy are needed. Additionally, if the data or information is biased, inaccurate, or incomplete, then AI tools cannot produce accurate results. This is why many believe the best option is to use a hybrid approach combining human skills with AI functionalities to achieve optimal results.

Improving Claims Experience, Customer Retention, and Closing Rates

Claims automation AI is a game-changer when it comes to improving the claims experience for customers and claimants. This technology streamlines the claims process to close claims quickly, fairly, and accurately.

People can file a claim online, and the system can quickly assess its validity and even flag potentially fraudulent claims for further investigation. This results in faster and more accurate claims processing, which shortens the claims lifecycle. Automating as much as possible also means that adjusters have more time to engage, empathize, and sympathize with claimants, ultimately improving that person’s overall experience.

On the back end, AI-enhanced claims automation has the power to identify patterns in adjuster performance and overall claims-handling efficiency and areas in need of improvement. By analyzing customer feedback – for example — AI tools can help companies pinpoint and address specific customer pain points promptly. Claims automation AI is likely to lead to higher customer satisfaction rates, higher customer retention rates – and lower costs.

For a deeper look at improving efficiency, download our e-book, Claim Success: Achieving Excellence in Claims Management – and check out Riskonnect’s Claims Administration software.