Using AI insurance claims to deliver fast and accurate decisions

Most of us need to get auto, homeowners, or life insurance at some point in our lives. AI for Financial Services makes it easier to get the insurance services you need. It also helps insurance companies meet the demands of a highly-regulated industry that’s becoming more tech-savvy every day. With artificial intelligence (AI) for insurance, claimants can get help faster and adjusters can simplify operations.

AI insurance tools like chatbots and virtual assistants make the insurance experience easier and more convenient. Policyholders can report claims, check claim status, and receive updates in real-time. AI also helps personalize customer experiences. It looks at customer behavior and preferences to offer tailored recommendations.

AI systems can analyze documents and media files to quickly assess claims. This allows insurers to settle simple claims quickly, reduce processing times, and standardize workflows.

Another key area where AI is useful is claims adjudication, including fraud detection and prevention. AI can reduce financial loss and keep policyholders happy. Plus, AI has a vast knowledge base and can analyze information quickly, making it helpful for:

• Automating insurance claims processing for routine tasks
• Spotting unusual patterns in claims data with pattern recognition
• Analyzing the behavior of policyholders to catch and flag inconsistencies during the process
• Cross-referencing and matching claims with historical data

AI can be used to predict future risk and loss. This helps insurers allocate resources better and set better pricing strategies. AI does this by analyzing historical data and trends.

By adding AI into workflows, not only do employees experience the benefits, but the customers do too. With AI, an enhanced customer experience is always available and personalized to fit the user’s needs.

Policyholders can connect with an AI-powered chatbot anytime, day or night, for faster resolutions to their questions or concerns. With the ability to assist multiple people simultaneously, chatbots significantly reduce wait times and keep customer satisfaction high. Even when representatives are in a different time zone, insurance claims adjusters can rely on AI tools to ensure support is always available‌ — ‌whether it’s midnight on a Sunday or any other moment when traditional service desks might be closed.

To provide the best customer support possible, AI analyzes customer data to recommend the best solutions for each customer. It can suggest the right policy or coverage options based on the customer’s needs, goals, history, or preferences. Predictive analytics helps AI anticipate customer complaints or concerns ahead of time, like upcoming policy renewals or additional coverage needs. This personalized care builds trust between the customer and the company.

Real-time claims tracking provides policyholders with peace of mind by allowing them to monitor the status of their claims in real time. AI makes this possible by sending notifications or texts with updates and expected timelines. For example, after a car accident, the driver can be easily kept up-to-date on the repair process, reducing anxiety.

AI can help human insurance claims adjusters save time by streamlining repetitive and technical tasks. This frees them up to focus on more complex, urgent, and high-priority claims. And the benefits of AI start even before intake, with proactive analysis, and continue to processing.

With AI-powered insurance software, your business can integrate automated claims intake and processing directly onto its website. AI solutions are already making a difference in insurance technology. Some existing solutions include:

• Insurtech or insurance software
• Life insurance management software
• Property and casualty insurance software
• Health claims insurance

AI simplifies the automatic claims intake process. Financial services customer service agents and policyholders can each benefit from these services. Chatbots and virtual assistants save time for both groups.

Claims triage is another area where AI can save time and effort. It can prioritize different requests based on complexity and urgency, as well as assign straightforward claims to automated systems and complicated cases to human adjusters.

Complex claims can be handled by an AI agent before being passed on to a human. This process reduces manual data entry through natural language processing (NLP). The AI agent will have already collected the user's name, account number, and details about the request. With this approach, representatives can jump straight into supporting the request when it reaches them. No time gets wasted on repeating information or asking questions

Automated decision-making and actions like policy validation and settlement proposals can be tasked to AI. For policy validation, AI can check if a claim is covered under the terms of the policy and calculate a payout. It can also generate settlement offers for routine claims.

AI can be used to analyze media, like photos and videos, to conduct a damage assessment. It will eventually be able to create an estimate for repair costs when dealing with car accidents, property damage, and more.

AI can improve the quality and accuracy of claims by enhancing customer experience and through data-driven insights. Here are a few tasks AI can handle that improve outcomes:

• Policyholder retention: AI can unify policy and claims data environments to create a single view of customer information. This is critical because most policyholders will shop for their insurance after a claim event. Using AI, insurance companies can serve the right message at the right time to help keep good customers in their book of business.
• Proactive updates: AI keeps claimants informed about their claim status through automated notifications.
• Personalized recommendations: Based on claim history and demographics, AI suggests policies or services.
• Predictive analytics: AI uses historical data to forecast claim trends.
• Risk assessment: Identifies potential risks in claims portfolio.

Insurance carriers manage a lot of data from different sources. They need to use this data to make customers happy and run their business smoothly. For example, they might use data to create personalized products or improve their operations. To do this, they need to access data from telematics, IoT, underwriting exchanges, public records, and more. They also need to analyze weather patterns, risk profiles, claims history, and rating trends.

When you know where your data stands, you can implement AI-powered analytics platforms to assess risk, segment customers, and build predictive models. This gives you a complete view of each customer. When customers call or chat, you and your partners can enhance their experience right away. You can even suggest personalized products, like home and auto bundles or usage-based insurance.

AI learns over time and refines its skills. But if the AI is trained on bad data, its output will reflect that. This can result in incomplete records and results, inconsistent formatting or responses, and claims management processing errors.

Keep your data accurate and clean with robust data validation and cleaning processes. If the data being fed to the AI system is accurate and clean, you'll have fewer issues. Internal data should be regularly checked and kept up to date. When choosing, developing, or managing the AI technology on the backend, use machine learning algorithms that can adapt to incomplete data.

AI systems are built and trained using data that’s created and interpreted by humans. As a result, the same biases that humans have can show up in ‌AI output. This is unintentional, but it’s not always easy to spot because bias can be subjective. One way to address this issue is to make sure that the data that’s used to train AI systems is unbiased. It’s also important to have human oversight to make sure that AI isn’t producing biased results. To do this, conduct regular audits of AI systems to identify and mitigate bias and use diverse datasets to train the AI system. This will help to ensure that AI tools are fair and accurate for everyone.

Insurance data is a delicate area of information that requires extra attention. The insurance industry has strict laws and regulations, as does AI. To protect policyholder information, businesses must stay up-to-date on both insurance and AI regulations. Regular compliance checks are essential, as laws in both areas change and evolve frequently. Advanced encryption and cybersecurity measures should be considered as soon as a business starts researching AI systems.

The line between AI and human collaboration is expected to blur in the future of AI insurance claims. Policyholders will enjoy personalized insurance experiences and proactive risk mitigation. Insurers should watch for emerging regulatory frameworks and opportunities for end-to-end automation.

Businesses can expect further integration with emerging technologies and trends including:

• Blockchain integrations that provide secure, untampered records of transactions
• AI-powered devices like smart watches that collect real-time data to detect potential risks before they occur
• Augmented reality that helps adjusters visualize damage or assess risks remotely
• Cloud solutions and computing enable scalable AI systems by providing storage and processing power to handle large volumes of data

AI won't replace insurance claim agents, but it can support them. AI is still in its early stages, and it's too unregulated to act alone. Human agents will always be needed to oversee, guide, and check the work of AI. Even if some processes can be automated, like training or self-service learning through documentation, a human will always need to manage the software. Developers will always be needed to update and troubleshoot the technology.

Automated systems handle straightforward claims processing or assist humans in more complicated cases. By streamlining repetitive tasks, AI allows human adjusters to focus on complex and high-stakes claims, improving overall efficiency and customer satisfaction.

According to a 2024 survey, many insurance companies adopting AI focused on piloting language learning model (LLM) technology. The study explored AI’s impact on insurance sales and underwriting, operations and claims processing, and risk control and pricing. The claims processing research specifically shows:

• Machine learning (ML), predictive analytics (PA), natural language processing (NLP) each have been adopted by 47% of respondents.
• 65% reported they are currently piloting the LLM technology.

AI insurance covers risks related to using and deploying AI systems. AI has become integral to many industries, but it's not perfect. It can make mistakes, get hacked, and even cause legal problems. For example, an AI chatbot could pull up the wrong user's information or suggest the wrong policy. AI insurance can help businesses manage these risks.