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The Crucial Role of AI in Insurance Claims Management

August 3, 2023


Insurance claims processing is a demanding and time-consuming endeavor. Techniques such as automatic assignment and OCR-based document reading have helped streamline the process, but they no longer enable insurers to effectively minimize claims impact or loss ratio. It is no longer sufficient for insurers to rely on human processing, data analytics, or both combined to make critical decisions in various areas involved in claims management.

Moreover, customer centricity was not always at the forefront of priorities in the insurance industry. But now, with changing customer dynamics, providing exceptional customer experience is no longer optional. With the help of AI, today’s insurance firms are redefining customer offerings by delivering valuable products, enhancing underwriting processes for accuracy, and streamlining claims management for improved efficiency.

AI in the insurance industry has been a game-changing technology that presents insurers with remarkable opportunities for faster and more dependable decision-making, with reduced or minimal human intervention.

The Rise of AI in Claims Management

Post-Covid, organizations worldwide accelerated digitization and embraced the use of AI in their business processes, leveraging efficiency benefits and enhanced capabilities that AI systems have to offer.

In the claims lifecycle, AI systems can support people-oriented tasks and enhance capabilities through technologies such as generative AI and image processing automation. These technologies can interact with adjusters, claimants, claim handlers, and third-party systems/representatives in a way humans do.

AI-powered solutions enable insurers to streamline and automate processes in the end-to-end lifecycle of claims management, resulting in faster and more accurate claim settlements. This presents a unique opportunity for the insurer to position customer experience at the center of every business decision.

AI in Customer Experience

AI-powered Automation for Claims Handling

AI can be leveraged to automate business rules that can effectively filter and process the simple steps required for accepting claims during claims registration.

Beyond the rules and validation techniques, AI-powered solutions can be put in place for the following tasks to improve claims processing speed and deliver a better customer experience:

  • Verifying policy details
  • Flagging large loss claims
  • Assigning claims handler/adjuster based on traits observed in large loss claims handling
  • Assigning surveyor based on expertise/claims handling efficiency, customer desirability score, and not just by location proximity

Accurate Fraud Detection

The goal is to identify potential fraud with a high degree of accuracy so that the other claims can be cleared quickly while the identified cases are scrutinized further in detail. AI in claims management can enhance fraud detection by including metrics like claims frequency and policyholder claims impact, the technology can conduct exploratory analysis, offering insight into the following:

  • Flagging claims and assigning a fraud severity score, which is then routed to the adjustor for intervention
  • Qualifying claims for automated processing
  • Flagging claims for further need of documentation

Combining the high-efficiency document image processing techniques that AI offers, the claims documents can be verified, analyzed, and processed automatically. With the help of combination bots, AI in the claims function can:

  • Process claims documents automatically
  • Assign fraud scores derived from analyzing structured and unstructured data like loss details, photos, and voice
  • Assign cases with high fraud scores to the special investigation unit

Data science elevates the application of AI, leading to quicker closure of claims and efficient use of claims adjustors’ valuable time.

Enhanced Risk Assessment and Claims Prioritization

Insurers can derive litigation propensity along with large loss prediction using AI technologies. This helps them to prepare and efficiently handle high-expense claims that have the potential to incur high losses. The techniques used range from exploratory analysis and pattern identification to random forest algorithm, enabling the insurers to shift left towards risk prediction and prioritization of claims that are potentially huge settlements.

Telematics and AI in Auto Insurance Segment

Telematics has become more pervasive in the auto industry, allowing carriers to directly understand the behavior of individual drivers instead of proxying it with fleet-level variables. The telematics products range from more “traditional” telematics devices that collect driving maneuvers and location to camera systems that monitor a driver’s alertness or level of distraction. The impact of telematics has been significant in the commercial auto segment, but it has been a struggle to digest the large amounts of data that the telematics systems capture, limiting the usefulness of data and reducing the return on investment. In auto insurance, AI algorithms analyze driving data and recorded video to reconstruct the conditions surrounding a crash, enabling insurers to make faster claims settlements through efficiency and significant cost savings.

Using AI in Claims: A Few Key Points

With the increasing usage of AI in claims management, it is important to conduct quality and compliance, and leakage audits to ensure overall improvement within the guardrail. While building detection models, it’s important that the savings derived from loss prevention are balanced with the cost of false alerts. With the help of machine learning techniques, insurers can improve predictive accuracy and enable loss control units to achieve higher coverage with low false positive rates.

Monitoring tools like performance dashboards display real-time data on effectiveness, efficiency, data quality, regulatory compliance, and customer satisfaction. These are desirable features that help senior management to monitor and keep track of benefits and provide customers with a seamless, pain-free experience. That said, the target value propositions should be focused more on improving cycle time, efficiency, effectiveness, data accuracy, and the quality of the customer experience.

In Conclusion

AI technology is going to evolve and get better with time, delivering higher value with each passing day. While insurers are focusing on leveraging AI in revenue streams, it is important that the claims function is not left behind. AI in claims management has a crucial role to play in customer centricity and sustenance for insurers.

By leveraging the power of AI, insurers can streamline claims processing, enhance fraud detection, improve risk assessment, and deliver a better and faster claims experience. As the industry continues to evolve, embracing AI-driven solutions will be crucial for insurers to meet the changing demands of policyholders.

About the Author

Santhakumar Subramaniyan

Santhakumar Subramaniyan

Santhakumar Subramaniyan, Assistant Vice President with Hexaware’s Insurance Products Practice is a seasoned Insurance domain consultant adept at applying technology solutions to improve business outcomes and drive cost optimization for Insurers. He has vast experience in Solution design for digital transformation initiatives, core platform replacement/implementation, data migration and analytics program. Highly enthusiastic about adopting emerging technologies like Data Science, ML, AI to deliver business value for insurance industry clients.

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