AIoT Reshapes Insurance: A New Era of Smart Underwriting, Claims, and Fraud Prevention

The Rise of AI and IoT (AIoT): Redefining the Insurance Industry

With the rapid development of Artificial Intelligence (AI) and the Internet of Things (IoT), Taiwan's insurance and healthcare industries are embracing new opportunities for digital transformation. Traditional underwriting and claims processes have long relied on manual review, which is cumbersome and inefficient. Insurance fraud also poses significant financial losses for the industry. Today, the application of AIoT not only enhances the automation and accuracy of underwriting and claims but also brings forth new business models, such as dynamic pricing, preventive insurance, and real-time claims. For Taiwan's information service providers, this is a critical moment to enter the smart insurance market.

AIoT Applications in Underwriting and Claims

In underwriting, AIoT, combined with wearable devices and health data platforms, can instantly analyze an insured person's health records, medical history, and risk factors. For example, Swiss Re's Life Guide Scout integrates health data through large language models (LLM) to help underwriters quickly assess risks, reducing manual review time. Such AI underwriting assistants can provide real-time recommendations, improving underwriting accuracy, and continuously optimize risk assessment mechanisms through data training.

The claims side benefits from breakthroughs in deep learning and image recognition technology. AI can automatically review claims applications, using image recognition technology to interpret medical documents and accident photos. For example, US startup insurer Lemonade uses an AI-powered automated claims system, allowing 40% of cases to be reviewed and paid within seconds. Furthermore, generative AI can automatically produce claims reports, helping specialists quickly review them and improve work efficiency.

AIoT Enhanced Risk Assessment and Fraud Detection

AIoT applications in risk assessment enable insurance companies to more accurately predict the health risks of insured individuals. For instance, Cathay Life introduced an AI predictive model that can assess the probability of policyholders being hospitalized or undergoing surgery within the next 8–10 years, with an accuracy of 70%. Additionally, AIoT can collect real-time health data through wearable devices (e.g., smart bracelets, blood pressure monitors), allowing insurance companies to conduct dynamic risk assessments and even adjust premiums based on healthy behaviors, thereby enhancing policy personalization.

In fraud detection, AI uses correlation analysis and image recognition technology to instantly identify abnormal claims. According to an Allianz Group report, AI-modified insurance fraud cases have increased by 300% in recent years, indicating a growing problem with forged medical documents and exaggerated losses. To address this challenge, insurance companies are adopting AI-driven image detection systems, such as the technology developed by German startup Vaarhaft, which can quickly determine if claims photos have been AI-forged or modified and flag suspicious areas for further review. Taiwan's Cathay Financial Holdings also partnered with Graphen AI to build a claims fraud relationship graph, using AI to instantly analyze suspicious cases and improve investigation efficiency.

AIoT Empowers New Smart Insurance Business Models

With the development of AIoT technology, the insurance industry is shifting from a "claims-oriented" to a "risk management-oriented" approach, fostering several innovative business models:

Usage-Based Insurance (UBI)

AIoT transforms insurance pricing from static to dynamic, adjusting rates in real-time based on the insured's behavior. For example, Allstate's Drivewise program in the US collects driving behavior data through in-car devices, with AI assessing risk and adjusting premiums. The same concept can be applied to health insurance; for instance, monitoring exercise levels and heart rate via smart bracelets allows good health habits to reduce premiums, forming a "Pay How You Live" model that encourages healthy behaviors and reduces claims risks.

Preventive Insurance

AIoT allows insurance companies to become partners in proactive health management, rather than just payers after an incident. For example, Taiwan Life partnered with Canada's Lydia AI to assess individual risks through AI health scores and provide personalized health advice. In the future, insurers can further integrate health data, proactively remind clients to undergo screenings or preventive treatments, and even offer health management incentives to reduce long-term medical costs.

Real-time Claims and Microinsurance

The combination of AIoT and blockchain technology can enable automated, real-time claims. For instance, flight delay insurance can use AI to monitor flight information, and when a delay occurs, the system automatically processes the payout without manual application. Such low-threshold, high-frequency microinsurance will attract more young consumers.

Challenges and Response Strategies

Despite the many innovations AIoT brings to the insurance industry, several key challenges remain to be overcome:

Data Privacy and Regulatory Compliance

AIoT requires handling large amounts of personal health data, making privacy protection crucial. Insurance companies need to establish transparent data usage policies and adopt techniques such as de-identification and encrypted storage to mitigate risks.

AI Decision Transparency and Fairness

The decision-making mechanisms of AI underwriting and claims need to be explainable to avoid discriminatory pricing or unfair treatment. For example, Cathay Life states that AI risk assessment is only for reference, with the final decision still made by manual review to ensure fairness.

Technology Integration and Cost Considerations

Many insurers have traditional IT architectures, and adopting AIoT requires considering technological compatibility and costs. It is recommended to start with pilot projects, such as implementing an AI claims system first, and then gradually expanding the application scope once effectiveness is proven.

Talent and Organizational Transformation

AI may impact the division of roles in existing positions. Insurers need to train employees to adapt to the AIoT environment; for example, underwriters need data analysis skills to collaborate with AI systems and improve decision quality.

Conclusion: AIoT Leads Insurance Industry Upgrade

AIoT is driving the insurance industry's shift from a passive claims model to proactive health management, bringing more personalized and real-time insurance services. Through smart underwriting, dynamic pricing, and AI fraud detection technologies, insurance companies can not only enhance operational efficiency but also build closer customer relationships. Taiwanese information service providers can leverage this opportunity to develop professional AIoT solutions, assist the insurance industry's digital transformation, and secure a place in the global smart insurance market. In the future, with the integration of AIoT with blockchain and big data analytics, the insurance industry will further move towards intelligence and automation, ushering in a new era of InsurTech.