The Liang Insurance Fraud Case published on the official WeChat account of the People's Procuratorate of Qingdao City reveals that since 2020, certain collusion between Liang, the head of a car repair shop, Sun, the head of a car service company, and Zhao, an individual from an insurance company, has occurred. They purchased second-hand new energy vehicles of brands like Beiqi and procured collision insurance for these vehicles. Subsequently, they deliberately staged vehicle flooding accidents during heavy rain, and then instructed an assessor named Hua, arranged by Zhao, to provide false assessment reports on behalf of the insurance company.

A recent case from Pingdu Court shows that in just a few years, criminals, along with relatives, friends, and employees of auto repair shops, fabricated over 40 car accidents and fraudulently obtained over 1.5 million yuan in claims. Specifically, the defendant Wang operates an auto repair shop. Leveraging his "professional knowledge," he pre-replaces original factory parts of high-end vehicles with lower-priced aftermarket parts and then fabricates traffic accidents in remote, unmonitored locations to fraudulently obtain insurance money through false litigation or direct claims.

In the schemes of insurance fraud syndicates, not only are there fake "collision participants" and "actors," but also some repair shop technicians find themselves unable to stay away and become involved in the chain of insurance fraud.

Data released by the People's Court of Shunyi District, Beijing, indicates that from January 2019 to October 2023, the court heard 26 cases of motor vehicle insurance fraud involving 52 defendants. Among them, there were 23 cases of collusion between auto repair personnel and customers bringing their vehicles for repairs, accounting for a staggering

Analysis: Reasons for Rampant Auto Insurance Fraudce Fraud

Auto insurance becomes a hotbed for fraud due to its simple claims procedures and short payout cycles. The following reasons mainly contribute to why auto insurance fraud occurs repeatedly and becomes a prevalent phenomenon.

1. The lure of "low cost, high return" tempts fraudsters to take risks willingly. The root of the myriad of fraud schemes behind auto insurance fraud may lie in the powerful drive for profits. Some unscrupulous individuals rack their brains to design various complex scams to gain illicit wealth. Moreover, there exists a significant information asymmetry between insurance companies and policyholders, with policyholders often having a better understanding of the actual condition of the vehicle. This provides them with the opportunity to exploit this information advantage for fraud.

2. In selecting accident locations, perpetrators tend to carefully fabricate accidents on roads lacking surveillance, such as highway exits or areas near villages. They often opt for rear-end collisions, a collision form relatively easy to assign responsibility for. They exploit the absence of surveillance in these areas to conceal their illegal activities, increasing the chances of successful fraud.

3. In insurance fraud cases, after fabricating accidents, sometimes neither party will choose to report to the police but instead directly fill out a "Self-quick Handling Agreement for Road Traffic Accidents." After completing this operation, the party deemed fully responsible for the accident will report the case to the customer service hotline of their own insurance company. Subsequently, both parties will drive their vehicles to the assessment institution to determine the extent of the loss, thereby obtaining relevant documents and assessment prices issued by the insurance company. Sometimes, the accident locations they report to the insurance company are entirely fabricated. Due to the large volume of accident assessments handled by insurance companies daily, negligence and carelessness may inevitably lead to incomplete and inaccurate inspections of the damaged vehicles at the scene of the accident.

4. Due to intense competition among insurance companies, customer information is generally treated as proprietary and protected, creating insurmountable data barriers between them. Insurance companies operate relatively independently in various stages of underwriting, risk assessment, and claims processing, mainly based on the limited information they possess to make business judgments. This information asymmetry provides favorable space for fraudulent activities by unscrupulous individuals. Additionally, insurance companies often fail to adequately assess risks during underwriting and still do not perform well in key aspects such as on-site inspections and physical examinations after accidents, all of which provide ample opportunities for recurring auto insurance fraud.

Features: Challenges in Identifying Auto Insurance Fraud

Auto insurance fraud, due to its characteristic of organized groups, often involves perpetrators gathering together to commit fraud in an organized manner. There is collusion both internally and externally, with insiders from insurance companies providing "professional guidance" for insurance fraud or supplying false documentation. Furthermore, the continual evolution of insurance fraud forms makes fraudulent activities increasingly concealed and complex, making them difficult to easily detect. Additionally, methods of defrauding insurance are becoming more complex and covert. Fraudsters utilize AI technology to forge images, addresses, information, and device registration data, making it difficult for traditional security measures to confirm authenticity, necessitating the use of more advanced technology for analysis and tracing.

At the same time, due to the specific requirements of insurance claims, many cases of fraud are only discovered after claims have been settled. Furthermore, when pursuing historical cases for recovery, there is a need to face the issue of statute of limitations, posing significant challenges to recovery efforts.

Solution: Collaborative Efforts to Combat Auto Insurance Fraud

Preventing auto insurance fraud requires cooperation among insurance companies, traffic management departments, procuratorates, and other relevant agencies. By strengthening management, refining procedures, fulfilling responsibilities, improving coordination, advancing governance, and utilizing big data, a comprehensive prevention system can be established to effectively curb insurance fraud and uphold the healthy and stable development of the insurance industry.

Insurance companies need to enhance their anti-fraud capabilities:

1. Establish robust data risk control and analysis models to monitor abnormal patterns in insurance data and promptly detect signs of fraudulent behavior. Dingxiang Dinsight assists enterprises in risk assessment, anti-fraud analysis, and real-time monitoring, enhancing the efficiency and accuracy of risk control. Dinsight's average processing speed for daily risk control strategies is within 100 milliseconds, supporting the configuration and deposition of multi-party data, and leveraging mature indicators, strategies, models, and deep learning technology for risk control self-monitoring and iterative mechanisms. Paired with the Xintell intelligent model platform, which automatically optimizes security strategies for known risks and configures support for risk control strategies in different scenarios based on risk control logs and data mining potential risks. Its standardized processing, mining, and machine learning processes based on associative networks and deep learning technology provide one-stop modeling services from data processing, feature derivation, model construction to final model deployment.

2. Utilize identity verification technology to ensure the authenticity of policyholders' identities and analyze their behavioral patterns to identify abnormal activities. Dingxiang Device Fingerprinting generates unified and unique device fingerprints for each device by internally connecting information from multiple devices. By analyzing behaviors such as multiple account logins, frequent IP address changes, and frequent device attribute changes that are abnormal or inconsistent with user habits, it tracks and identifies fraudulent activities. Paired with Dingxiang's frictionless verification based on AIGC technology, it prevents threats such as brute force cracking, automated attacks, and phishing attacks, effectively preventing unauthorized access, account theft, and malicious operations, thus protecting system stability.

3. Utilize image recognition technology to analyze photos and videos in claims documents to detect possible forgery or tampering. Dingxiang's comprehensive panoramic face security threat perception solution intelligently verifies through multi-dimensional information such as device environment, facial information, image authentication, user behavior, and interaction status, quickly identifying more than 30 categories of malicious behaviors such as injection attacks, live forgery, image forgery, camera hijacking, debugging risks, memory tampering, Root/jailbreak, malicious Rom, simulator operation, etc. Upon discovering forged videos, fake facial images, or abnormal interaction behaviors, it automatically blocks operations. It also dynamically adjusts video verification strength and friendliness, achieving seamless verification for normal users and strengthening verification for abnormal users.

4. Establish cooperative mechanisms with law enforcement agencies, other insurance companies, and third-party data providers to share information and intelligence, strengthen monitoring and crackdown on fraudulent activities.

Regulatory authorities need to enhance collaborative efforts:

1. Traffic management departments should strengthen business guidance and refine accident liability determination procedures. Strengthening guidance for traffic accident assessment service centers, urging them to fulfill their duties strictly, and using appropriate accident liability determination procedures depending on the situation to lay the foundation for subsequent case handling.

2. Procuratorates should play a leading role and increase supervision over cases. Strengthen cooperation, communication, and information exchange with traffic management, control application, and other departments to discover and transfer supervision clues of insurance fraud to promote case handling, and promptly transfer issues such as law enforcement unfairness to relevant functional departments.

3. Ensure smooth execution of sentences and ensure full coverage of administrative and criminal penalties. For individuals involved in cases who do not meet the criminal filing standards, they should be lawfully transferred to administrative departments for administrative penalties to avoid law enforcement and judicial vacuums.

4. Promote enterprise compliance construction and source governance in view of the common occurrence of insurance fraud involving employees of automobile sales and service enterprises and insurance companies. Procuratorates should actively promote legal publicity and cooperation between law enforcement and enterprises.

5. In response to the concentrated fraud in the auto insurance field, develop supervision models for vehicle insurance fraud cases, establish information sharing and cooperation mechanisms, achieve data interoperability, establish an information database for insurance fraudsters, enhance automatic data screening and comparison functions, timely initiate review mechanisms, and increase analysis efforts to discover clues and promote case handling.