Dr. Sanjiv Dwivedi, Head – Investigation and Loss Mitigation,

Bajaj Allianz General Insurance Co. Ltd.

The insurance business is built on the foundation of trust, wherein insurers trust that information provided by customers while buying a policy is true, and in turn, customers have faith that insurance companies will be there by their side in case of an exigency. Frauds in the insurance industry are rampant, which leads to cracks in this foundation of trust. The fraudulent cases in insurance have been on the increasing trend for the past few years which has led to the Investigation & Loss Mitigation function in companies plays a crucial role in the insurance industry to counteract these illegal activities.

The Previous and present patterns of a variety of Insurance frauds made the possibility of building the “Process of Insurance Investigation”. In early years, investigation departments in insurance companies just verified documents and incidents. To combat fraud effectively, investigators have embraced modern tools and strategies that uncover anomalies and gather accurate details previously missed by traditional methods. By adopting advanced technology, the industry is now better equipped to detect and prevent fraudulent activities, significantly reducing associated losses.

Hence, insurance claims investigations are now being used to combat fraud or inflated claims. The investigation plan should include the scope of the investigation, meet all parties involved, tasks/trigger-oriented plan of action, and their timelines.

Fraud-Specific AI and Machine Learning Capability Enhancement

The need of the hour is to launch an AI Technology Model to improve fraud detection rates, reduce the claim settlement time, minimise processing time, improve customer experience, and reduce customer grievances. The model will help to manage the indicator, do a trend analysis of each indicator, and improve the indicators periodically. The framework is coupled with automated analytics, which will aim at filtering suspicious claims for more detailed review.

Analytical techniques will help with anomaly detection, predictive modelling, text analytics, and network analysis. These methods, along with appropriate collection and transformation of data, will produce insight about suspicious cases based on previous experience, statistically anomalous behavior, and linkages between entities. Their main advantage compared to simple rules is their ability to narrow down the target group for investigation so that it includes as many fraudulent cases and as few false positives as possible.

Conclusion

A better loss prevention framework in insurance companies directly contributes to claims cost reduction and portfolio optimisation, while indirectly enabling improved services to customers. Smart business is about getting things right the first time. To support this approach, it’s essential for the insurance industry to actively foster fraud awareness across a broad ecosystem, including Academia, Industry, Bureau, Local/District/State Administrations, Social Influencers, and Customers, ensuring more informed and resilient practices.

Special emphasis should also be placed on reaching vulnerable sections of society, such as senior citizens, to enhance Fraud Awareness. Insurers should exemplify such efforts by conducting Fraud Awareness campaigns that engage diverse communities through webinars, blogs, teasers, practical guidance, and targeted content shared via social media platforms.