By Rahul M. Mishra
While advancements in technology continue to aid businesses in their daily operations, they have also presented an opportunity to fraudsters who deploy new ways to scam people. Akin to other sectors, the insurance industry, too, has become a hunting ground for fraudsters. Today, insurance firms consistently find themselves battling persistent issues like false claims, identity theft, etc. As one of the world’s most data-intensive industries, with billions of premiums handled each year, there is an enormous demand for fraud detection and prevention.
Artificial intelligence has emerged as a useful tool for detecting and averting fraud in recent years. Its unmatched capacity for processing data has made it an essential part of fraud detection software for all insurers. According to the Precedence Research analysis, the worldwide artificial intelligence insurance market is expected to increase at a CAGR of 33.06% from 2023 to 2032, with a projected revenue of around USD 79.86 billion. These figures demonstrate how AI is expected to become a cutting-edge technology in the evolving insurance sector.
Role of AI in Fraud Detection
There are various ways by which AI helps insurance industries to detect fraud. Here’s a look at some of them:
Data Analytics
- Insurance companies can manage huge amounts of data efficiently by utilising data analytics. By employing the analysis of data from several sources, artificial intelligence can identify patterns, trends, and irregularities that may indicate fraudulent activity.
- Insurance companies can generate valuable insights from data analytics by employing AI in their approaches. This then helps insurers identify high-risk areas, understand the fraud reasons and create focused strategies to lower the risks.
Case Management
- Artificial intelligence improves case management by automating the processes of fraud investigations. It further helps in automatically allocating cases to investigators, prioritising high-risk cases, and tracking the status of investigations. This simplified system guarantees that fraud cases are processed swiftly and effectively.
- Artificial intelligence-driven case management solutions improve communication and interaction among investigators, claims adjusters, and other stakeholders. These systems offer a centralised platform for exchanging information, tracking case changes and coordinating actions.
Identifying Patterns
- AI specialises in detecting patterns and deviations in massive datasets. It can detect unusual trends in earlier claims data, which may imply fraudulent activity. For example, AI can detect unusual claim frequencies, discrepancies in claim information and relationships between allegedly distinct claims. With improved pattern recognition, insurers can flag probable fraud situations for additional examination.
- Systems with artificial intelligence are always learning from new information, making them extremely adaptable to respond towards changing fraud strategies. As fraudsters create new frauds, AI systems improve their algorithms to detect emerging tendencies. This continuous learning capacity guarantees that insurers keep ahead of fraud trends while maintaining strong detection skills.
Predictive Analysis
- Artificial intelligence utilises predictive analysis to determine the risk of fraud based on past data and behavioural trends. It can forecast the likelihood of fraud for every new claim by analysing characteristics like claim history, policyholder behaviour and external data sources. This predictive capability allows insurers to prioritise high-risk claims for in-depth examination while optimising resource allocation and decreasing fraud-related losses.
- Predictive analytics also allow insurers to implement proactive steps to avoid fraud beforehand. By identifying and monitoring high-risk policyholders, insurers can conduct targeted actions like additional verification processes or enhanced inspections.
Real-time Monitoring
- AI-driven real-time monitoring systems can analyse claims data as it arrives, allowing insurers to detect and respond to fraudulent activity right away. Furthermore, it lowers the likelihood of paying out false claims while increasing overall operational efficiency.
- These real-time monitoring systems may create dynamic warnings in response to specified criteria and changing fraud tendencies. These notifications tell investigators about probable fraud instances while allowing them to take rapid action.
Claim Validation
- AI facilitates claim validation by automating the verification of the information. It helps systems cross-check claim information against other data sources, including medical records, police reports, and repair estimates, to verify correctness and consistency.
- Validation systems, with the help of AI, guarantee that all claims are processed uniformly and following regulatory guidelines. Moreover, these systems might include compliance checks and validations to ensure that all processes and transactions follow industry standards. As a result, consistent and compliant claim validation enables insurers to avoid penalties and preserve a favourable reputation.
AI may assist in the aforementioned ways to improve customer happiness, earnings, and fraud reduction, as well as in effectively managing time and operational complexity. Additionally, with an appropriate combination of AI solutions, training, and technology, insurers can gain a competitive advantage while improving customer satisfaction and trust.
The author is co-founder and Director, Policy Ensure
Disclaimer: Views expressed are personal and do not reflect the official position or policy of Financial Express Online. Reproducing this content without permission is prohibited.
