Star Health and Allied Insurance is accelerating its adoption of Artificial Intelligence to combat an estimated 30% fraud rate in industry claims. The insurer, which reported a 25% rise in net profit to ₹550 crore in Q1 FY2027, has partnered with Amplify Health to automate and secure its claims processing. This move is designed to improve operational efficiency, though it brings new challenges regarding data security and the accuracy of AI models.
Star Health and Allied Insurance is stepping up its use of artificial intelligence to address a significant industry challenge: fraud, waste, and abuse. The insurer estimates that roughly 25-30% of health insurance claims across the sector are impacted by fraudulent activity. To counter this, the company has begun deploying advanced AI tools to detect anomalies, process claims faster, and improve its risk assessment capabilities.
In June 2026, the company entered a three-year partnership with Amplify Health to install a new claims intelligence platform. The primary goal is to automate the processing of over 50% of its cashless claims using AI within the next two years. By integrating directly with network hospitals, the company aims to facilitate a faster exchange of medical data, allowing for quicker approvals and reducing the time patients spend waiting during hospitalizations.
Investors are closely watching these technology investments, as the company seeks to balance digital growth with better profit margins. In its recently reported results for the first quarter of the 2027 financial year, Star Health showed a 25% year-on-year rise in net profit to ₹550 crore. Underwriting profit—a key measure of the core insurance business—climbed to ₹111 crore, a significant improvement from ₹16 crore in the same quarter last year.
The push toward digital adoption is visible across the company's operations, with 70% of new business now coming through digital channels. The insurer has also introduced a face-scan feature that provides customers with an immediate health indication. However, the company clarified that this specific tool is for informational purposes only and is not currently used for underwriting or final customer onboarding.
While this digital shift offers efficiency, it also introduces specific operational risks. The lack of standardized medical billing documents from hospitals can make it difficult for AI systems to process claims perfectly without manual intervention. Furthermore, relying heavily on technology requires robust data security measures to protect sensitive customer information. Investors may track whether the company's AI models can accurately distinguish between legitimate complex medical cases and fraudulent claims, as human oversight remains critical for high-value or complicated approvals.
The next important update for shareholders will be the company’s ability to scale this AI-led claims model and whether it can maintain its improved profit margins while navigating stiff competition in the Indian health insurance market.