Redefining What’s Possible with Intelligent Innovation

Bajaj Finserv Health (BFHL) is redefining what’s possible in India’s health-tech landscape. In just six years, this trailblazer has harnessed the power of AI to transform outpatient claims and fraud detection, and is now boldly advancing AI adoption for inpatient claims as well. By pioneering intelligent solutions, BFHL is not just processing health insurance claims—it’s setting new standards for innovation, trust, and impact across the industry. In India, Third Party Administrators and insurers adjudicate claims using scanned hospital bills and Schedule of Charges (SOCs) documents. Adjudicators must manually match invoice line items to non-standardized SOCs, which vary by hospital, room category, treatment level, and package—making the process slow, error prone, and difficult to scale. The manual, paper-based matching of hospital invoices to SOCs leads to frequent tariff errors, causing overpayments across the industry—an estimated 5% leakage, or `3,800 crore ($420M) annually. For Bajaj Health alone, this represents a $40M opportunity. With digital claim exchanges still limited, such manual workflows will persist for years. BFHL recognized this as a critical industry challenge and partnered with Microsoft to build a scalable, AI driven solution. 

BFHL adopted an “AI-first” approach and partnered with Microsoft’s Industry Solution Engineering team, forming a joint task force of engineers and insurance SMEs. They designed AI agents to read, interpret, and validate digitized claim documents against SOC data, with outcome-driven workflows where agents handle repetitive matching, while human experts manage exceptions. The teams built hypotheses, validation datasets, data pipelines, and APIs to seamlessly integrate this AI-driven pipelines into BFHL’s existing claims workflow engine.

The solution digitizes thousands of SOCs and stores them in elastic, while invoices are digitized during claims processing. An intelligent search maps invoice line items to SOC entries and flags mismatches for adjudicators through a user-friendly UI. A feedback mechanism via UI allows the modelling team to capture corrections and improve their extraction and matching rates. Using Azure Foundry, the team built a strong ground truth data and continuous improvements in extraction, the team achieved nearly 80% line-item matching accuracy.

Initial SOC digitization and automated line-item matching show a 25% improvement in paying accurately and a 30% reduction in processing time. With ongoing model learning, this will deliver major time and cost savings and offers a reusable architecture for future BFHL workflows.

As Bajaj Finserv Health forges ahead, it stands as a beacon of what’s possible when technology and purpose unite. By embracing AI not just as a tool, but as a catalyst for positive change, BFHL is empowering people, transforming lives, and setting a new benchmark for the entire industry

“Our partnership with Microsoft has helped us turn a very difficult industry problem into a scalable AI-driven capability. As we take this live, I am confident we will improve our ‘paying right’ approach by 30 40% while empowering our teams to focus on higher-value decisions rather than manual checks. This is a foundational step in how we intend to solve the toughest challenges in insurance going forward.”

Devang Mody
Managing Director & Chief Executive Officer