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Health insurance claims are evolving from a traditional back-office administrative function into a vital component of digital healthcare infrastructure.
According to Dhruv Rastogi, chief AI officer, Medi Assist, artificial intelligence (AI) is transforming healthcare insurance by making claims processing faster, more accurate, transparent and scalable. Traditionally, claims assessment depended heavily on manual reviews of medical records, policy documents and supporting evidence. This often resulted in longer turnaround times, inconsistent decision-making and administrative inefficiencies. Today, AI-powered intelligent document processing, predictive analytics and large language models are helping healthcare administrators interpret medical documents faster, extract relevant clinical information, validate policy coverage and support more consistent claims adjudication.
Across the industry, AI is improving claims accuracy by reducing manual inconsistencies and enabling evidence-based decision-making at scale. AI can also prioritise claims based on complexity, route cases to the appropriate teams and allow administrators to focus on exceptions and complex cases.
Also, AI is equally important in strengthening financial integrity across the healthcare ecosystem. Modern machine learning models can analyse millions of claims to identify anomalous billing patterns, duplicate submissions, unusual provider behaviour and emerging fraud trends that traditional rule-based systems may miss. This enables organisations to proactively address fraud, waste, abuse and operational leakages, while ensuring genuine policyholders continue to receive seamless service. As healthcare transactions grow in volume and complexity, AI-driven intelligence will become increasingly important in balancing efficiency, accuracy and trust, Rastogi told Pharmabiz.
Claims represent one of the richest sources of healthcare data, connecting hospitals, insurers, providers and patients. When AI-enabled claims' systems are integrated with digital health records and connected care platforms, they reduce administrative bottlenecks, improve coordination and create a more responsive, patient-centric healthcare ecosystem, he said.
Transparency for members is equally important. Faster processing must be accompanied by clearer visibility into claim outcomes, expected timelines, policy deductions and pending requirements. Our AI-powered intelligent document processing has enabled over 40% of cashless pre-authorisation requests to be processed within five minutes, demonstrating how automation can improve speed without compromising accuracy, he stated.
The next phase of AI in healthcare insurance is moving beyond automation to orchestrate the entire patient journey from hospital admission through claims settlement and discharge. AI-powered bill estimation and out-of-pocket prediction models are helping reduce post-discharge waiting times. At Medi Assist, this capability with Raksha Prime has enabled up to 20% of eligible patients to leave the hospital even before the final bill is generated, delivering a faster cashless discharge experience across more than 6,000 network hospitals and reducing waiting times of three to six hours to under a minute, he said.
Looking ahead, Generative AI, multimodal AI and autonomous AI agents will enable more proactive, personalised and predictive healthcare experiences. Their success, however, will depend on responsible AI governance, human oversight, transparency and strong data privacy practices ensuring technology continues to advance both operational excellence and patient trust, said Rastogi.
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