How Medi Assist is Driving AI-Led Transformation in Health Benefits

Medi Assist Healthcare Services is India’s largest health benefits administrator. Founded in 2000, it has become an industry leader, managing around 25% of the country’s total health insurance premiums across the Group and Retail segments. In the complex landscape of health insurance, Medi Assist is a vital intermediary between insurance companies, policyholders (individuals and corporate employees), and healthcare providers (hospitals). Its core function is to streamline health insurance claims administration, ensuring a smoother and more efficient process for all stakeholders.

Satish Gidugu, CEO & Whole-Time Director, Medi Assist Group, is steering the company into its next phase of growth through an AI-driven, data-centric digital transformation. In an in-depth interview with CIOL, he discusses how Medi Assist is raising the bar with investments in AI-powered claims processing, predictive analytics, and user-friendly digital interfaces to enable faster, more accurate claim handling. 

Satish holds a bachelor's degree in technology (Naval Architecture) from the Indian Institute of Technology, Madras. He was previously associated with redBus (a part of MakeMyTrip ), SAP Labs India , and Intergraph Consulting. Excerpts from the interview. 

Medi Assist has seen the number of claims processed grow from 3.1 million in FY21 to 7.63 million in FY24. That’s a huge increase. Can you share what key operational and technological changes have driven this growth and how you plan to sustain this momentum?

Our journey is one of continuous innovation, driven by a vision to make healthcare more accessible, efficient, and user-centric. With our technology-centric approach and extensive network, we are revolutionizing health benefits administration and enhancing access to quality healthcare across India.

The growth in claims volume stems from our commitment to operational excellence and technological innovation. Several key changes have driven this momentum. A key driver has been our investment in AI and data digitization. In the past four years, we’ve built a vast data repository by digitizing every document we receive. This has enabled two key AI-driven solutions: first, we can now predict a policyholder’s out-of-pocket expenses even before the hospital generates the final bill—enhancing transparency and improving customer experience. Second, our AI-based fraud detection capabilities have led to a 60% improvement in fraud savings compared to last year.

To sustain this momentum, we will continue to invest in technology, further enhancing our digital platform with advanced AI and automation capabilities. 

Medical inflation is a growing concern in India. If you say that Medi Assist is making healthcare more accessible across the country, how exactly are you managing rising healthcare costs?

Medical inflation is indeed a significant challenge in India, and alarmingly, it's rising at a rate that surpasses the global average. According to recent reports, healthcare costs in India have been increasing by approximately 10-15% annually, far outpacing general inflation. This burden disproportionately affects the common man, with out-of-pocket healthcare expenses pushing many families into financial hardship. Studies show that a large percentage of Indians do not have adequate health insurance coverage, and a single hospitalization can deplete their life savings.

We play a crucial role in managing and optimizing healthcare expenditures through several key strategies:

• Negotiated Network Rates: We leverage our extensive network of healthcare providers to negotiate favorable rates for our policyholders.
• Claims Management Efficiency: Our advanced technology and streamlined processes minimize administrative overhead and reduce the potential for errors or fraud.
• Data-Driven Insights: We utilize data analytics to identify cost drivers and areas for improvement. Through data analytics, we’ve managed to bring down healthcare inflation from an industry average of 11–12% to just 5%, delivering direct savings to customers. By analyzing claims data, we can identify trends, negotiate better rates with providers, and implement cost-containment measures. Additionally, automating claims processing and policyholder enrollment has reduced administrative costs and improved turnaround times, enhancing the customer experience.
• Reducing Fraud: Fraudulent claims are a key driver of rising premiums. Our AI/ML models have improved fraud detection by 60% year-over-year, helping insurers control costs and keep premiums in check.
• Transparency and Empowerment: We provide our policyholders with clear and accessible information about their healthcare costs and benefits. By empowering them to make informed decisions, we encourage responsible healthcare utilization. 

Can you explain the ‘Borderless Health’ vision? Can you provide more insights on how Medi Assist is working towards this and what key milestones you envision in the coming years?

At our flagship Raksha Summit, in collaboration with BCG, we unveiled our transformative vision of 'Borderless Health'. This concept envisions a paradigm shift in healthcare access, aiming to provide seamless insurance coverage across India's diverse demographics – Affluent, Middle, and Emerging – and all key segments: Government-to-Citizen (G2C), Employer-to-Employee (E2E), and Business-to-Consumer (B2C).

'Borderless Health' transcends traditional insurance offerings. It's about constructing an integrated healthcare ecosystem where quality care is accessible to all, irrespective of socio-economic background or location. We're building a 'digital highway' for healthcare, enabling seamless information flow and readily available services.

A central challenge we're addressing is the development of an efficient operating model. This model must deliver tailored insurance packages and innovative care models effectively while minimizing unit costs to ensure affordability and accessibility. This challenge is particularly complex in India due to the scale of the population, the diversity of healthcare providers in terms of digital connectivity and infrastructure, and the persistent issue of fraud and abuse in some parts of the system. India’s greatest growth stories have been defined by leapfrogging technological generations—like the shift from 2G to 4G. For health insurance to achieve a similar leap, all stakeholders must embrace digital transformation, AI, and automation.

At the core of this vision is the ‘JAM Trinity’: J for joined health data to enable informed decisions, A for automation to streamline processes and reduce costs, and M for mobile-enabled access to empower policyholders. By combining these elements, we aim to create a personalized, efficient, and scalable health insurance ecosystem that ensures affordable and accessible care for all.

This is a bit of a long question, just to set the context: With data being the key, and you being a third-party administrator, can you give a sense of how this works in real-time? Healthcare providers, based on their digital maturity, may have some kind of HMS, but it’s a siloed environment since we don’t have standards like HIPAA yet (though there are conversations around the Digital Information Security in Healthcare Act). Given the accountability deficit here, how does technology work seamlessly to enhance operational efficiencies for both providers and care receivers?

Healthcare data in India remains fragmented due to the lack of universal standards like HIPAA, and the complex data ecosystem, with its multitude of providers and varying levels of digital maturity. Despite this, at Medi Assist, we’ve built a technology backbone that bridges these gaps and enhances operational efficiency for both providers and care receivers. Our platform integrates with various Hospital Management Systems (HMS) regardless of their digital maturity, using APIs and data mapping to create a unified flow of information. This allows real-time claims processing, automated pre-authorization, and faster discharge processes—reducing wait times and significantly improving the customer experience. This unified data flow not only enhances efficiency but also fosters greater accountability, as all parties have access to real-time, transparent information. Our platform adheres to stringent data security protocols, ensuring the confidentiality and integrity of patient information.

On the provider side, our AI-driven fraud detection tools identify anomalies and prevent overbilling, ensuring accurate payments and reduced operational leakages. For policyholders, predictive analytics enable cost transparency by estimating out-of-pocket expenses before the bill is generated, helping them make informed decisions. Additionally, automation in claims processing and customer service reduces turnaround times and administrative costs, improving efficiency across the board.

Fraud detection in health insurance is a major challenge. You mention that AI analyzes over 160 data points per claim—what have been the most significant findings, and how have they impacted fraud prevention and cost savings?

Fraud detection in health insurance is indeed a critical challenge, and at Medi Assist, we're leveraging the power of AI/ML to address it head-on. Our AI models analyze over 160 data points per claim, enabling us to identify subtle anomalies and flag potential fraud with remarkable accuracy.

A significant finding has been the AI's ability to predict final hospital bills even before they are compiled. By examining millions of past transactions, treatment types, and intricate policy details, the AI generates highly reliable estimates. This has dramatically streamlined the discharge process. Just last month, for instance, over 20,000 patients experienced faster discharges due to hospitals' confidence in the AI's predictions.

Beyond expediting billing, AI serves as a powerful tool for fraud prevention. Fraudulent claims are a major contributor to escalating premiums and healthcare costs. The AI assigns a fraud propensity score to each claim, analyzing complex patterns that would often escape human detection. Suspicious claims are then flagged for further scrutiny by our expert team, ensuring a rigorous and accurate review process.

The impact has been substantial. Since the launch of this AI-driven system in February, we've witnessed a doubling of fraud savings. More importantly, the AI's accuracy and efficiency continuously improve with each claim processed, further strengthening our ability to prevent fraud and deliver significant cost savings to both insurers and policyholders.

With AI-driven innovations, particularly in improving patient discharge times and claim settlements, what is your outlook for Indian healthcare? Do you see AI-infused, data-driven digital transformation as the next big thing? How is Medi Assist aligning itself with these emerging trends?

Absolutely! AI-driven innovations will continue to evolve and reshape the landscape of Indian healthcare, with data-driven digital transformation serving as its cornerstone. At Medi Assist, we're already witnessing the transformative power of AI in expediting patient discharge times, streamlining claim settlements, and reducing fraud. For instance, with Raksha Prime, we have not only crossed 1 lakh discharges since inception but have also reached a 20k hit rate month on month.

Looking ahead, we envision AI driving personalized and predictive healthcare experiences, empowering individuals with proactive insights and tailored care.