Dr Sabine Kapasi, Co-Founder and MD, Enira Consulting and Dr Ashish Panghal, Senior Consultant, Enira Consulting talks about the role of AI in insurance sector in India
India’s population, now exceeding 1.428 billion, is largely young, with more than half of the population under the age of 25 and over 65 per cent below 35. Despite this youthful demographic, health insurance coverage in India remains alarmingly low. According to the National Insurance Academy, 95 per cent of the population remains uninsured, and 73 per cent lack adequate health coverage. National Health Accounts Estimates in India reported that out-of-pocket expenses account for 52 per cent of current health expenditure (FY-20), one of the highest globally. This gap in coverage is a significant concern, especially as access to quality healthcare is recognised as a basic human right.
Medical treatments are becoming increasingly expensive, and medical inflation is a concerning issue in India. Furthermore, advancements in medical technology, such as robotic surgeries for knee replacements, often fall outside the purview of traditional insurance coverage. This has led to low insurance adoption rates.
In 2019, the National Statistical Office reported that private hospitals account for more than half of all inpatient hospitalisations in both rural and urban areas, at 52 per cent and 61 per cent, respectively. Yet, India continues to face significant challenges in healthcare access and quality. The country ranks 145th on the global Healthcare Access and Quality (HAQ) index, lagging behind countries like Bangladesh and Sri Lanka, according to the Lancet’s Global Burden of Disease Study in 2017.
Digital health insurance, though still in its early stages, presents a promising solution. Digital insurers are seeing a growth rate of 20-30 per cent (according to PwC survey). This shift in consumer behavior is evident, with more people opting for the convenience of online platforms.
While agents still hold a strong presence in the market, the future of health insurance in India is clearly leaning towards digital solutions, with advancements in Artificial Intelligence (AI) helping make insurance more accessible, fair, and efficient.
AI’s role in no-cap health insurance and fair pricing
The integration of AI in health insurance offers a revolutionary opportunity to implement no-cap health insurance, ensuring unlimited coverage for patients while managing costs and risks for insurers. Traditionally, health insurance has been bound by policy limits and caps, which often leave policyholders with unmet medical expenses. AI can transform this by improving risk assessment, enabling insurers to offer more comprehensive coverage without the typical restrictions.
AI-powered tools can analyse vast amounts of data to predict potential health risks more accurately than traditional methods. This leads to more precise premium calculations, ensuring that the costs for the insurer remain manageable while offering fair pricing to consumers. In a system where data is used to tailor insurance premiums based on individual risk profiles, AI can reduce the likelihood of arbitrary or inflated pricing, making health insurance more accessible and equitable for all.
AI in health insurance pricing models
AI holds the potential to completely transform the way health insurance premiums are determined. By analysing vast datasets of medical histories, lifestyle choices, and genetic information, AI can offer a more personalised approach to pricing. Instead of relying on broad risk categories, insurers can set premiums that more accurately reflect the individual health risks of policyholders.
AI’s ability to analyse big health data from Unified Health Interfaces (UHI) and financial systems will enable more equitable pricing models that reflect an individual’s real health risk.
Furthermore, AI can continuously learn from new data, adjusting prices in real time to reflect changes in a person’s health or lifestyle. This dynamic pricing model not only helps keep premiums fair but also incentivises healthy behaviors, as policyholders may receive lower premiums for maintaining healthy habits. This is a stark contrast to the current one-size-fits-all approach, where premiums often do not reflect individual risk accurately.
Tackling operational challenges with AI
India’s low insurance penetration can largely be attributed to the high cost of premiums and inefficiencies in the claims settlement process. AI and machine learning (ML) offer a way forward, transforming Health Insurance 2.0 by automating and streamlining many processes that have traditionally been slow and cumbersome.
The development of AI-driven insurance platforms reduces paperwork and simplifies complex procedures, resulting in faster claims processing, improved customer satisfaction, and reduced operational costs. By eliminating the need for manual intervention in claim assessments, AI allows insurers to offer quicker resolutions, reducing the frustration often experienced by policyholders. India, leading the world in fintech adoption at 87 per cent, supports the development of digital health wallets and integrated health-tech ecosystems. Insurtech players are also exploring micro-insurance models with low premiums and disease-specific payouts.
Enhancing risk assessment with AI
Risk assessment is a cornerstone of the insurance industry, and AI is making it more accurate and precise. By analyzing large datasets, AI can detect patterns and correlations that were previously invisible to human analysts. This allows insurers to predict risks with far greater accuracy, enabling them to offer more tailored coverage to policyholders.
AI’s ability to assess risk extends beyond individual policyholders. By using machine learning algorithms, insurers can evaluate risk at a more granular level, factoring in variables like geographical location, age, and medical history. This data-driven approach ensures that premiums are more accurately priced, benefiting both insurers and policyholders.
AI in underwriting
AI is already playing a significant role in underwriting by making processes more efficient, accurate, and customer-friendly. One such innovation is the use of videography in health assessments, allowing insurers to conduct real-time assessments of an applicant’s health condition. Through VideoMER technology, insurers can capture and verify health data during live assessments, improving transparency and reducing fraud.
Additionally, digitisation has transformed the way medical data is processed. Pathology reports are now analyzed using AI algorithms, which help determine eligibility for policies faster than ever. AI also automates medical examination report checks, ensuring that all information provided by the applicant is accurate and reducing the chance of errors.
Digital lending platforms like Aarogya Finance use AI-based psychometric testing to assess credit risk for patients without traditional credit histories. With default rates as low as 2 per cent, these systems show AI’s ability to predict risk more fairly than traditional methods. A similar approach could be used for risk scoring in health insurance. AI can also be integrated with Software as a Medical Device (SaMD) solutions to improve and automate risk prediction, helping identify risks across different customer groups. This could enable insurers to offer policies to high-risk or traditionally excluded populations, such as the uninsured in rural areas or those without credit histories.
AI in claims processing
One of the most significant impacts AI is having on the health insurance sector is in claims processing. Traditionally, claims have been a time-consuming process prone to errors and delays. AI-powered automation now enables insurers to process claims with greater efficiency and accuracy, minimizing human errors and speeding up claim settlements.
Natural Language Processing (NLP) and image recognition are two AI technologies that have revolutionized claims processing. NLP helps insurers interpret customer inquiries and documents, while image recognition technology allows for quick assessments of medical bills and related documentation. These technologies ensure that claims are processed more swiftly and accurately, reducing operational costs and enhancing customer satisfaction.
AI is particularly effective in handling low-ticket-size claims, offering quicker resolutions and improving overall customer experience. Automating claim processes with AI reduces fraud, administrative burden, and processing times, enabling insurance providers to pass on savings to customers in the form of reduced premiums.
Ethical considerations of AI in insurance
Despite the immense potential of AI in transforming the health insurance sector, its integration comes with several challenges. Data privacy concerns, the digital divide, and the need for regulatory frameworks that address AI’s unique challenges are some of the major hurdles that insurers must overcome.
In India, the regulatory environment surrounding AI in insurance is still evolving. The Insurance Regulatory and Development Authority of India (IRDAI) has begun addressing AI’s role in the industry, focusing on data security, consumer protection, and ethical AI usage. Insurers must ensure that AI tools are not only compliant with existing laws but also transparent and free of bias. Ethical considerations, such as ensuring fairness in pricing and preventing discrimination, are crucial to building trust with consumers.
Looking ahead, AI’s role in health insurance will only continue to expand. With advancements in machine learning and data analytics, insurers will be able to offer even more personalised coverage options and pricing models. The integration of IoT devices and telematics will further enhance real-time data collection, improving risk assessment and offering more dynamic pricing.