Digital transformation is fundamentally reshaping the health insurance industry: Sumeet Aggarwal, CTO, ManipalCigna Health Insurance
Sumeet Aggarwal, Chief Technology Officer, ManipalCigna Health Insurance, highlights how digital transformation is revolutionising customer experience in the rapidly evolving health insurance sector. By embracing cutting-edge technologies like AI, machine learning, and blockchain, ManipalCigna is leading the way in delivering personalised and secure services. Aggarwal delves into the challenges and ethical considerations of implementing these innovations while speaking about the profound impact of emerging technologies on the sector’s future.
How do you see digital transformation impacting customer experience in the health insurance industry? Can you provide examples of successful digital initiatives?
Digital transformation is fundamentally reshaping the health insurance industry, significantly enhancing the customer experience. By integrating advanced technologies like AI and machine learning, health insurers can provide personalised recommendations, streamline claim processes, and improve overall service efficiency. Majority of our policies are also sourced digitally, ensuring a 360o digital experience across all touch points. Additionally, our mobile app allows customers to manage their policies, access health services, and receive instant support through a chatbot. These initiatives not only make interactions more convenient and responsive but also empower customers with greater control over their health insurance needs, providing them with a personalised experience. The result is a more engaged and satisfied customer base, which is crucial in today’s competitive market landscape.
What are the main challenges health insurance companies face when implementing digital solutions, and how can these be overcome?
Implementing digital solutions in the health insurance sector comes with its own challenges. One major challenge is data security and privacy, as health insurance companies handle sensitive personal information. Ensuring compliance with regulations like data privacy and maintaining robust cybersecurity measures is critical. Another challenge is integrating new technologies with existing legacy systems, which can be complex and costly. The legacy systems are challenging due them being monolith in nature. In a monolithic architecture, each component and its associated components must all be present for code to be executed or compiled and for the software to run. Monolithic applications are single-tiered, which means multiple components are combined into one large application. To overcome these, companies must invest in modern, scalable IT infrastructure and prioritise training for their staff to adapt to new tools and processes. At ManipalCigna Health Insurance, we have tackled these challenges by enhancing our cybersecurity protocols, ensuring a seamless and secure transition to digital operations. Our Zero Trust security framework ensures that no one is trusted by default from inside or outside the network, and verification is required from everyone trying to gain access to our resources on the network. Additionally, fostering a culture of innovation within the organisation helps in embracing digital transformation more smoothly
What are the ethical considerations and potential biases that insurers need to be aware of when deploying AI and machine learning in their operations?
When deploying AI and machine learning in health insurance, it’s essential to consider that AI systems can inadvertently perpetuate existing biases if they are trained on unrepresentative or biased data. This can lead to unfair treatment of certain customer groups. To mitigate this, insurers must implement rigorous testing and validation processes to identify and correct biases in their algorithms. Due to the probabilistic nature of AI models, which is a root cause for biases, it leads to hallucinations, meaning it can give incorrect outcomes. Therefore, such models need fine tuning on app specific data, to ensure it is a mature model. ManipalCigna ensures fine tuning in order to avoid potential biases when we deploy AI and ML in our operation. Transparency in AI decision-making is also crucial, as customers should understand how their data is being used and how decisions affecting them are made. At ManipalCigna Health Insurance, we are committed to ethical AI & ML practices by continuously monitoring our systems for bias and ensuring they operate with fairness and transparency. We also engage with stakeholders to align our AI & ML initiatives with broader ethical standards and regulatory requirements.
What emerging technologies do you believe will have the most profound impact on the insurance sector over the next five years, and why?
Emerging technologies such as blockchain, the Internet of Things (IoT), and advanced data analytics are poised to revolutionise the health insurance sector over the next five years. Blockchain technology can enhance transparency and security in transactions, reducing fraud and increasing trust between health insurers and customers. IoT devices, such as wearable health monitors, can provide real-time health data, allowing health insurers to offer more personalised and proactive health management solutions. Advanced data analytics enables health insurers to better understand customer needs and preferences, leading to more tailored and competitive health insurance products. At ManipalCigna Health Insurance, we are actively exploring these technologies to enhance our service offerings and provide greater value to our customers. By leveraging these innovations, we aim to stay ahead in the rapidly evolving health insurance landscape.
How can insurance companies leverage big data and analytics to create more personalised and competitive products for their customers?
Big data and analytics offer immense potential for creating more personalised and competitive health insurance products. By analysing vast amounts of data from various sources, insurers can gain deep insights into customer behaviour, preferences, and risk profiles. This enables the development of customised health insurance plans that cater to individual needs, improving customer satisfaction and retention. For instance, at ManipalCigna Health Insurance, we use predictive analytics to assess health risks and recommend tailored wellness programs, helping customers maintain better health and reduce health insurance costs. Additionally, big data helps in pricing optimisation, ensuring that premiums are competitively set based on accurate risk assessments. By harnessing the power of big data, we can provide more relevant and attractive health insurance solutions, ultimately enhancing our market competitiveness.
In what ways can technology help address issues such as fraud detection and prevention in the health insurance industry?
Technology plays a crucial role in fraud detection and prevention in the health insurance industry. Advanced analytics and AI can identify unusual patterns and anomalies in claims data, flagging potentially fraudulent activities for further investigation. Machine learning algorithms can continuously learn from new data, improving their accuracy in detecting fraud over time. For example, insurance companies can implement an AI-driven fraud detection system that analyses claims in real time, identifying suspicious behaviour and preventing fraudulent payouts. Blockchain technology also holds promise in combating fraud by ensuring transparency and immutability in transactions. For example, ManipalCigna Health Insurance uses these technologies to detect frauds including document tampering, etc. By leveraging such technologies, we can protect our customers and maintain the integrity of our health insurance services, ultimately contributing to a more trustworthy and efficient health insurance ecosystem.
