Building a Digital Ecosystem for Solving Customer Problems

You joined ManipalCigna Health Insurance in December 2022. How has your journey been so far, and can you share the key IT interventions or programmes you have undertaken at the company?

Since joining the company, my journey has been both dynamic and rewarding. With over seven years in the insurance space, I have always believed that innovation should be grounded in solving real customer problems. At ManipalCigna, we have focused on building a future-ready digital ecosystem that’s agile, scalable, and deeply customer-centric while in parallel working on some foundational capabilities that help us be ready for the future. We pulled together a data lake, which is now the powerhouse for the entire AI capabilities and customer journeys.

We introduced several key interventions. One of them was the launch of ‘Expert Assist’, an AI-powered chatbot. The system offers real-time support and escalates issues to live agents in a smart manner. We used AI and Robotic Process Automation (RPA) to improve backend operations. This was especially helpful for claims and servicing. We used AI to predict claims. It also assists the contact centre by providing automatic replies to emails. Including in fraud detection models, to prevent abuse.

Beyond automation, a unified 360-degree view of the customer has helped us deliver contextual and personalised experiences across channels.

We have enhanced and enabled sales with a simple yet powerful customer onboarding platform and a distribution platform with a real-time dashboard for agent hierarchy to manage, track, and engage with leads and customers, helping them in smooth servicing and renewals. Our e-servicing portal and mobile app have helped move 50 percent of traffic from call centres to self-service, giving a smooth experience to customers.

Ultimately, every intervention has been aimed at simplifying customer journeys and improving internal efficiencies, which in turn enhance the customer experience in terms of reduced TATs.

What have been the key benefits or outcomes of these implementations?

Our digital initiatives have delivered strong, tangible outcomes. Fraud detection has improved, with systems that can now flag suspicious patterns in real-time, enhancing trust and reducing fraudulent instances.

More importantly, we have made the insurance experience simpler and more intuitive for our customers. From managing policies to accessing documents or filing claims, everything can now be done through our mobile app or chatbot, eliminating paperwork and delays, and providing a personalised experience to our customers. On the operations side, automation has helped us reduce manual interventions, improve consistency, and lower operational costs. At ManipalCigna, our focus remains on leveraging technology not for its novelty, but for its ability to genuinely improve customer outcomes. We are building solutions that empower users and offer them choices tailored to their needs, meaningfully, over time.

Could you highlight any challenges faced during these implementations – possibly outlining them initiative-wise?

Every technology transformation comes with its own challenges, and ours was no different. One of the biggest foundational requirements for any AI-led transformation is data. Managing and safeguarding data is complex and requires rigorous governance frameworks and adherence to principles like Zero Trust security.

For instance, while developing the chatbot, one major challenge was ensuring a seamless handover to live agents without disrupting the user experience. Adding voice support and preserving conversational accuracy required several rounds of training and refinement.

Our mobile app also evolved into a comprehensive self-service platform, which meant balancing rich functionality with ease of use. This required careful UI/UX planning and multiple iterations. 

On the backend, implementing RPA involved identifying the right processes, ensuring compliance, and managing change across teams. 

These challenges reminded us that successful transformation is as much about mindset and collaboration as it is about the technology itself. These challenges were about prioritising based on value rather than complexity. The devil is in the details, ensuring complete digitisation and automation throughout the entire process rather than only at the touchpoints.

What were some of the core learnings from the projects undertaken so far?

The past year and a half have reinforced many critical learnings. One of the biggest takeaways is that simplification, reusability, and scalability matter. Particularly in health insurance, where the volume and complexity of data can be overwhelming, simplifying claim processes has a direct impact on customer satisfaction. We aim to do more than settle claims in three seconds. We focus on speed. We also value accuracy and transparency in every customer interaction.

We have also learned that data hygiene and governance are non-negotiable. As we move towards more AI and GPU-driven analytics, ensuring clean, secure, and well-structured data is essential. Technology can only be effective when built on a solid foundation of reliable data.

Another important learning is the growing value of personalisation. Customers today expect services that are not only fast but also relevant to their unique needs. By building deep customer insights into our systems and enabling self-service tools, we are empowering users in a way that aligns with modern needs.

Strong cross-functional collaboration among tech, product, operations, and compliance is key. It transforms digital strategies into successful outcomes. We use technology to simplify health insurance. It helps us make the process faster and more personal for customers. We are growing at a rapid pace, and the systems we build have to be scalable. So, they will help us manage the growing volume without major changes.