Behind IndiaFirst Life AI Tech Strategy
Setup in 2009, IndiaFirst Life insurance company has since been offering the best solution for customers’ insurance needs. With a paid-up share capital of ₹663 crores, it is one of the country’s youngest life insurance companies. Promoted by two large public-sector banks — Bank of Baroda with 44% stake and Union Bank of India with 30% stake, it is one of the few insurance companies in India to break-even within five years since inception. To drive its working, IndiaFirst Life largely depends on technology across functionalities such as customer engagement, operational efficiency, differentiation & risk management. To better understand their tech strategy, the impact of COVID on tech and data, emerging AI trends post-COVID and more, we got in touch with Sankaranarayanan Raghavan who is the chief technology and data officer at IndiaFirst Life Insurance Company Limited. Raghavan believes that analytics and data science will help them in creating a better customer, employee experience in addition to improving productivity and efficiency. “We also believe that we can innovate on products that are best suited for a segment/market, based on analytics and data science,” he said. They have also tied up with many insurtech companies such as Toffee Insurance, Riskcovry and Gramcover for tasks such as the better distribution of their insurance solutions through digital platforms, providing innovative and bit-sized insurance propositions to different partners, offering group insurance-based solutions, among others. Below is the detailed interview: How does the company use analytics and data science in its overall working? Please share some use cases. Currently, we are using analytics and data science in sales and operations. In sales, it is used right from the time we are hiring the right talent to select the area/segment the person should be allocated. While onboarding a new customer, based on the customer’s initial data, our model suggests the right product that reflects his persona and provides options to him. In addition to that, our model predicts the possibility of fraud and persistency. All the models deployed can learn and update itself. We are in the process of implementing AI-based OCR for the documents that are submitted, which are further scrutinised automatically. In operations, other than the scrutiny, we use models in renewals to increase the persistence, revenue and at claims stage to weed out fraudulent claims. We are in the process of deploying a model, which will help in assessing the case from underwriting guidelines. What does the overall tech strategy at the company look like? What are some of the new implementations and innovations in emerging tech? The tech strategy is focused on deploying technology and tools that help to reduce the time, give better efficiency, have better usage of AI/ML in both the customer and employee life cycle. The aim is to provide superior customer experience and be light on architecture with full movement to microservices. While we have embarked on the hybrid cloud, we will be expanding it further to help the digital arm of the business. We have also recently deployed and implemented low code no platform giving one universe app to the sales force. Our tech stack is pretty much a new age with a focus on voice and multilingual. How are AI and data science implemented across domains such as customer engagement, operational efficiency, risk management and others? Early Claims Prediction Model: Developed an ML Model to flag out plausible early claims at the time of customer onboarding.Fraud Detection Model: Identifying fraud at the time of onboarding and at regular intervals during claims.Sales Nudges: Inputs that help the sales team to spend their energy at the right and desired areasApplication Stage Persistency Prediction: Our ML model will run during the form filling by Identifying the predictability of the persistency at the onboarding stage.Customer engagement at the right time: This is about when to intervene and how to intervene, creating a win-win situation What have been some of the impacts of COVID on technology and data? Given that IndiaFirst Life has embarked on the digital journey for a few years now, the shift to the new normal wasn’t felt — for both customers and employees. Our onboarding is 100% electronic for the past two years. Employees are highly mobile with a tablet/laptop. In servicing, we have servicing capabilities available in WhatsApp, Portal, IVR, chatbot and email. Post-COVID, we have seen a 2X uptake on the digital channels giving the benefit of early implementation of digital-early. Our Sales team uses e-Sampark an innovative way of reaching out to the customers. Our ‘Ghar Bhaite Insurance’ initiative has shown good uptake too. What are the emerging trends around digital, data and technology disruptions in the industry? As India is becoming Atmanirbhar and transitioning to Bharat, the voice is going to disrupt the industry. The transition of Insurance from being a push to pull product, together with Voice, multilingual and simple products, will increase not only the insurance adaption in the country but also to better-secured society. How can companies capitalise on digital-tech developments and brace the firm for a more optimistic picture? Digital technology helps in modularising things, making it agile, speeder time to market, experiment new innovative models and reach the unreached. These features of the digital-tech bring a whole lot of opportunity to anyone who has got an idea to execute it. This empowerment and ability to make people experiment gives raises a newer way of reaching out, thereby opening up a whole lot of opportunities.
Setup in 2009, IndiaFirst Life insurance company has since been offering the best solution for customers’ insurance needs. With a paid-up share capital of ₹663 crores, it is one of the country’s youngest life insurance companies.  Promoted by two large public-sector banks — Bank of Baroda with 44% stake and Union Bank of India with […]
Raghavan believes that analytics and data science will help them in creating a better customer and employee experience.
["Interviews and Discussions"]
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["AI", "ML", "data science", "analytics", "Aim", "Ray", "RAG", "fraud detection", "microservices", "R"]
Srishti currently works as Associate Editor at Analytics India Magazine. When not covering the analytics news, editing and writing articles, she could be found reading or capturing thoughts into pictures.