How Coverfox Utilises Machine Learning
Mumbai-based Coverfox Insurance was founded in 2013 to “Make insurance simple,” said its CTO Piyush Ranjan, during a recent conversation with Analytics India Magazine. Initially founded by Varun Dua and Rane, the insurtech startup reinvented itself under the leadership of Sanjib Jha, John Mayne and Piyush. It aims to provide omnichannel and automated insurance experience to first-time insurance buyers, millennials, and India’s rural segments. A BTech graduate from IIT Kanpur, Piyush joined the Coverfox team in March 2020. He comes with close to 15-years of experience across sectors. Piyush started his career as a Software Engineer in Cleartrip, post which he worked with Ola as the Senior Director of Engineering. He is helping Coverfox build its consumer application and introduce data science and machine learning practices. Edited excerpts from the conversation: AIM: What are your products? Please elaborate on their working methodology. Piyush Ranjan: Coverfox offers diversified technical solutions to address market gaps across the Indian insurance ecosystem. Coverfox allows all customers to compare and choose from multiple insurers with advisory on best coverage matching their needs for various products and claims assistance. We offer motor (both personal and commercial vehicles such as taxi and GCV), health, term life, travel, corona, super top-up, personal accident, critical illness cover and ULIP insurance products on our platform. Our mobile application for retail consumers went live recently and offers car, bike and health insurance. We will soon be expanding our catalogue to cater to a wider audience in need of digital insurance products, especially bite-sized ones. Coverdrive — our seller app, offers hi-tech selling capabilities right in the palm of your hand. We also offer LIC microinsurance products on this platform. AIM: Tell us about the tech stack. Piyush Ranjan: Coverfox is a fully cloud-native platform. We have a micro-services based backend that allows us to create new products and integrations with minimal intervention. We largely use open-source products. Our language of choice is Python. We heavily use big data platforms to store large datasets. We run machine learning models on top of this data to provide a superior customer experience. AIM: What tech tools do you use? Piyush Ranjan: Our cloud is powered by Amazon Web Services. For our big data pipeline, we use Kafka, Redshift, Tableau for analytics and dashboarding. We use tools to power our personalised user communication journeys across different products. We have very strong data analytics and data science pipelines with deep observability at every step. We also have an in-house multi-product, sales and service CRM specifically built for insurance selling and bubbles up all the customer intent information seamlessly to the sales agent as required. All the technology is built in house with no dependency on any external vendors. AIM: How are you leveraging AI and ML technologies? Piyush Ranjan: Coverfox is ushering in true Insurtech 2.0 via fully automated real-time policy issuance with 3-Way API integration of Coverfox, Insurance Partners, and Corporate Partner. Using data science models to recommend the most relevant policies The decision to reach out to the customer over calls is based on a machine learning model that predicts the customers needing help to avoid unnecessary calls. Product funnel optimisation using quote visibility gap analysis, discount maximisation and price benchmarking engines. Fully automated claims process and support. AIM: Who do you see yourself competing with? How do you differentiate yourself from your competitors? Piyush Ranjan: The Insurtech industry has seen a boom due to the pandemic and India’s already growing online consumer base. Our direct competitors are other web aggregators like Policybazaar, InsuranceDekho and Turtlemint. We aim to differentiate ourselves by offering the industry best insurance services fully digitally. Our tech capabilities and well thought out product strategy make us a favourite of our customers. AIM: How is Coverfox reimagining the insurtech landscape in India? Piyush Ranjan: Coverfox is leveraging AI and tech to reimagine an insurance landscape independent of call centres, building a one-stop solution for all insurance needs at the consumer’s fingertips, building on the following key pillars: Understand: Helping consumers understand insurance more seamlessly than ever by curated content, video guides, informational blogs and newsletters, chatbots and voice bots, and online forums.Compare and purchase: Empowering consumers to compare and purchase within 90 seconds through robust product journeys and end-to-end online flows on app and web.Smart recommendations and automation:A deep learning model to recommend the best plan basis customer needs and demographics.Compare: AI-led intuitive UI/UX to help users make informed insurance buying decisions within minutes.Scan and fill: Scan existing policy documents and fill the form to reduce customer hassle.Post-purchase: Seamless post-purchase services with easy renewal, fully digital policy updates, and a very simplified claims process. AIM: Share a few company growth numbers. Piyush Ranjan: We have increased productivity of the call centres by six times; moved bike insurance (both new sales and renewals) to fully un-assisted mode — an industry first. We are the first insurtech company to integrate with LIC to sell micro-insurance products fully digitally. Additionally, we have 50+ insurance partners on Coverfox.com, with over 600 insurance products and variants in end-to-end API integration. Our monthly net burn reduced significantly to make our gross margin profitable. Our recently launched B2C App has witnessed early growth and achieved nearly 100k+ installs within three months. AIM: What is in the pipeline for Coverfox? Piyush Ranjan: We plan to get India insured and empowered by building at the intersection of tech, ease, and access. The growth projection for the Indian insurance landscape looks promising; however, this scale will be unlocked through insurtech innovations. The need-gap we are solving for: The insurance buying experience hasn’t evolved for over a decade, with consumer acquisition and conversion heavily dependent on call centres. B2C innovations in the pipeline:Reducing the dependency on call centres by increasing the share of unassisted sales.Increase the size of data science and machine learning practice to unlock more business opportunities, such as cross-sell and renewals.New Developments in B2B:Multiple key partnerships onboarded and in the pipeline to ramp up motor and health sales.Onboarded India’s largest rural business partners to sell bite-sized rural policies in a fully digital fashion. To understand how technology has been powering the insurance sector, click here.
Coverfox provides omni-channel and automated insurance experience to first-time insurance buyers, millenials and the rural population of India.
Coverfox provides omni-channel and automated insurance experience to first-time insurance buyers, millenials and the rural population of India.
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["AI", "machine learning", "ML", "deep learning", "data science", "analytics", "Aim", "RAG", "chatbots", "Kafka"]
After diving deep into the Indian startup ecosystem, Debolina is now a Technology Journalist. When not writing, she is found reading or playing with paint brushes and palette knives. She can be reached at debolina.biswas@analyticsindiamag.com