Sarojini Rao*, a retired teacher, invested a sum of Rs 1 lakh in a three-year equity linked saving scheme through her bank. Her goal was to get tax benefits, and she was told she only had to pay the premium once. During the second year, though, Rao’s account was debited of another Rs 1 lakh as premium, giving her sleepless nights. She later learnt from her bank that a ULIP scheme was sold to her instead of the ELSS plan she wanted to opt for.
Rao’s story is not uncommon. The insurance sector in India is plagued by Insurance mis-selling, the deliberate sale of products or services that are unsuitable for the customer’s needs. A typical example would be of a broker who sells life insurance to someone who has no dependents.
Mis-selling is not only a business challenge for Insurance companies, but also a huge inconvenience to customers. From banks mis-selling insurance to even the insurance ombudsman acknowledging higher percentage of mis-selling on life insurance policies, this sector certainly knows what hurts it the most.
Since 2015, the Insurance Regulatory and Development Authority of India (IRDAI) has been asking banks to adopt an Open Architecture model for banks to have tie-ups with insurance players – life, non-life, and health segments. However, experts have suggested that the existing and bancassurance model is riddled with challenges.
Now new-age Insurtech companies are stepping in with technological expertise to design products that engage with customers in a manner that makes onboarding and claims management processes a breeze.
Insurtech, like fintech, is a term used to refer to a company that uses technology to disrupt the insurance industry. World over, Insurtech companies are working to evolve better pricing models using deep learning trained artificial intelligence (AI) to handle the tasks of brokers and find the right mix of policies to complete an individual’s coverage.
In India, Symbo Insurance, a full stack insurtech company, is focused on context-based, customer need-oriented insurance. Symbo Insurance promises a great experience on the back of its investments in machine learning and risk identification parameters during the customer on-boarding and settlement processes.
In an interview with Sify.com’s Sairaj Iyer, Mitesh Jain, co-founder and group CTO at Symbo Insurance shares how new technologies are helping his company and the Insurance sector.
Sify: In a country known to have a high mis-sold ratio for insurance, how has technology helped solve issues?
Mitesh Jain: This is a problem for any sector which is picking up. To ensure the customer knows and understands what he is buying, it is important that the product is explained to him in terms which he/she understands.
Technology can play a pivotal role in terms of effectively educating the buyer about coverages and exclusions of insurance, to begin with. The individual-level data points can be very effectively used with the help of machine learning and data crunching algorithms to identify right-fit products for the individual. This right fit product can be derived by effectively churning thousands of data points of the user and cohort of users with similar profiles, needs, and risk exposures. This could eliminate mis-selling from the industry.
What are your thoughts on the flaws and potentials of India’s Insurtech market with that of overseas markets such as Singapore or even the West?
India has been at the forefront of technology advancement in fintech and other domains for the almost the last decade. India’s insure tech market is poised to set up the right set of products for large scale and trustable distribution of insurance products of insurers and distributors across the global. The sheer scale of the Indian market makes for effective use of AI and ML to build products which add immense value in low context markets like Singapore and West.
Among the contemporary trend on Artificial Intelligence, Machine Learning, Chatbots, P2P for micro-insurance, and Internet of Things, what is likely to offer the highest return on investment to insurance service providers?
Machine learning is something we are invested heavily in. With the amount of data available today, we need these machine learning algorithms to identify risk exposure and needs to a particular segment or cohort of users and identify the best-fit products for them.
What machine-learning technologies has Symbo invested in lately?
Currently we are setting up a data lake to collate data across our systems. On that data clustering algorithms applied followed by Navie Bayes classification will provide the right set of the knowledge base. Further, logistic regression can be effectively used to achieve the right user classifications.
Your profile suggests that you work in the areas of Enterprise, Affinity and Point of Sale Partners. What has been the characteristic differences between the tech practices of these three distribution channels?
Symbo has three distribution mechanisms – namely, enterprise, affinity and point of sale Partners(PoSP).
The three channels cater to three very different and very specific audiences. While affinity channel very effectively reaches the TIER 1 user of need at their point of need, POSP [Point of Sale Partners] model is built to ensure right insurance products and benefits reach the India 2 population. We also target the SME channel.
In the enterprise segment, Symbo is working in making commercial insurance available to all the SMEs, by translating traditional insurance purchase process into automated end to end web-based journey. For the affinity line of business, Symbo is working with the insurer to create need based bite-sized covers and work in partnership with relevant partners. For example, Symbo partnered with marathon ticketing websites to create an API based mechanism to embed a Marathon insurance product as part of the customer’s online journey. For their PoSP channel, Symbo focuses on serving the underserved markets and creating employment opportunities for partners. Symbo’s PoSP channel is trying to facilitate insurance sales by allowing partners to receive training, sell insurance and serve customers all via the Symbo partners mobile app. Symbo’s core value lies in customer service and hence Symbo does the claims servicing for all its customers for all the distribution channels. All of Symbo’s services are available in English, Hindi and expanding to other regional languages as well.
Can you please elaborate on the affinity channel?
In India, till now insurance has been sold rather than been purchased. The primary reason for this is that the user is not explained or apprised with the risk at the point of purchase or point of need. Affinity is a channel, of distribution where in a user is apprised of the risk that exists and of appropriate cover for it at the “Point of Need”. e.g. Imagine a person is buying a spectacle. One of the worries is what if I accidentally break these costly glasses. Providing them spectacle cover which also covers them for cataract, is the most appropriate as per the need at that point in time.
For the SME channel, when you say you convert traditional purchase process to an automated web-based journey, what is Symbo exactly helping do?
Currently, the channel of insurance which is reaching out the SMEs, are the agents. While agents serve SME needs of insurance, there is a huge lack of risk consulting and the problem of mis-selling in the SME market. Also, most of the SME market is still not penetrated and adequately covered. Symbo, using its proprietary technology reaches out to these SMEs via digital medium and provides an assessment of their risk. Symbo’s technology plays a very key role in educating these SMEs of their insurance needs, eventually enabling them to acquire these insurances online. Symbo also assist in the filing of claims and the complete process of it.
What proprietary technologies are you talking about?
Symbo has a proprietary algorithm which does risk identification and risk consulting for individuals and SMEs. The algorithm enables individuals to identify the priority of various insurance products and the quantum of the sum insured they should buy, based on multiple factors.
*Name changed to protect identity
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