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By Rahul M Mishra
While gaining ground in India, the insurance market is expected to become one of the fastest-growing markets in the world. Currently, the Indian insurance market is the 10th largest in the world; however, it is anticipated to become the 6th largest by 2032, according to a report by Swiss Re.
In order to meet this aim, the insurance companies in India need to tap into new markets, such as Tier 2 and Tier 3 cities. These cities have become hotbeds of business growth owing to several developmental factors. However, to target this market efficiently, the insurers need to adapt new-age technologies such as AI. As AI technology has advanced, it has become an integral part of the insurance sector.
The insurers have been adopting AI technology to enhance the customer experience, streamline operations, and make faster and more accurate decisions. As growth in Tier 2 and Tier 3 cities has become necessary for the insurers, AI will aid them in penetrating these markets.
Aiding in personalised marketing
People residing in Tier 2 and Tier 3 cities have different purchasing habits and considerations when compared to those in metropolitan areas. Hence, the strategies that insurers would have used in developed areas might not work in the minor cities. Therefore, insurers need to understand the market and then cultivate their strategies in order to be successful there. One way to do this is by leveraging AI technology in order to provide personalised experiences. According to a previous Epsilon study, brands that offer personalised experiences increase the likelihood that 80% of consumers will make a purchase.
Based on the customer data, including behavioural patterns, demographic information, and location, the marketing strategies can be tweaked. The individualised approach will help target specific cohorts residing in Tier 2 and Tier 3 cities with relevant messaging. Another way is to form alliances with micro-FinTech companies in these areas that have a better understanding of people’s financial wellbeing.
Round-the-clock support with chatbots
Pandemic acted as a catalyst for the growth of conversational AI along with the rise of digitalization. The technology disrupted almost every sector in operation, and the insurance sector is not an exception. Insurance is a 24/7 industry, and since mishaps can occur at any time, so can the claims. Manually catering to the needs of customers can be daunting owing to the number of claims an insurer receives every day. Therefore, AI with bots can improve efficiency, improve processes, and satisfy customer needs.
An insurance chatbot makes sure that every query and claim receives a real-time response. A conversational AI can initiate quotes, carry on conversations, ascertain the customer’s intent, recommend products, and even respond to follow-up queries. A Statista statistic claims that one-third of customers found chatbots to be “very effective” in answering their questions. Chatbots can also be customised in local languages to provide 24/7 support. This guarantees that no customer will go unanswered and gives them the option to connect to a live agent if necessary, keeping customers of Tier 2 and Tier 3 cities satisfied.
Identifying potential customers
Businesses continue to benefit from AI and predictive analytics in terms of identifying consumer trends, creating customer profiles, and creating more precise potential target audiences. But it’s also doing much more, both in terms of gathering data and using it to provide customers with the individualised service they require. All marketing initiatives must include target group segmentation, and insurance companies are no exception. If businesses don’t know whom to persuade, convincing consumers in Tier 2 and Tier 3 cities is challenging.
Today’s marketers can accurately identify the best target audience thanks to AI and predictive analytics. It also helps identify new subgroups of this group that share characteristics with insurance in a quicker and more accurate manner. With the help of these data sources, insurers can make ex ante decisions about pricing and underwriting, enabling proactive contact with a bindable quote for a product bundle customised to the customer’s risk profile and coverage requirements.
Facilitating fraud detection
Insurance companies found it challenging to expedite the claims processing process under the previous traditional model because of the daily claim volume. It can be difficult to identify specific patterns in the claim data that might call for closer examination under human supervision. But with AI, it only takes a few minutes and skilful programming for digital tools to detect particular claim patterns that happen arbitrarily or in large quantities. And all of this is accomplished without unnecessarily raising operating costs or adding to the workload.
Therefore, it is in the best interests of the insurance companies and the claimants for the claims to be resolved as soon as possible. The entire claims process has been streamlined and expedited as a result of technology like artificial intelligence (AI), data analytics, and other related tools. AI and other technological advancements have not only significantly sped up the processes, from data capture to settlement initiation, approval, and authorization to tracking payment and recovery and managing communication but also aided in improvising fraud detection.
All things considered
Along with AI, insurance companies also require a well-coordinated strategy that involves re-evaluating the company’s capabilities. This can be accomplished by living up to each company’s value proposition and thinking creatively about how to best meet the needs of customers in Tier 2 and Tier 3 cities. Then they can finally understand how to leverage AI and learn how to create value for their products. With the advancement of AI technology and its accessibility, modern insurers are tapping Tier 2 and Tier 3 at an astonishingly rapid rate and expect to soon modify their priorities according to their customers. As they leverage the power of AI, they can extend their reach, find potential customers, efficiently detect fraud, and cater to the needs of the customers in these minor cities.
The author is co-founder and director, Policy Ensure
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