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Powering Insurance Agents with AI

In the post-CoVID-19 era, a tremendous amount of focus, time, and energy has been invested in understanding the customer or policyholder based on the insurer's proprietary data and the data collected by many other research agencies. The customer is deeply analyzed and offered customized or personalization, as we call, solutions and offerings.

However, the investment made by insurers has only been focused on 5% of the number of policies sold or approximately 11 Lacs policyholders, that are sold by direct sales, web aggregators, and online sales.

This begs the question, why are insurers only investing in distribution channels that represent 5% of the number of policies sold?

According to the IRDAI numbers released in March 2021 for the Indian insurance business, for the financial year 2019-20, the agents' market share is 78.40% ( a whopping 226.14 Lacs policies), followed by Bancassurance at 11.22%.

Online business is just a minuscule at 1.06%, contributing just over 3 Lac policies. As per a study, in Europe, online sales have not crossed 10% of total sales.

Are we missing something here?

Are we not overlooking the agency sales force, the bread and butter of insurance sales? Is it time we should start thinking about how this massive sales force of 22.78 Lac agents that represent 78% of the market share, out in the field who are trying to protect the financial hardship of people in case of unforeseen events happening?

Agents continue to sell the old traditional way by understanding the customer need based on discussion or offering a product understood well by the agent. For example, if an agent has an easy time selling a product to one customer, why not sell it to the next customer as well?

By following this logic, the agent is applying the needs and judgment of one customer to others instead of understanding the individual needs of all his customers.

Isn't this is an opportunity for insurers to take their investment in better understanding the customers and increase their agents' productivity by using advanced technologies that can enhance their selling skills?

Increased Focus on the Agent Channel

Agents should be hand-held from the day the agent starts his journey as an entrepreneur with a business idea of selling insurance and service their families when they need them most. The best thing about all the agents these days is they own a smartphone and know how to operate an app, which solves the delivery aspects.

As the first step, the agent needs to be trained. Gone are days when we trained the agents in classroom settings, or one course fits all. In these days of technology or machine learning, the insurer should profile the agent and match him with the skill set of other successful agents matching his profile, area of operations, etc., to have a fix on his training needs. Training has to be modular and focused on financial, insurance, and company products.

In the blog article, “The Top 3 Emerging Trends for Agent/Advisor Analytics Using AI,” we discussed at a high level what we believe are the top three emerging trends where artificial intelligence predictive and sentiment analytics can help insurance companies improve the effectiveness of their independent agent distribution channel.

As the agent moves in the life cycles, he should be supported to have a good closure rate and reducing the time taken for closure. This can be achieved by providing access to agents to recommend the products using AI and ML techniques on similar lines as for online customers. The only difference here is the agent will be coming online instead of the customer directly. The product recommendation can be further strengthened by profiling his customers and enabling him to recommend the product based on ML and AI processes.

Today, the average agent productivity is just 1.86 policies per year per agent for the private insurance players. On the other hand, the industry is churning out hundreds of MDRT club members every year. Also, insurance penetration in India is relatively low.

These facts indicate that agents have an opportunity if they are properly mentored to be successful in this trade. In a previous blog article, "Using AI for Increasing Agent Productivity,” we focused on how AI technologies, such as predictive analytics, can provide insurers with the opportunity to engage with agencies to help improve their productivity proactively.

Agents can also be informed about customer behavior concerning regular premium payment, mode of communications, self-service portal. Agents should be sensitized to the advantages of the self-service method of communications. These tools are not only ways of effectively communicating but also frees the agents' bandwidth for fresh new sales. The second aspect, i.e., advantages to agents, is hardly enforced. Based on ML inputs, if any customer education is to be imparted, Agent and Insurer should not wait for onboarding of the customer, but it can start and inbuilt in the sales process.

Conclusion

We conclude that effective AI and ML tools made within reach of agents by enabling/integrating with social media platforms can be a game-changer for the agents' life cycle.

The Indian insurance industry can take the lead and set an example on how the face of and perception of insurance agents in any society can be changed. This goal is not a daunting task since a considerable amount of focus and energy have already been spent on understanding the customer based on the insurer's proprietary data and data collected by many other research agencies.

It is just a question of making it available to agents on the platforms where they are comfortable and not on the platforms where Insurers are comfortable.

Note: All numbers are quoted from HANDBOOK ON INDIAN INSURANCE STATISTICS F.Y. 2019-20 published by IRDAI.

Interested in learning more about how Aureus is transforming the insurance agency sales force with AI? Click on the link below.

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Arun Agarwal
Arun Agarwal
Arun is a senior executive with over 24 years of experience in the BFSI sector. He has worked with leading insurers like Aviva and Pramerica Life and has led teams towards the achievement of the organization's long & short terms business goals. As an insurance domain expert, Arun has made significant contributions by driving excellence across operations, sales management and compensation policies and execution, financial planning & business strategy, MIS and regulatory reporting functions.

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In the post-CoVID-19 era, a tremendous amount of focus, time, and energy has been invested in understanding the customer or policyholder based on the insurer's proprietary data and the data collected by many other research agencies. The customer is deeply analyzed and offered customized or personalization, as we call, solutions and offerings. However, the investment made by insurers has only been focused on 5% of the number of policies sold or approximately 11 Lacs policyholders, that are sold by direct sales, web aggregators, and online sales. This begs the question, why are insurers only investing in distribution channels that represent 5% of the number of policies sold?

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