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Insurance Agents - Will They Disrupt or Perish?

The past two decades of the insurance industry has seen a lot of experimentation of distribution models: Max Life starting with a multi-level marketing model, Aviva trying to build both agency and bancassurance channels simultaneously, Canara HSBC starting with only bancassurance model and experimented with an agency in between, Pramerica Life & HDFC Life replicated agency sales channels to target a cluster of consumers formed, basis occupation or usage of common services.

Let us try to understand the risk brought by heavy dependence on banking partners. Aviva lost approximately 50% of the top line in a single month when its banking partners changed hands (HDFC Bank acquired CBoP, Canara Bank formed its own JV). In this turmoil, the Agency channel came to the rescue for Aviva Life.

In India, most banks follow the Corporate Agency (CA) model to distribute insurance products. This structure has emerged because of cost and ease of compliance in the CA model compared to the broker model. IRDAI (Registration of CA Regulations, 2015) as added extra weight of risk as it has allowed CAs to have arrangements with three life insurers to solicit, procure and service their insurance Products

The expanse of Indian territory, diversity of cultures, and languages make an agency sales force a necessary channel for the country to connect with the masses. With a literacy rate of 77.7% for 2020 and English being not a mother tongue, insurers do not have choices left but to build the agency channel if they want to connect with the masses (70% of the Indian population is in rural areas). These rural areas offer their own challenges in technology infrastructure as experienced in online classes (various media reports).

The agency channel has proven its stability and trustworthiness as a key pillar of insurance distribution in India. It has proven its mettle as indicated by business numbers released by IRDAI for the financial year ending 31st March 2021. In New Business Premium (Non-Single Premium: Individual category ) segment, two slots among the top five have been occupied by carriers classified as non-banks promoted insurance companies. LIC of India continues to maintain a 60%+ market share even in CoVID days riding on agency sales force only. These facts further reinforce a dedicated agency sales force's need and demonstrate its real potential and capabilities.

Still, managers of this channel say managing an agency sales force is remarkably interesting and challenging when people skills are tested to the limit.

It can be summarized as the ever-present challenge for insurers to identify.

“Who is my successful agent?”

This leads to the key term: “Successful.” The industry needs to fix the definition of how this metric can be quantified. Currently, multiple definitions are used from time to time to suit the individual need or prevalent need of organization management.

Some sample quantifications are:

  • Who is producing three policies in a financial year (a traditional way of looking since the age-old days of LIC of India)

  • Agents selling one policy per month/quarter

  • Agents earning INR 10K per month from the insurance business

  • The agent can run his/her household on income generated from the insurance business

  • The agent can move out from his primary occupation and make the Insurance sales as his primary occupation.

It is a fairly straightforward task to answer at least some of these questions post facto. For example, at the end of the quarter, the insurer can easily determine how many agents sold at least one policy in each month of the past quarter.

Identifying the Successful Agent

The key, however, is to be able to answer these questions for upcoming quarters, i.e., to predict which agents will be successful in the upcoming quarters. Insurers who can predict their agents’ performance in the upcoming quarters can optimally utilize their resource bandwidth deployed for managing agents and ensuring that the good performers remain on track. At the same time, laggards get additional attention to improve their output.

However, predicting an agent’s performance is a task that is far from simple. A variety of factors such as demographic and geographic spread, tradition, cultural differences, seasonality of income & expenditure pattern, etc., often affect an agent’s performance.

Machine Learning Assists in Identification

Today the advent of machine learning and deep learning techniques helps us analyze vast amounts of data and predict an agent’s performance by factoring in all available information. What looked like a challenge in the past - non-availability of agents' profile and performance data, drivers of enhanced performance, are all available with the insurers today and can enable successful implementation of the modern-day decision-making techniques. The data captured in reward and recognition platforms of insurers is helpful too in this analysis.

With the help of machine learning models, organizations are developing their pan India strategy and giving it a localized execution approach for a state/territory in moving the agents on the path of success. Interventions span the entire life cycle of an agent, starting from recruitment and training. Internal data is often supported by external data for enhancement.

These techniques have been successfully deployed in the Indian landscape and push up the industry's productivity and agent’s lifespan. Players playing the game of wait and watch have also started biting the bullet as they do not want to be left out in the near future when the environment is conducive for an aggressive push for sales by these agents.

Conclusion

In years to come, we will see a total makeover and transformation of how this channel works and delivers, but, indeed, it is going to stay, and insurers are investing and will continue to remain invested in this channel

An agent's success has a cascading effect. It brings cheers and smiles of hard faces on agency managers and the faces of the agent's families. The success stories have led to a paradigm shift in society's outlook on Indian Insurance agents. Many individuals have started venturing into the insurance solicitation business as a startup, giving flip and extra teeth to the agency channel.

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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