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The Top 3 Emerging Trends for Agent/Advisor Analytics Using AI

In order for regional insurance carriers to continue to grow, the acquisition of new customers and retaining existing customers is imperative. Because of this, identifying cross-sell and upsell opportunities has never been more critical. One of the significant challenges carriers face when growing their company is analyzing and managing the capabilities of their agent distribution channel.

Consumers who purchase their coverages through agents expect personalized service and help when filing claims. Therefore, the carrier expects its agents to pro-actively contact their customers about new coverages or price changes for existing policies. These agents should also review the customer’s coverages before renewal to suggest changes or upgrades.

The question many insurance carriers have is: “How can we analyze and manage our network of agents to ensure they are taking the right actions to acquire new customers and retain existing ones for us?”

This article is the first of a series that will address how predictive and sentiment analytics can help insurance companies improve the effectiveness of their agent distribution channel.

Trend #1: Understanding Agency Sentiment

In addition to understanding the sentiment of individual agents and advisors, insurers can benefit by understanding what the sentiment is at any given time of an entire agency. The sentiment of agencies across a defined geographic region or by individual products can be analyzed on a real-time basis.

Sentiment analytics can play a major role in identifying an agency that is at risk of underperforming. For example, if the overall sentiment of an individual agency should drop significantly, the negative impact for the insurer can be far more significant than that of one agent.

Trend #2: Increasing Agent Productivity

One area where analytics can have an immediate impact is predicting and improving agent productivity. Currently, many insurance carriers can only analyze agent productivity based on the premiums written and the loss ratio of the agency.

By using the combination of internal and external data for predictive analytics, insurers can now have a better understanding of the sentiment of their agents, their market potential, as well as evaluate their agent’s performance for a particular line of business.

Using predictive analytics provides insurers with the opportunity to proactively engage with individual agents and advisors to help improve their productivity.

Trend #3: Managing the Agent/Advisor Network

Maintaining a network of agents involves attracting new agents, working to retain the higher-performing agents, and not renewing underperforming agents. Predictive analytics can be used to identify, retain, and optimize the agent distribution channel.

Identifying “Ideal” Agents and advisors

Predictive models can be developed based on what the “ideal” agent is for an individual insurer. These models take into consideration specific geographies, policyholder demographics, and products offered by the insurer.

Retaining Existing Agents and advisors

By using existing data that insurers have today, variables can be identified to develop predictive models to determine who the best performers can be within a specific geographic or demographic segment. Insurers can then focus their efforts to support these agents pro-actively.

Underperforming Agents and advisors

By measuring and tracking the sentiment of agents over time, predictive models can be implemented to determine which agents are not improving their performance. The addition of this information can be useful to the insurer's decision-making process regarding the renewal or non-renewal of an underperforming agent.

Conclusion

Sentiment and predictive analytics can provide insurers a better understanding of how their agent/advisor network feels about their company and products.

Predictive analytics can help insurers proactively address agent productivity as opposed to only analyzing productivity based on premiums written and loss ratios. By taking a proactive approach to assist agents, insurers can better understand if agencies are receptive to improving their overall performance.

Successfully managing an agent/advisor network consists of identifying “ideal”  agents, retaining the higher-performing agents, and addressing non-performing agents. Once these “ideal” agents are on-board, insurers can stand out from other carriers by proactively supporting these agents and retaining those agents.

Sentiment analytics is a non-intrusive way to help insurers understand what the sentiment is of an agency as a whole in addition to individual agents and advisors. The sentiment of one or more agencies can be analyzed across a geographic region or by individual products.

In our next article, we will focus on understanding individual agent sentiment as well as the sentiment of the entire agency.

Interested in learning more about how Aureus can help you improve the effectiveness of your agent distribution channel? Click on the link below.

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Anurag Shah
Anurag Shah
Anurag Shah is CEO and co-founder of Aureus Analytics. He was the founding member and CEO for EdVenture prior to joining the leadership team at Omnitech, where he served as the COO and Head of Global Operations.

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