Four ways to win insurance distribution with artificial intelligence

Digitalization has put the customers in the driver’s seat of insurance distribution. Carriers must take a proactive stance on this phase of the insurance value chain, meeting customers where they are. But a recent survey found a massive gap between customer expectation and carrier approach. Could artificial intelligence (AI) address this? We discuss four use cases of AI in insurance distribution.

AI has incredible potential across the entire insurance value chain, right from marketing to underwriting and claims management. The industry is growing at a rapid clip, expected to cross $2.5 billion by 2025. This milestone indicates a compound annual growth rate of 30.3% between 2019 and 2025. And the potential of AI goes beyond underwriting or claims approval; it could transform the sales and distribution phase of the insurance value chain as well, gaining from sophisticated AI algorithms available in the market today.

The Challenges of Traditional Distribution

In the pre-digital world, insurance customers would visit a local carrier or contact a financial planner to explore policy options. More often than not, there would be a leading carrier for a specific product or in a localized market. Based on the information the customer provided, the carrier would perform underwriting activities and share a quote.

Digitalized insurance distribution systems upended this picture. Today, nearly every carrier has an online portal that allows customers to peruse their product and service catalog, before making a decision. Research suggests that as many as 71% of customers engage in some form of digital research before buying a policy. There’s no commitment involved: if the offering seems unsatisfactory, customers can quickly navigate to another provider’s online store and look for a more effective alternative.

This shift in consumer behavior prompted significant disruption in the insurance sector, one that put customers on the driver’s seat. As a result, carriers faced the following challenges:

  • A dip in customer loyalty - With a plethora of options opened up, the rate of switching increased, and loyalty levels took a significant hit.
  • The criticality of brand awareness - Leadership in a specific product segment or region was no longer enough, with customers now aware of career brands previously outside their line of sight.
  • Rapid market saturation - Sectors like auto and property & casualty (P&C) saw a decline in the number of new customers acquisition every year, owing primarily to market saturation.
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All of these forces makes it critical for carriers to reimagine their distribution networks and take a proactive stance. Instead of only launching an online catalog and waiting for aggregators to bring in customers, insurers need direct digital channels to drive sales. This business need for digital channels is where AI plays a massive role.

READ MORE: AI & Machine learning in P&C insurance: Technology, use cases, and opportunities

Four Use Cases for AI in Distribution

Digital technologies such as optical character recognition (OCR), machine learning (ML), and natural language processing (NLP) can help insurers gain from a customer’s digital behavior. This payoff points to a massive opportunity – with so many prospects researching digital channels, there is a vast repository of customer data that the AI engine can leverage, which can empower the distribution to make smarter decisions. The principal use cases include:

1. Advanced customer segmentation

Market saturation means that there’s only a small pool of customers joining the insurance buyer pool every year. Carriers have no option but to attract and capture customers with existing policies, and AI could be a huge help to achieve this. Third-party databases and social media can furnish prospect audiences with advanced segmentation, and each segment’s preference would decide the selection of the most effective distribution channels.

2. Adaptive channel allocation

Given that there are multiple channels of distribution at play, carriers must zero in on the best-fit distribution channel for every customer. AI’s ML capabilities can make this happen by learning from the customer’s digital behavior, past purchases, interaction history, etc. These insights could even go beyond the digital world and impact physical agent allocation as well. Despite the rise of online policy shopping, insurance customers continue to value human interactions. AI can help optimize workloads and formulate schedules that would match human agents with high-intent prospects.

3. Demand analysis and product configuration

In today’s dynamic insurance landscape, analyzing demand to detect new opportunities is vital. AI can process vast databases of historical records to predict future demand, analyzing demand areas to specific channels. For example, millennial customers could be forgetting to renew their insurance policies. At the same time, the AI engine infers that millennials customers spend a large portion of their workweek on LinkedIn. By using this correlation, carriers can leverage LinkedIn ads to distribute a brand-new policy renewal offering explicitly.

4. Automated policy recommendations

This use case applies AI’s capability to understand natural languages like English. The customer would answer a set of pre-defined questions, and AI would convert the responses into a machine-readable format. The inputs would then be analyzed to extract sentiment information: What is the customer’s real risk appetite? What are the motivations behind the purchase? The answers to these questions would allow policy recommendations to become more refined and intuitive, even without the intervention of a human agent.

Why Insurers Can’t Afford to Ignore the Power of A

To inspire and retain customer loyalty, the strategic intervention of AI will prove vital. As the industry currently stands, there is a clear gap between customer expectations and the carrier approach – especially when it comes to distribution. A recent survey found that 65% of insurers are focused on answering queries on Facebook. Yet, just 8% of customers said Facebook was among their top #2 preferred channels. Meanwhile, chat and email are deprioritized by insurance carriers, despite 49% of customers operating on each of these channels.

READ MORE: Case study | Top insurance firm leverages Birlasoft's AI-based solution to augment underwriting and drive growth

Meeting customers where they are should be a core objective for modern-day insurers. AI technology embedded in distribution systems can help attain this goal. Consider the case of Insurify, an AI auto insurance startup that matches customers with insurance carriers, streamlining distribution. Innovations like this are the future of this industry, paving the way forward.

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