AI in insurance

How is the insurance industry making use of AI technology?

The present information age is possibly the most exciting period throughout human history, whereby technological innovations are moving at an incredible speed. The science-fiction technology in the past like autonomous cars, quantum computing, and artificial intelligence are becoming more practical – in particular Artificial Intelligence (AI). It is used across various sectors to improve workplace efficiency and augment simple tasks as humans do.

In this transformation, the insurance industry will undergo fundamental changes in each part of its value chain. Insurance will shift from its current state of “detect and repair” to “predict and prevent”. The speed of change will accelerate when insurers start to utilize AI technology to improve productivity, decision making, and customer experience, which will lead to lower costs. The impact will be tremendous especially on the following 5 key areas in the insurance value chain. 

insurance value chain graphic

Product Development

Customer expectations for products and services are increasing, it has become a necessity for insurers to have personalized, convenient, and affordable insurance products. Moreover, a broad range of new exposures is cropping up, such as cyber risk, the sharing & gig economy. With that being said, the evolving landscape is creating a huge opportunity for new insurance product development.

Insurers will leverage AI and Big Data to maximize the relevance, speed, and agility of product development. AI will be fed with a huge amount of data and eventually discover a pattern within the data to generate insights like demand forecasts and the type of insurance products (existing or new) that drive strong sales. This eliminates the whole process of market research or the need to seek insights from partners, brokers, and agents which could be time-consuming. As a result, AI enables insurers to continuously offer new insurance products that can consistently adapt to the new individual’s needs.

Distribution

Insurance distribution is highly complicated due to different distribution channels, brokers, online sales journeys, aggregators, online businesses, etc. In the pre-digital era, the distribution system was created following an agent model that requires agents to find customers themselves and process applications with massive amounts of paperwork. The internet shaped the new behaviour of customers, with an expectation of fingertip access to information and better product recommendation.

Insurers will apply AI to learn about the customer’s digital behaviour, communication history, and past purchases for advanced customer segmentation. Despite the rise of purchasing the policy online, the insights generated can move beyond digital space and impact physical agents because some customers still value human interaction. AI will improve the sales teams’ effectiveness at closing more leads and provide them with invaluable insights about their customers, making it easier to upsell or cross-sell other insurance products. For example, AI uses predictive analytics to target and rank leads based on their likelihood to close. This eventually helps the sales representatives to prioritize sales activity and work only on the most promising leads.

Underwriting

Insurance underwriting is the most complicated and manual process within the insurance process. Underwriters have to make insurability decisions based on a wide set of complex factors such as health, lifestyle, hobbies, and others. They are responsible to generate a quote for the premium that meets the risk level of the individual prospect to prevent the insurer from high losses. 

Therefore, insurers will make use of AI to develop a sophisticated and proprietary model for underwriting. AI enables large data sets to be processed in no-time, identification of ambiguities in the insurance application process, and group risks based on the past risk assessment data. By making assessment more precise, insurers create a better bindable quote of insurance products that fit the coverage needs and risk profile of customers. At the same time, it ensures healthy margins for every quote offered by the insurers. Thereby, creating an equilibrium balance of profitability and risk.

Claims Management

Historically, claims are the most emotional segment of the insurance value chain. It is the primary point where customer experience and loyalty collide with the insurer’s long-term reputations. To initiate a claim, customers are forced to file a claim and deal with multiple points of contact, which could take a long time to process. As for the insurers, it’s a cut from the profit for claims payout and additional resources are required to deal with fraudulent claims. 

Insurers can use AI to deliver a pre-assessment of damage evaluation and fraudulent claims before routing them to the claims handler. Simple claims and customer interactions can be processed by AI automatically in real-time, the remainder of more complex cases will continue to be handled by humans, who bring real empathy to the table. At the same time, AI can also provide enriched information with analytics-enabled dashboards to support humans on complex claim handling to quickly examine the claims and provide customers with an immediate resolution. 

Customer Service

Nowadays, insurers with high customer satisfaction and great customer service are much more likely to retain customers than those who don’t. It is because customers value great customer service more than ever before, even more than the settlement amounts. Therefore, it put insurmountable pressure on the insurers to distinguish their brands in this competitive digital space.

Insurers will use AI to change the way businesses respond to customer enquiries. It is particularly helpful in answering a bulk of low-level customer enquiries and checking billing information. It greatly reduces the time to respond and enables the support to be available 24/7. Besides this, AI also serves as an enabler instead of a total replacement to customer service agents. For example, AI collects data and uses it to identify the best customer service agent to address the customer’s needs. It will then provide the agent with useful background information before the customer interaction.

Making Transition with AI

Insurers need to understand that standing still is not an option, it’s a surefire recipe to be eliminated from the competition. As the bar rises across the entire industry to deliver greater customer experience, future-driven insurers can no longer be stuck in the 20th-century insurance model. With AI, insurers can upgrade the entire value chain by restructuring complex processes, simplifying product offerings, increasing policy flexibility, enabling digital connectivity, and enhancing distribution options. Although many unknowns lie ahead, insurers who take the necessary steps will be well-positioned to adjust and respond along the way.

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How tigerlab helps with AI

tigerlab as an API-driven insurance platform enables insurers the possibility to integrate with any 3rd party AI applications that are important to the business. It allows insurers to gather data from different providers into a single platform in real-time. So, are you ready to make the leap into AI? It’s easy to discover the power of AI coupled with a reliable insurance platform by talking to tigerlab today!