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  • Writer's pictureRavikiran Papthimar

Artificial Intelligence (AI) & Insurance

New age technologies such as AI, ML & NLP are poised to reimagine the entire insurance lifecycle from customer acquisition to claims processing.

The Artificial Intelligence (AI) market was valued at USD 16.06 billion in 2017 and is expected to reach USD 190.61 billion by 2025, at a CAGR of 36.62% during the forecast period. Asia pacific region would exhibit the highest CAGR of 59.8% during 2018-2025.

KPMG’s Insurance practice estimates that AI will reduce accident frequency by 80% by 2040. This will result in a potentially drastic reduction in loss costs and premiums.

Many insurtech are leveraging AI technologies to slash costs, speed response times and improve customer service. Here are some of the top 10 use case where AI can be leveraged in Insurance

  1. Usage Based Insurance / Behavioural Policy Pricing: IoT sensors will provide personalized data to pricing platforms, allowing safer drivers to pay less for auto insurance and people with healthier lifestyles to pay less for health insurance.

  2. Customer Experience: AI will enable a seamless automated buying experience, by leveraging on customers’ geographic and social data for personalized data.

  3. Customized Claims Settlement which is faster: Virtual claims adjusters along with Online Interface will make it more efficient to settle and pay claims following an accident. This will also help in simultaneously decreasing the likelihood of fraud.

  4. Chatbots/AI assistants: Having Chatbot to respond to customer and also settle claims without human intervention will create an Insurance experience that is fast, simple and delightful.

  5. Re-imaging Claim Processing: Use image recognition software or computer vision to settle auto claims without the need for a visit from an adjudicator. Home sensors, drones and smart devices will often generate a first notice of loss (FNOL) before the customer needs to contact the insurer

  6. Better Claim management process: AI can identify patterns in data and help identify fraudulent claims in the process. Using machine learning capabilities business can capture patterns and traits that would be invisible to the human eye

  7. Customer Care done right: Use AI Capabilities to improve the process of Customer care during the process of filing a claim with the call center team

  8. Customer Segmentation: AI perform customers’ segmentation according to their financial sophistication, age, location, etc.

  9. Customer Lifetime Value Prediction: Using AI algorithms to predict the likelihood of the customers’ behaviour and attitude, maintenance of the policies or their surrender.

  10. Claim Prediction: Forecasting the upcoming claims helps to charge competitive premiums that are not too high and not too low. It also contributes to the improvement of the pricing models. This helps the insurance company to be one step ahead of its competitors.

McKinsey found that 82% of enterprises adopting machine learning and AI have gained a financial return from their investments.

At the same time one of the key concern introducing new technologies will be in convincing the public that automation isn’t simply a Trojan horse for denying their claims — a worry that 60% of consumers have expressed about purchasing coverage via chatbot, according to a recent survey by Vertafore.

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