3 Ways AI is Giving Traditional Insurers a Competitive Edge
Insurance carriers in the US and globally are facing pressure from insurance startups like Lemonade and Metromile. These new entries into the insurance space are providing customers with a completely different digital experience than they were used to from traditional insurance providers. However, there is one area that companies who have been around for over a century are way ahead and that is in data. Collected over years, it is a goldmine of information. If it is properly utilized, it will keep the advantage on their side. They can use data mining with AI and Machine Learning to know more about their customers and develop better product offerings, personalize the customer journeys and vastly improve claims processing and customer experience. All this brings with it improved operational efficiency and cost savings. AI can lead to a $390 billion cost-saving for insurers by 2030 (NEXT)
These are the 3 areas where AI is finding the highest adoption. This is only the tip of the iceberg and there are more insights that can be found here.
1. Insurance carriers are increasingly using AI to automate mundane tasks
The insurance sector, similar to banking, has a large amount of documentation on both the transactional and administrative sides. This is repetitive and mundane, even though it is most important. 15% of an employee’s time is taken up in such repetitive tasks and the risks of human error are high because of the tediousness. The bright side of this is that insurance documentation is based on specifically defined rules and so lends itself to rule-based software like robotic process automation or RPA. When RPA is coupled with intelligent automation, then even exceptions can be easily handled. AI and RPA are also being used in intelligent chatbots to improve customer support as well.
2. AI improving underwriting speed and customer personalization
AI plays a crucial role in the underwriting process by generating risk models, calculating premiums, and checking prices. The automatic calculations are accurate enough to ensure that a customer finds the cost transparent. Insurance underwriting automation has found greater acceptance in the retail line with instant quotes and attractive prices that retain customers. In the commercial lines, manual underwriting is still dotted with a load of physical and digital paperwork. By using artificial intelligence systems that assess every application against billions of data points from both internal and external sources, underwriters get higher visibility into risk factors for each client.
3. Artificial intelligence helps in improving claims procedures
Claims processing is a highly nuanced process but it also includes time-consuming administrative work. Insurance carriers have an abundance of historical data that can be used to train artificial intelligence systems to pick up these nuances at a higher accuracy than a human agent can. Further, the AI systems only get better with time as they apply their learning to signal red alerts when they identify fraudulent claims. The whole process starts from the time a policyholder files a claim. RPA can extract the information from emails, paper documents, etc, and fill in details into claims forms. Mundane work that need not be done by a human. Cognitive bots then process the claim and if all is right it will be approved and sent for payment clearance. High-value claims and those with red flags will be moved to a human agent. In this way, the claims process is streamlined for speed and accuracy and human agents focus on more valuable usage of their time.
