--With many traditional life insurance agents retiring, AI can step into the gap and present customers with the right proposal at the right time.
--AI-powered chatbots can also sweeten the customer experience by providing 24/7 customer service, answering questions and resolving issues in real time.
--Insurance agents can also use AI to refine their messaging process across different media channels, as well as to reduce fraud.
Breakthroughs in machine learning and AI mean that insurers can tap into insights from vast troves of data and refine their operations on a more granular level than ever before. Consequently, insurance companies are finding new ways to enhance the customer journey, streamline operations and make better decisions.
Machine learning and AI permit insurers to employ large data sets that would be a nightmare for humans to parse. According to Dror Katzov, CEO of Atidot, many insurance companies only use 20% to 30% of their data. There is much more that could be used to improve the customer experience, from digital policy delivery to better customer engagement and claims management.
AI can help insurers identify customer behavior and adjust product offerings accordingly. Just consider what it can do for life insurance. With many traditional life insurance agents retiring, there is an opportunity for AI to step into the gap and present customers with the right proposal at the right time. AI can continuously model the different situations that consumers face and provide better risk models to help insurers make savvier decisions, which opens up the means for more dynamic pricing. For example, an AI model could be trained to recognize if a person has started going to the gym and offer them a better insurance rate for adopting a positive lifestyle change.
AI-powered chatbots can also sweeten the customer experience by providing 24/7 customer service, answering questions and resolving issues in real time. This frees customer service agents to handle more complex issues. Moreover, AI can also personalize product offerings based on customer data, making it easier for insurers to provide the right coverage at the right price and to produce client-advocacy documents, such as cover letters, in much less time.
Insurance agents can also use AI to refine their messaging process across different media channels. Jeff Root, managing partner at DigitalBGA, says the assistance offered by AI will obviate the need for many types of instructive classes. “You should never have to buy a course again,” Root says. “All the courses selling you Facebook ads for any sort of life insurance… you can get the information online through this [Chat GPT] AI bot.” Aside from helping businesses generate leads through social media platforms such as Facebook and Google, AI can also help businesses be more agile and responsive to changes in the market.
For ages, fraudulent claims have been the bugbear of the insurance industry. (Florida, for instance, has been a bastion of fraudulent claims – so much so that many insurers have exited the area.) AI may help to remedy this situation by improving fraud detection, enabling insurers to quickly identify suspicious claims and prevent fraud before it occurs. Additionally, AI can enhance risk management by providing more accurate pricing and underwriting decisions, resulting in better outcomes for both insurers and policyholders.
All that said, there are challenges associated with the adoption of AI in the insurance industry. It has long been a burden for the industry to establish trust with the customer; AI can help automate more processes, but human oversight is still essential.
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Ethical and legal considerations constitute the main challenges surrounding AI. There are valid concerns about how AI is used to price insurance policies and how it may lead to unfair discrimination against certain groups. The European Union's General Data Protection Regulation (GDPR) requires companies to explain their decision-making processes when using AI and to provide individuals with the right to contest decisions made by automated systems.
Another challenge is the potential for bias in algorithms. AI systems learn from the data sets they are fed, and if that data contains biases, the AI system will also be biased. For example, an AI system may learn that individuals living in a certain ZIP code are more likely to make fraudulent claims, leading to discriminatory pricing or coverage decisions.
Privacy is also a significant concern. As insurance companies collect and analyze large amounts of data, it's important that this data is stored securely and that customer privacy is protected. Steps must be taken to prevent data breaches and exposure of sensitive information.
Finally, the effectiveness of AI in insurance depends on the quality of data that is being used. If the data is incomplete, inaccurate or outdated, the AI system will not be able to make accurate predictions or provide useful insights. For instance, although ChatGPT–the most popular AI chatbot in the world today–can deliver fast results, there is always the possibility of it offering up erroneous information. On a positive note, Nvidia has developed a new way to keep AI from "hallucinating," i.e. offering up incorrect or inappropriate content.
AI's potential for innovation is exponential. AI can help insurance companies meaningfully and efficiently use more of their data, improve customer engagement and refine their targeting process. Nonetheless, businesses interested in using AI should closely monitor developments in the space and be cognizant of the challenges associated with its adoption. With scrupulous implementation and judicious oversight, AI can supercharge the insurance industry and provide better services to customers.