PriyaPatel
TLDR:
Key Points:
- AI bias can affect algorithm results
- Gen-AI combines large datasets for predictive analytics
Artificial intelligence (AI) in insurance plays a crucial role in improving trust, accuracy, and personalization for customers. AI bias, which occurs when algorithms produce prejudiced results due to erroneous assumptions in the machine-learning process, is a key consideration in ensuring the accuracy and fairness of AI-driven processes. Gen-AI, a form of AI that combines large datasets with enterprise and personal data, is elevating the quality of predictive analytics in the insurance industry.
Knowledge-based generative artificial intelligence has shown the ability to quickly answer questions and execute complex workflows, as demonstrated in a study by McKinsey & Company. By leveraging AI technologies, insurance companies can enhance customer experiences, improve accuracy in risk assessment, and personalize products and services based on individual needs.
Incorporating AI into insurance processes can also help in managing complex claims and litigation, as well as enhancing rate planning and customer engagement. AI opens up new opportunities for insurers to streamline operations, enhance data analytics, and stay competitive in a rapidly evolving industry landscape.
