Insurance Thought Leadership | Top Problems That AI, ML Help Solve
The global life insurance and retirement industries face an inflection point due to the convergence of challenging economic, technological, competitive, and societal headwinds. Going digital has been a top priority, as it helps reduce cost and enhances customer experiences. Digital transformation has led to the increasing adoption of predictive analytics, artificial intelligence, and automation in various business functions. According to McKinsey estimates, the potential total value of AI and analytics across the insurance vertical is approximately $1. Soon, AI will be deeply embedded into the insurance value chain, providing unmatched power to insurers:
- Automating manual processes in underwriting.
- Eliminating errors and inefficiencies in claims processing.
- Enabling predictive insights to deliver superior outcomes.
Our CEO, Dr. Ryohei Fujimaki, Ph.D., discusses the top challenges that AI and machine learning will help solve in the insurance industry, including:
Underwriting and pricing: The underwriter needs much information for commercial property insurance, such as occupancy, data on adjacent buildings, loss estimates, and typical hazards. According to a McKinsey report, claims for personal lines and small-business insurance will be fully automated, enabling carriers to achieve straight-through-processing rates of more than 90% and dramatically reducing processing times from days to hours or minutes.
Claims Processing: The process will now be automated, relying on IoT sensors and real-time monitoring to prevent incidents from happening and sending notifications for critical events requiring immediate attention. As insurance carriers get better at leveraging data and implementing predictive analytics, the focus will shift from product-led to customer-centric models. The insurance industry’s adoption and investment in digital capabilities to unify data, advanced analytics, and people will ultimately make the industry more agile, efficient, and transparent.
Read the rest of the article at Insurance Thought Leadership. @ITLupdates
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