Leveraging AI and Predictive Models for Risk Analysis and Pricing

Digital Transformation, Insurance Industry News & Views - March 23 2022

Karen Furtado, Partner, Strategy Meets Action, a ReSourcePro Company, is a well-known authority on insurance technology and how it fuels transformation within insurance companies. Her focus is helping insurers prepare for the future of the industry through the decisions they make today. Karen’s deep understanding of how to effect change guides insurers in the development and implementation of their transformation roadmaps. Her comprehensive knowledge stretches across foundational technologies such as policy admin, billing and claims, the implications of insurtech, and enhancing adaptability and flexibility in a changing market. For more than 30 years, Karen has held leadership positions across the insurance industry. In this article, which originally appeared in Chisel AI's inaugural Commercial Insurance Underwriting Priorities eBook, Karen connects the dots between Artificial Intelligence (AI) and improved risk analysis and pricing.

Almost everyone will agree that the pace of change the insurance industry is operating within continues to accelerate. As new products and services are brought to market, customer experience is redefined, and operational efficiency is gained as transformational technologies advance. Commercial lines insurers are looking to data, analytics, and AI to address specific business needs. These include:

  1. Reducing or supplementing data entry
  2. Verifying risk appetite
  3. Leveraging new data sources, scores, and models to support straight through processing
  4. Leveraging AI and predictive models for risk analysis and pricing

Karen Furtado Quote LinkedIn

When looking at the changes taking place in commercial lines underwriting, one needs to view the shifts based on the segment, with distinct differences for small, middle, and large markets; specialty; workers’ comp; and other areas.

  • Small commercial underwriting continues to transform and advance the levels of straight through processing across all lines while simplifying the submission process by reducing the data collection fields, using new data sources and new models, and providing digital engagement experiences in sales and service for both the agent and policyholder.
  • The middle market is looking to automate the ingestion of the email – pdf submission process with a variety of AI tools that include RPA, NLP, and machine learning to advance risk analysis with new AI tools and provide backend automation on policy contract comparisons.
  • Large complex risks and specialty lines often have massive amounts of data to ingest for risk assessment, including both unstructured and structured data in many formats. The ability to capture and extract data, recognize forms, and organize the data for underwriters is becoming essential.

Recent SMA research finds that 87% of commercial lines insurers are investing in technologies in the AI family. Most of those who are not investing are interested but are smaller and lack the budget at this time. Insurers especially see potential in leveraging AI for unstructured data, with 63% of commercial lines insurers citing this as an area of top potential. From the people, process, and technology viewpoints, the wide range of AI capabilities – RPA, NLP, machine learning – all will play major roles in underwriting transformation.

Read the Underwriting Priorities eBook

For more insights on the digital evolution of commercial insurance underwriting, grab your complimentary copy of the 40-page Underwriting Priorities eBook. Thirteen industry leaders, analysts and insurtechs including AF Group, Celent, Marsh, Novarica, and Zurich North America discuss how the commercial lines underwriter of the not too distant future will be much more data-aware and digitally-enabled than ever before. Read the eBook

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