Implications of AI in the Insurance Industry

AI transformation areas

Pricing and underwriting

Pricing transformation may involve adopting new underwriting and risk monitoring approaches in order to improve manual processes like document reviews or even eliminate them altogether. Automation and data analytics can also be used to increase pricing efficiency and accuracy, while sophisticated, real-time risk monitoring improves capital efficiency in back-testing and model validation.


Insurance products are complex but AI can be used to simplify the sales process and even open up opportunities in emerging markets through digital and scalable channels. Approaches like advanced visual recognition and third-party app integration can be used to improve and expand distribution strategies for every branch.

Claims and costs

Claims and costs professionals could use AI to create new workflows that will be more accurate and responsive to customer needs. For example, response processes (i.e., for claims adjudication and personal data administration) could be automated. Additionally, new analytical models and external data can be used to reduce fraud and the substantial costs associated with it.

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