Despite a dozen years of increasing investment in machine intelligence (MI) (regression, non-parametric statistics, machine learning, and artificial intelligence), financial services enterprises (banks, insurance companies, and asset managers) have generally failed at implementing productively transformative MI-enabled end-to-end systems.

While a few narrowly targeted implementations have seen limited success, most attempts at enterprise transformation within financial services, generally and insurance, specifically have not succeeded.

This presentation will discuss approaches to address this enterprise MI failures with four AIs not discussed enough: 1) Augmented Intelligence; 2) Intelligent Automation; 3) Assessed Intelligence; and 4) Adaptive Intelligence. Anecdotes and recommendations will be framed predominantly in the context of insurance-company-related use cases, challenges, and potential.

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