We’re diving into how algorithmic underwriting - or the increasingly prevalent 'smart follow' - can be enabled despite the lack of defined digital data standards in complex risk markets.
The final stage of the data lifecycle in insurance is decision making. Data is used in decision-making processes carried out by both human underwriters and AI software and is used to inform decision making at every stage of insurance.
We’re diving into how algorithmic underwriting - or the increasingly prevalent 'smart follow' - can be enabled despite the lack of defined digital data standards in complex risk markets.
If data extraction in insurance is the first stage of the data lifecycle, then the next stage has to be data augmentation.
The insurance industry is undergoing a digital transformation which is led by AI and machine learning technology.