What are the potential use-cases for ML and DL in the insurance sector , and what obstacles still exist between these technologies and broader adoption ?
ML & DL
Machine learning and deep learning in the insurance space
What are the potential use-cases for ML and DL in the insurance sector , and what obstacles still exist between these technologies and broader adoption ?
WRITTEN BY : ALEX CLERE
Machine learning and deep learning have really taken root in the insurance sector over the last couple of decades , building on the foundational layer set by artificial intelligence ( AI ) technologies to better contextualise data and create dataled outcomes .
The result is a gradual automation of the insurance value chain , helping to remove manual effort from previously arduous and cumbersome tasks – and helping insurers to realise tangible gains across risk , claims speed , and fraud prevention .
Indeed , machine learning and deep learning are such promising technologies that McKinsey estimates that the whole sphere of artificial intelligence will drive value within the insurance industry of up to US $ 1.1tn a year .
What ’ s the difference between ML and DL ? Before we can fully understand the advantages that machine learning ( ML ) and deep learning ( DL ) can bring to the insurance industry , it helps to be fully cognisant of
76 September 2023