ML & DL
“ There is a role for humans and machines in any business process ; instead of man versus machine , the approach should be man and machine ”
OLIVER TEARLE HEAD OF INNOVATION TECHNOLOGY , THE AI CORPORATION
the differences between the two . Both begin with artificial intelligence ( AI ) – which is obviously the ability for computers to process and contextualise data in the same way a human could .
Machine learning utilises AI to make data-driven predictions based on the data and learned experiences . In contrast , deep learning is an additional layer of ML where algorithms attempt to model high-level abstractions in data .
One use-case that already exists for deep learning is in improving the accuracy of risk forecasting , particularly in insurance lines where there is a lot of structured and unstructured data together – like auto insurance , for example .
LexisNexis Risk Solutions surveyed more than 300 insurance professionals in the fields of data science , analytics , actuarial , technology , underwriting , product management and claims working for some of the 100 leading insurance carriers in the US .
The findings from that poll show that three-quarters of insurance-industry respondents think AI and ML can provide a competitive advantage to carriers , while more than six in 10 respondents ( 62 %) work at companies that have already started to adopt AI and ML . insurtechdigital . com 79