Guest blog: How machine learning can better equip insurersFrom simple one-way analysis to generalised linear models (GLMs) and data enrichment, the insurance industry is still evolving. Machine learning is the next step. It’s already transforming major industries such as medicine and entertainment, as well as the judiciary system, and we can learn lessons here.

Working with artificial intelligence and machine learning technologies forces you to think and learn from what’s been done in other industries. You need to be able to extrapolate from one industry to another. Data extraction used to be impractical or prohibitively expensive but today, intelligent cognitive systems and cheaper storage make it much more available.

Is it coming after our jobs? No, in a nutshell. Machine learning doesn’t replace actuaries and statisticians: it simply becomes another tool to help them work more effectively.

It will help us make better use of the data we already have, using more variables and more complex algorithms. It will improve decision making and our understanding of customers by giving us more accurate predictive models. It will help us to better tailor products and add-ons that meet customers’ needs. In the telematics space, machine learning can help improve the calibration of telematics scores and make sense of all the data coming out of the complex internet of things (IoT).


It’s only a matter of time before this technology reaches the insurance industry. With the right investment and stakeholder buy-in, we can stop trying to shoehorn everything into GLMs and embrace machine learning as an effective new tool.

For industries that embrace machine learning, the future will depend on how well they marry its predictive power with old-fashioned human wisdom.



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