hyperexponential, which offers a SaaS pricing platform for insurers, has released a new report on how actuaries can do more with AI.
It stated that while machine learning has been a major talking point for many years, actuaries are not really using it. It said, “When I ask around in my network of actuaries, I find that the interest in Machine Learning is limited. There are over 94,000 actuaries worldwide, according to LinkedIn, yet only 2,300 have the term “Machine Learning” on their profile.”
hyperexponential highlighted that there are a lot of similarities between actuaries and machine learning specialists. For example, both deal with linear regression and both are experienced with R programming. Despite this, actuaries are slow to adopt machine learning.
One of the main reasons is that machine learning in insurance carries high risk. It stated that while they boast more accuracy, better data processing, trend recognition and much more, there is still added risk when using the technology. One key example of this is AI bias or the technology simply making a mistake due to incorrect data.
However, hyperexponential reduces this risk as it ensures the machine learning methodologies are explainable.
Another hurdle is that actuaries need more training to understand and use the technology. However, hyperexponential states there are countless resources that can help an actuary understand the basic introductory material through to more in-depth learning.
It added, “Academic research can sometimes be hard to understand, but many digestible alternatives exist. Google’s TensorFlow guidance documentation has grown immensely over the last couple of years, and it’s now possible to build your own Recurrent Neural Network just by following a step-by-step guide.”
The next barrier is a lack of demand for machine learning models. hyperexponential stated that it is easy to lose motivation for implementing machine learning if there aren’t any ideas for additional research. It said, “Think harder; there is almost certainly something else you could try if you have a bit more time to invest in the exercise, and if you’re stuck, there’s probably some deeper training you could do. Talk about it with other experts. You may just stumble across a gold mine if you hunt for ideas because there are likely to be a range of competitive advantages from finding a model that is more accurate, more efficient, and makes better use of your data or delivers a better experience.”
hyperexponential concluded, “With all of this in mind, I am in no doubt that we as actuaries must press ahead and continue our learning and innovation in emerging technologies like Machine Learning and AI. Actuaries are ideally placed to take advantage of the AI revolution. We have the skills and data, and most of us enjoy the process.
“There are competitive business advantages, and if anything, it’s fascinating to watch what robots do in different situations, especially when they are so naive about the human world. Who knows, maybe one day, an AI will replace most of my job, and perhaps they’ll write an article about encouraging greater use of humans.”
Read the full report here.
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