Tips on whether data scientists can replace actuaries

It is often argued that however sophisticated computer systems might get, they will never be completely autonomous and eliminate the need for human intervention. How true is this argument though? With the advent of robots and automated computer systems, do humans stand a chance in the professional world?

One field where the debate of whether automation of data science could replace the need for human intervention is in the finance department and the job of actuaries to be specific. Actuaries are trained professionals whose task is to analyze financial data, determine risks, probabilities and uncertainties in the future.

By combining Mathematics, statistics and various theories, the actuaries are able to draw insights from financial data and predict the possibilities of certain financial circumstances materializing. Actuaries have been instrumental in the insurance field, in banking institutions and even in the stock market. Is their jobs on the verge of being gobbled up by automated data science?

In this Guttulus blog post, we are going to look at the possibilities of data science replacing actuaries by comparing the differences and similarities in the way actuaries and data scientists works. At the end of the day we will make a conclusion on whether data science can truly replace actuaries;

Tips on whether data scientists can replace actuaries

Data scientists and actuaries share skill sets

Data scientist and actuaries have a lot in common in terms of skill sets. They both need proficiency in mathematics, statistics and an eye for detail. The only difference is that computer scientists have more knowledge in the computing side of things.

This therefore means that data scientists can competently handle most of the tasks which the actuaries handle. They will treat the financial data as any other set of data and draw insights from the data to try and make predictions from the insights.

Differing responsibilities

Whereas the skill sets of data scientists and actuaries are almost similar, their professional responsibilities are almost worlds apart. Actuaries are very particular about what they do- they use financial data to estimate the cost of losses, predicting likelihood of losses or profits and advising companies on how to best place themselves to make the most of the future.

Data scientists on the other hand can literally work in any field and don’t have defined roles and responsibilities. Theirs is to solve problems by analyzing data sets and trying to discover hidden patterns behind the data.

Data scientists don’t do predicting a lot

The other difference in the responsibilities of actuaries and data scientists, is the fact that the latter don’t do predicting a lot. They are expected to draw insights from real time data and make sense of that data. Actuaries on the other hand are expected to use real time data to try and predict possibilities of the future.

Automation changes the complexion completely

When talking about data science automation, the complexion changes completely. With automated data science, the future of actuaries begins to look bleak. Computer scientists are helping design automated systems which in the near future, will be used in areas such as finance and do the job of actuaries better than them. Here are some of the reasons why automated data science is better than actuaries;

Computers have proved to be faster than humans

Trials to automate some of the basic elements of data science have proven that automated data science processes are way quicker than what humans are capable of doing with the same set of data. Who doesn’t want to save time while processing and analyzing a set of data?

Instead of hiring humans, employers will opt for automated systems instead.

Automated data science is more accurate

Provided the training is done properly and using the right software on appropriate hardware, automated data science is way more accurate than what humans are capable of. A research by the MIT Big Data Analytics, showed that the accuracy level of a properly trained system is in the neighborhoods of 96% in terms of accuracy.

Who doesn’t want an accurate assessment of financial data? Banks and insurance companies sure do.

Automation improves prediction abilities of systems

In predictive analytics, the time and effort spent to predict or forecast trends using a given set of data is reduced by a very big margin. Although systems haven’t been automated to be used in prediction, tests point towards very successful and accurate automated predictor systems.

Since actuaries are expected to make predictions in the sensitive field of finance, employers will always opt for better and more accurate predictions from automated data science systems.

So, will data science replace actuaries?

For now, actuaries can rest assured that their jobs are secure but only just! The moment complex automated data science systems debut into the world of finance, the complex will completely change. Only those actuaries with knowledge on how to work in conjunction with these sophisticated systems will be considered for jobs.

Guttulus would therefore advise actuaries to learn new skills especially in AI and machine learning to ensure their job security.

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For more tips and guides on data science, talk to us here at Guttulus and read our blog on a regular basis. Give Guttulus a call today on data science and we will gladly be of service to you.