The Meta Trends in Actuarial Science

The fields of statistics, data analysis, and probability are transforming. Thanks to the analytic capabilities of big data, artificial intelligence is becoming more commonplace in these fields. In other words, we’re seeing the rise of meta trends in actuarial science. 

Here are some examples of current meta trends of actuaries:

1. Data Science Tools

Actuaries are benefiting from the development of better tools for data science. For example, the open-source R programming language has become popular due to its ability to handle large datasets and its wide range of statistical packages. In addition, Python is gaining popularity because of its user-friendly syntax and robust data analytics libraries. 

2. Open Data

The rise of big data has made it possible for actuaries to access more data than ever before. In particular, open data — data that is freely available for anyone to use and reuse — is becoming increasingly important. Actuaries are using open data to develop new products, improve existing products, and even create entirely new businesses. 

3. Machine Learning

Machine learning is a method of artificial intelligence where computers can learn from data without being explicitly programmed. Actuaries are using machine learning to develop new pricing models, predict customer behavior, and even automate the underwriting process.

These are just a few examples of the meta trends currently shaping actuarial science. As the field continues to evolve, we can expect to see even more exciting changes in the years to come.