Standard Machine Learning (ML) has already achieved considerable success in many sectors such as healthcare, marketing, and finance including insurance. However, one cannot define standalone ML as fully intelligent system as it still relies on human experts to perform the following important tasks. Let’s assume we deal with motor insurance pricing problem. The pricing department uses several machine learning algorithms such as GLM or neural networks to model claim frequency. The traditional project workflow is much reduced with AutoML techniques.
Why Automated Machine Learning is
important for insurers?
Solved hiring problems
Current high demand for data science talents and shortage on the job market is solved with usage of automated solution.
Reduce process complexity
AutoML allows IT department and actuaries to reduce the number of repetitive tasks by automating data cleaning and model build processes.
Frees time for more analysis and validation, especially for stakeholders’ and regulators’ stress scenarios.
Actuarial processes in insurance and reinsurance companies are better managed due to simplified process workflow.