A Business Strategy for Insurance Companies Using Deep Learning for Risk Assessment and Mitigation

An explanation of the model's projections that is straightforward and easy to understand is beneficial to stakeholders, financial institutions, and regulators. Several distinct kinds of tree-based classifiers, including deep neural networks (DNNs), were pitted against one another in this research project. This study's objectives were to (1) classify insurance risk based on historical data and (2) give the appropriate model for risk assessment in order to enhance the risk assessment capabilities of life insurance companies through the application of predictive analytics. The objective was to implement strategies that would simplify machine learning model comprehension for non-experts. The DNN classifier performed the best when compared to other classifiers, achieving an AVC value of 0.86 and an F1-score of 0.56 on the validation set.