Improving the Accuracy and Performance of Deep Learning Model by Applying Hybrid Grey Wolf Whale Optimizer to P&C Insurance Data

The insurance industry is based on risk calculations, high profits, and detailed information. predictive models that companies utilize allow to make accurate decisions about the sector. This research focuses improving accuracy of predicting customers Property Casualty (P&C) insurance. In this study, a reliable quantitative analytical big data method has been developed, Hybrid Grey Wolf Whale Optimization (HGWWO) utilized with Deep Learning Model for evaluating customer behavior P&C discussed Gray Wolf-Whale algorithm steps involved in optimization process. paper presented details how create Optimizer, Optimizer then combining both initialization, evaluation, relevant dataset improve prediction accuracy. We have also compared performance model few traditional machine learning models.