INSURANCE PREMIUM PREDICTION USING MACHINE LEARNING
Keywords:
MachineLearning,DataCollection,Preprocessing,Informeddecision-makingAbstract
The accurate estimation of insurance premiums is vital for insurers to maintain competitiveness and financial stability. Traditional methods often struggle to account for individual risk factors, necessitating more advanced, datadriven approaches.This research harnesses machine learning (ML) techniques to construct a robust model for precise premium prediction, with the objective of optimizing insurance underwriting procedures. By conducting an extensive literature review, gathering and preprocessing data, and developing sophisticated models, we significantly enhance accuracy and reliability. Ethical considerations are paramount throughout the research process to ensure responsible and fair utilization of ML technologies. By leveraging our findings, insurers gain actionable insights that facilitate informed decision-making in a dynamic and intricate marketplace.Our study bridges the gap between traditional underwriting methods and modern data analytics, offering a novel framework for insurers to adapt to evolving risk landscapes.
References
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