Insurance Claim Analysis Using Machine Learning Algorithms
May 15, 2021
The most important advantage of Machine Learning (ML) to use in Insurance Industry is to facilitate data sets. Machine learning (ML) can be successfully useful across Structured, Semi Structured or Unstructured datasets. Machine learning can be used accurate across the value chain to identify with risk, claims and customer actions, by means of advanced predictive accurateness. The probable applications of machine learning in insurance are plentiful from perceptive risk appetite and premium leakage, to expense administration, subrogation, proceedings and fraud detection. Machine learning is not a novel technology; this technology is following from the last few decades. There are 3 main categories of learning they are supervised learning, Unsupervised Learning and reinforcement learning. The greater part of the insurers arefollowing Supervised Learning fromlast few decades for assessing the risk by means of known parameters in dissimilar combinations to acquire the preferred outcome. Present age insurers are motivated to unsupervised learning, in this predestined goals are clear. If there are any modifications in the variables, the method identifies those modifications and tries to change as per the goals. For example according to traffic the GPS Suggests different routes dynamically based on traffic conditions. In insurance industry also the learning is adopted for usage based insurance
