Machine Learning, Blockchain answer to risks & frauds
Due to various frauds, insurance companies in India faced a loss of $50 billion in 2011. If calculated with precision, this loss amounted to almost 9% of the insurance industry. If analytics is not implemented properly, insurance industry might face a greater loss.
The rising trend of process automation and lean compliance in the insurance sector will catalyze the emergence of machine learning across geographies in the near future. AI-based consumer needs analysis can help improve the probability of lead-to-quote conversion by insurers, thus reducing turnaround times. Using machine learning could also eliminate subjectivity in response and would lead to savings in overhead costs to a great extent.
The claims management process has multiple stages which can be automated by machine learning, using a combination of modelling, rules, text-mining and database searches. By applying machine learning techniques to claim audits, the machines can help enhance the ability to learn from those throughout the claims life cycle. Machine learning can help identify fraudulent claims and give the insurers a more accurate idea of a person’s lifestyle choices, thus, ensuring better compliance and preventing mis-selling of products.
The claims process in the insurance industry is risk-prone and the industry spends overall around $2 billion to identify fraud and compliance issues in the process. Blockchain can bring the customer closer to the insurance provider. Customers can approach other customers to create an insurance identity to insure themselves as a group. Blockchain is the answer to risks and frauds associated with the insurance process.