AI Powered Insurance Underwriting

The Problem

Insurance companies have spent substantial amounts of money to digitize the process of customer onboarding and policy binding. However, progress has been slow and incremental. Efforts to scale and digitize underwriting have failed. Manual underwriting can be a slow and laborious process that involves entering data manually, frequent interactions with clients and their representatives, performing a lengthy risk assessment process among others. Manual processes take longer and are prone to errors, quality issues and inefficient pricing. Can AI be used to improve the underwriting process?

Solution

AI models can be deployed on Kranium to automate the underwriting process. Computer Vision and NLP Models can automate data extraction and digitization tasks which can eliminate the need to manually review and key in information from each document. Also, Machine Learning models can be trained on historical data from various sources to perform a better risk assessment of customers. Additionally, Machine Learning models can be used to predict profitable pricing that fits the risk profile.