The seenity Blog
Can Risk Assessment Help your Customers?
Insurance companies face numerous challenges that can be addressed with the help of advanced AI. However, in the process of generating AI-powered risk models, it’s often hard to create the accurate correlation between the task on-hand and the AI environment.
From Broad Circumstantial Data to Actual, Concrete, Models
Insurance companies have relied heavily upon the Generalized Linear Model (GLM) for many years, and some still utilize it today. Before AI revolutionized our lives, implementing this model was achieved by categorizing users into groups based on factors such as age and cost of asset; these parameters were then applied to a formula that used limited computing power in order to draw conclusions.
Game Changing MLOps for the Insurance Industry
DevOps strives to streamline software development by bridging the gap between development and operations teams, delivering high-quality, reliable software faster and with less risk. Similarly, MLOps aims to manage the entire life cycle of machine learning projects, including data management, model creation, deployment and monitoring. By automating these processes, MLOps can help ensure that models are accurate, reliable and scalable.
Navigating the Data Deluge: How Seenity Empowers Institutions with AI-driven Data Visibility.
In today's digital age, institutions such as insurance companies, banks, and pension funds face an increasingly complex data landscape.