Product Brief - Ending bottlenecks in medical cost prediction

Overview

Actuaries in healthcare manually analyze past medical claims to predict future costs using rudimentary machine learning techniques. They refactor their constraints and rerun their models repeatedly, which takes a lot of time and expensive computing power every year. This makes the process very slow and complex- and as we’ve seen in recent market results, these models still don’t accurately protect loss ratios.

In 2024, major payers have seen their stock prices take a big hit as they fail to accurately predict healthcare costs and manage their medical loss ratios. This has been exacerbated by the need to frequently refactor constraints and rerun actuarial models, consuming significant computational resources and time, which has proven to be both costly and inefficient.

Like recent breakthroughs in capital market predictors, Intrepio will analyze past medical claims to predict future costs. AI models can run existing actuarial models much faster, eliminating the need for constant manual adjustments. This approach saves time, reduces computing costs, and simplifies the process, making it more efficient and effective.

What's more, AI can learn complex patterns in the data not obvious to humans and generate altogether new models for Intrepio clients based on learned information. This enables the creation of more accurate and insightful predictions, continuously improving over time. As a result, Intrepio clients stand to benefit from enhanced decision-making capabilities and significantly more precise risk assessments, making loss ratios favorable even in rapidly evolving markets.

What we're doing