Effective underwriting and actuarial models are crucial for ensuring your organization achieves optimal pricing while helping members get the coverage they need. Unfortunately, underwriting comes with many challenges.
How should you set your premiums? What if there ends up being more high-cost members than you plan for? Are you on track to meet your medical loss ratio requirements? How can you make your organization more competitive? Here’s how to address some of today’s biggest pain points in actuarial and underwriting.
Pain point: You need more accurate risk assessments
When deciding who to cover and setting the terms, it’s important to understand the risks you’re taking on and potential costs. However, those aren’t always easy to see. Inaccurate or insufficient risk assessments can lead to high-risk members not getting the proper coverage and cause your organization to pay more than what’s budgeted. Lack of visibility to risks and costs can also cause you to set sub-optimal pricing. You need more accurate risk assessments.
Solution: Predict costs and risks using AI
Tools that use artificial intelligence (AI) and machine learning (ML) can help you accurately predict costs (including identifying high-cost members and groups) and assess risks. For example, Lumiata offers the Spectrum AI Model Catalog, which features ready-made healthcare ML models that can be used as-is or customized based on your specific needs. You’ll gain access to a financial model suite that’s up to 80% more accurate than the nearest competitors’ cost prediction models, helping you predict and plan for expenses.
Our financial models include a high-cost patient model, group cost model, and stop-loss model. The Spectrum AI Model Catalog also includes clinical models, such as chronic condition management models, disease onset models, and hospitalization models, giving you insight into members who are at risk of medical events that could increase your costs.
Pain point: You need to be more competitive
For your business to succeed, groups need to be appropriately priced. However, determining the right prices can be tricky. You don’t want to price your plans so high that people can’t afford them or don’t want them, but you don’t want to price them so low that you end up with high costs. Sub-optimal pricing can also lead to market share erosion, hurting your business. You need to find a way to be more competitive.
Solution: Use predictions to set optimal pricing
Remember those financial and clinical prediction models we talked about? You can use insights from those to help you set optimal pricing and increase competitiveness while slowing market share erosion. When you can see what risks your members and groups have and know what costs to expect, you can set better prices, making you more competitive while reducing costs.
Pain point: You need a more reliable system
When working on underwriting, how complete is your data? Perhaps you have a good idea of how much each member or group might cost you on average, but what about anomalies? Unexpected high-cost members can make groups more expensive than you planned for, making your data less reliable. Failing to identify these high-cost members can also increase your costs above what you were expecting. You need more reliable data.
Solution: Detect anomalies to improve data reliability
Lumiata uses AI and ML to detect anomalies in the underwriting process, allowing you to factor them in when assessing risks and costs and setting plan prices. This makes your data more reliable, helping ensure you set prices that are high enough to cover expected costs yet low enough that members won’t leave you for another carrier.
See how Lumiata can solve your pain points
We believe that intelligent technologies like machine learning will transform underwriting and have seen the possibilities firsthand through our work with major payers. Are you ready to step into the world of machine learning? To learn how Lumiata can use AI and ML to address your specific pain points, click here to request a demo.