Who is this product for:
- Financial Advisors
- Financial Planning Software
- Advisory Platforms
- Investor Websites
- Available as hosted solution for advisors or via API data calls to power financial planning software and web solutions for advisors/investors.
- Industry’s most accurate healthcare expense predictions, leveraging big data and machine learning technologies.
- Personalized healthcare expense projections based on each client’s health condition and zip code.
- Projections include both pre- and post-Medicare medical expenses, and long-term care expenses.
- Quickly determine financial goals for funding (present value of future expenses at retirement).
- Evaluate and optimize supplemental Medicare options.
- Library of video content to educate financial advisors.
Wealth Management Capabilities
Generate Accurate & Personalized Projections
AiVante’s patent-pending analytics engines analyzes the massive “All Payers” healthcare claims databases and more than 1,000 health plan coverage variables. It then applies machine learning methods against the data to understand how medical spending is likely to vary based on an individual’s geographic location and their health condition, including how their health conditions are likely to progress over time. The result is highly accurate long-term predictions of medical and long-term care expenses, which can be presented in aggregate and disaggregated form (eg, premiums and out-of-pocket expenses by year). This personalized, “bottoms-up” approach is superior to traditional actuarial methods that use “top-down” methods.
Improve Financial Planning, Drive More Savings & Frame Product Solutions
The predictive data can be used to frame savings goals. For instance, a client’s retirement medical expenses might total $325,000, but have a present value of $185,000 at retirement, which can be framed as a goal to fund by retirement, perhaps by saving more and using Health Savings Accounts. Similarly, long-term care expenses can be framed as a separate savings goal by retirement, or can frame the need for a hybrid long-term care / life insurance product.