Recommendations
Q: How do Nayya’s recommendations work?
A: Nayya leverages a combination of machine learning and rules based systems as the backbones of our recommendation engine. By combining methods, we are able to efficiently recommend plans based on the complexity of the data needed. Specifically for our medical recommendations, Nayya has built (and continues to build and iterate on) multiple model types. A core feature of our medical recommendation models is the ability to assess both plan and user data simultaneously. This allows us to analyze the data of the user and map that information to the appropriate plan available that fits their individual needs.
As a high level overview, our recommendation process is to:
1. Analyze user data
2. Analyze plan data
3. Labels generated by actuaries based on analysis
4. Model is trained on actuary labels and synthetic data
5. Model is constantly reviewed and retrained as more users provide data
As a high level overview, our recommendation process is to:
1. Analyze user data
2. Analyze plan data
3. Labels generated by actuaries based on analysis
4. Model is trained on actuary labels and synthetic data
5. Model is constantly reviewed and retrained as more users provide data
Q: How is Accident Insurance recommended?
A: To trigger an accident insurance recommendation, Nayya looks at factors such as the users income, age, and risk indicators from our survey. If the analysis of user data indicates they are more likely to incur an accident claim than the “Average” person, and the plan is deemed affordable, that user will be recommended an accident plan.
Average user is defined internally by Nayya. This is similar to how an actuarial table works - a user with a value of “1” is no more or less likely to incur an accident than another, therefore they will not be recommended an accident plan. A user with a value of 1.1 would be recommended an accident plan.
Q: How is Critical Illness recommended?
A: To trigger a Critical Illness recommendation, Nayya looks at factors such as age, income, and pre existing conditions. A presence of these factors will impact not only if a CI recommendation will be generated, but also how much in coverage a user should enroll in. As a basic rule of thumb, as age increases and the number of pre-existing conditions increases, the higher the volume in CI recommendation will be.
Q: How is Hospital Indemnity recommended?
A: To trigger a Hospital Indemnity recommendation, Nayya looks at factors such as age, income, utilization, and plan design. Unique to Hospital Indemnity, this can be triggered as part of the medical recommendation OR as its own recommendation. For example, if a user indicated planned utilization, such as maternity, the benefit of the Hospital Indemnity plan will be calculated in the medical recommendation. However, an Hospital Indemnity recommendations can be triggered solely based on other factors, such as a certain age or presence of preexisting conditions.
Q: Does Nayya support HSA recommendations?
A: Yes, Nayya handles HSA recommendations in two ways. First, if a user is recommended a HDHP, they will be presented with HSA benefits education within Decision Support. Second, the user will see both an employer contribution (if applicable), and a recommended employee contribution. An interactive calculator is also available to view projected savings by year.
Q: Does Nayya support FSA recommendations?
A: Nayya does not recommend a specific FSA contribution, like with HSA’s. However, FSA eligibility and general education are included.
Q: Will Nayya always recommend an HSA plan?
A: No. Nayya reporting shows that ~48% of users were recommended an HSA Plan.
Nayya & ADP Confidential Information: Internal Use Only
If you have any questions please contact adp@nayya.com for more information.