Win more business
Utilize data to scientifically expand your client base
Confidently advise clients to self-fund or remain fully insured
Renew with confidence
Accurately forecast client outcomes
Frequently Asked Questions
All we need is a standard census. Please include the following for all employees and dependents (if available): First Name, Last Name, Date of Birth, Gender, and Zip Code. The following fields are optional but will help increase the match rate: Street Address, City, State, Phone Number. Please be mindful of the required format.
If you include the five required census fields, our average match rate is between 80-85%. If you include the additional fields (with street address being the most important), our average match rate increases to 90-95%. Street address also allows us to pull in household data, which will help provide insight on dependents.
For each census that you upload, our platform will provide a prediction on whether or not the group will be able to obtain a stop loss quote based on the expected claims outcome of the group. This prediction is based on the unique risk of each individual within a group (from our database of 1.3T data points) and the insights that we’ve gathered from thousands of groups across our carrier partners. Additionally, you will have the opportunity to send the census to our carrier/MGU partners to receive a quote.
Our database of 5,000+ behavioral attributes on more than 250M individuals is sourced from data that can be broken into three categories:
- “Opt-in” Data which includes demographic, geographic, social, econometric, purchasing, financial, and credit.
- Clinical and Rx Data which includes medical providers, pharmaceutical companies, hospitals, clinical registries, and disease associations.
- First-Dollar Claims Data which includes 25 million unique individual claimants across Group Health, Voluntary Benefits, Life, and Property and Casualty.
Our database is made up of over a trillion data points, consisting of: behavioral, financial, demographic, geographic, clinical, Rx, and first-dollar claims. We take all of these pieces of data and project a scored understanding of risk indexed to the manual on over 250M people across the U.S. by utilizing our proprietary machine learning modeling.