What do insurers do with the health data from my application scan?

The shift from in-person paramedical exams to remote, app-based health screenings has changed how insurance applications work. Applicants can now complete a significant portion of the health assessment process from their own phones, often in minutes. This convenience, however, raises a critical question for consumers: what exactly happens to the health data from my application scan? As insurers adopt this new technology, understanding the insurer application scan data use is essential for any applicant navigating the modern insurance marketplace. This report breaks down what data is collected, how it is analyzed for underwriting, and the evolving regulatory framework governing its use.

"A 2023 survey by the National Association of Insurance Commissioners (NAIC) found that 84% of health insurers are now using artificial intelligence and machine learning, with many applications focused on underwriting and risk assessment."

How insurer application scan data use works in underwriting

When you complete a digital health assessment, the data collected goes through a structured analysis process designed to give underwriters a clear picture of your current health status. The primary goal is to assess risk in a way that is faster and more efficient than the traditional, and often slow, process of scheduling a nurse visit and waiting for lab results. The core of insurer application scan data use is about translating digital biomarkers into actionable underwriting insights.

The process typically involves a few key types of data:

• Vital Signs: This includes measurements like resting heart rate, heart rate variability (HRV), blood pressure, and respiratory rate. These are captured by analyzing video of your face as light reflects off your skin (a technique called photoplethysmography, or PPG).
• Biometric Indices: Using the vital signs and other inputs, algorithms can calculate indices such as a Body Mass Index (BMI) estimation.
• Application Data: The scan data is always analyzed in the context of the answers you provide on the insurance application form.

This information is then fed into an underwriting engine, which is a sophisticated software platform that uses rules and algorithms to evaluate risk. The engine compares your data against the insurer's established risk classification guidelines. For example, your blood pressure reading will be assessed to see if it falls within the preferred, standard, or substandard risk categories. The speed of this process is a key reason for its adoption; underwriters can receive a risk score in near real-time, dramatically shortening the 30-to-45-day cycle common with traditional methods.

Data Point	Traditional Method	Digital Scan Method
Blood Pressure	Manual reading by a nurse	Estimated via phone camera PPG analysis
Heart Rate	Manual pulse check by a nurse	Measured via phone camera PPG analysis
BMI	Height and weight measured by a nurse	Estimated from facial biometrics and user input
Data Collection	In-person visit, manual data entry	30-second remote scan, automated data capture
Turnaround Time	7-21 days for results	Near real-time

Industry applications of digital health data

The use of data from application scans extends across several functions within an insurance carrier, primarily aimed at improving efficiency, accuracy, and the applicant experience.

Accelerated Underwriting

The most common application is in accelerated underwriting programs. These programs use data from digital sources, including health scans, to bypass the need for a full paramedical exam for qualified applicants. This allows carriers to issue policies faster, sometimes within 24-48 hours, for lower-risk individuals. The insurer application scan data use here is focused on quickly identifying applicants who fit a specific, low-risk profile.

Risk Segmentation

Insurers also use this data to better segment applicants into appropriate risk pools. By capturing a more immediate and objective snapshot of an applicant's health, carriers can refine their risk classifications. An applicant with excellent vital signs from a scan may qualify for a better rate than they would have based on application questions alone. This allows for more precise pricing and helps ensure the long-term sustainability of the insurer's risk pool.

Fraud Detection

While not its primary purpose, the data can also serve as a cross-check against the information provided in the application. Discrepancies between self-reported information and the objective data from a scan can trigger a review. For example, if an applicant claims to be a non-smoker but the scan data and other third-party sources suggest otherwise, an underwriter may request further information.

Current research and evidence

The regulatory and ethical frameworks governing the use of digital health data are a major focus of industry bodies. The National Association of Insurance Commissioners (NAIC) has been particularly active in this area. In 2020, the NAIC adopted official principles on the use of Artificial Intelligence (AI) in insurance, emphasizing the need for fairness, transparency, and accountability.

Following these principles, the NAIC's Big Data and Artificial Intelligence (H) Working Group has been studying how insurers use these new technologies. A series of surveys conducted by the NAIC found that while adoption is high, the maturity of AI governance practices varies. In response, the NAIC adopted a Model Bulletin on the Use of Artificial Intelligence Systems by Insurers in December 2023. This bulletin sets clear expectations for insurers to have a formal AI governance framework, including risk management and oversight, to prevent data misuse or discriminatory outcomes. Research from institutions like the Society of Actuaries continues to explore the predictive power of data from wearables and camera-based scans compared to traditional underwriting evidence, aiming to establish clear benchmarks for accuracy.

The future of health data in insurance

The trend is moving toward more dynamic and personalized insurance products. In the near future, insurer application scan data use will likely expand beyond the initial underwriting decision. We may see the rise of policies that offer premium adjustments based on ongoing health monitoring, where consumers can voluntarily share data from their own devices in exchange for discounts. This model is already in use in auto insurance with telematics devices that track driving behavior.

However, the expansion of data collection will also bring greater scrutiny from regulators and consumer advocates. The balance between innovation and privacy will remain a central theme. Expect to see stricter guidelines on data retention, clearer disclosures to applicants about how their data is used, and more robust rights for consumers to access and control their information.

Frequently asked questions

1. Is the health data from a phone scan as accurate as a nurse's exam? Camera-based health scans use a technique called photoplethysmography (PPG) to estimate vital signs. While these technologies are rapidly advancing, they are generally used for risk triage rather than as a direct replacement for clinical measurements. Research by organizations like the Society of Actuaries is ongoing to benchmark the accuracy of these digital methods against traditional exams.

2. How is my health data protected? Insurers are bound by data privacy laws like HIPAA in the United States, which set strict standards for handling protected health information (PHI). Data from a digital scan is encrypted during transmission and storage. The NAIC's model bulletin also calls for strong governance and security protocols for any AI systems used in underwriting.

3. Can an insurer decline my application based only on a scan? A scan is typically one piece of evidence among many. An underwriter makes a final decision based on your complete application, which includes your health history, answers to medical questions, and potentially other data sources like prescription history reports. An unusual reading on a scan would more likely trigger a request for more information or a traditional exam rather than an automatic denial.

As digital health screening technology matures, companies like Circadify are focused on developing tools that provide a secure, transparent, and user-friendly experience for insurance applicants. To learn more about how this technology is being integrated into modern insurance platforms, see our guides and resources for insurance professionals at circadify.com/industries/payers-insurance.