Author: Alena Sarri, Owner, Aquatots Swim School
Children’s activity data flows through every swim school, gymnastics club, and martial arts dojo on the planet. Yet most providers have no idea that children’s activity data represents a genuine commercial asset for the insurance industry. Enrollment platforms like Jackrabbit, iClassPro, and Amilia capture granular records of attendance consistency, payment regularity, family spending, and re-enrollment rates. Meanwhile, insurers spend billions chasing alternative behavioral data to sharpen their underwriting. The gap between these two worlds is wide, but it will not stay that way for long.
Children’s Activity Data Holds 5 Signals Insurers Already Value
The enrollment management platforms powering children’s activity providers collect far more than names and class times. Jackrabbit alone serves over 7,000 programs across 25 countries, tracking enrollment dates, drop dates with reasons, billing cycles, and skill progression. On top of that, iClassPro’s Pro Insights module monitors trial-to-enrollment conversion, family revenue contribution, and consecutive absence patterns. Platforms like Pike13 then expose invoice-level revenue per client through full REST APIs.
So why does this matter for insurers? Because children’s activity data contains five behavioral signals that map directly to risk assessment.
First, attendance consistency reveals routine and discipline. Second, payment regularity mirrors the financial stability metrics that already drive credit-based insurance scoring. Third, enrollment duration signals long-term commitment to healthy behaviour. Fourth, re-enrollment rates indicate family health consciousness. And fifth, family spending patterns across multiple children and activities paint a detailed picture of household financial resilience.
Together, these data points build a behavioral profile of families who are financially stable, health-conscious, and forward-planning. From an insurer’s perspective, that cluster of favourable characteristics is the definition of low risk. The childcare management software market was valued at over $200 million in 2024 and is projected to reach $359 million by 2031. Across these platforms, data flows from millions of families around the world.
Insurers Have Already Proven the Behavioural Underwriting Model
The insurance industry is not waiting around for traditional data sources. Discovery Vitality, launched in South Africa in 1997, now operates in over 40 markets and tracks steps, heart rate, sleep data, and even grocery purchases from 170,000 households. In 2018, John Hancock announced it would only sell interactive Vitality policies, making it the first major US life insurer to fully commit to behavioural data integration. As a result, Vitality policyholders earn up to 25% annual premium savings.
However, no insurer has yet partnered with a children’s activity provider for data access. This is confirmed whitespace. The closest examples include Humana Go365, which allows under-18s to participate with parental registration, and Players Health, an insurtech providing risk management for youth sports organisations. Neither involves data sharing from enrollment platforms.
The actuarial case for children’s activity data is strong. The WHO reports that insufficiently active people face 20 to 30% increased risk of death compared to active individuals. Additionally, the Cardiovascular Risk in Young Finns Study found that children who maintained physical activity for three or more consecutive years were 4 to 7 times more likely to remain active as adults. On top of that, adolescents in organised sports are 8 times as likely to be active at age 24.
These longitudinal studies give insurers exactly what they need: actuarial justification for treating childhood activity participation as a meaningful risk signal. Similar to how AI-driven fraud detection uses behavioural patterns to assess financial risk, children’s activity data provides pattern-based insights that traditional underwriting misses entirely.
Privacy Barriers Are Real, but Aggregate Models Offer a Path Forward
Any discussion of commercialising children’s activity data must confront the regulatory landscape head-on. The FTC finalised sweeping COPPA amendments in January 2025 that require separate verifiable parental consent before disclosing children’s personal information to third parties. Penalties reach $53,088 per violation per day. Meanwhile, GDPR imposes strict purpose limitation rules on children’s data, and the UK’s Age Appropriate Design Code presumes against sharing it with third parties.
So individual-level data sharing faces near-prohibitive barriers. However, aggregate and anonymised models change the equation. A compliant framework would apply differential privacy to all shared statistics, share only composite metrics like a “Family Wellness Index” derived from population-level patterns, and require granular parental opt-in consent that is revocable and time-limited.
The embedded insurance distribution model sidesteps data privacy concerns altogether. Instead of sharing children’s activity data, platforms sell accident insurance or family wellness products at the point of enrollment, capturing commission without transferring any personal records. The embedded insurance market is projected to exceed $3 trillion in premiums, making this a viable revenue path that requires zero data transfer.
Amilia’s partnership with ActiveXchange is the closest working example right now. It provides cross-customer benchmarking and AI-powered churn prediction with 85% accuracy. This model shows how aggregate enrollment insights generate commercial value without exposing individual records.
The Opportunity Is Real, but the Infrastructure Is Not Built Yet
The alternative data market reached $14.16 billion in 2025 and is projected to grow to $854 billion by 2035. Insurers are hungry for new behavioural signals, and children’s activity data represents one of the last untapped sources. The broader transformation happening across fintech suggests that these data connections between previously siloed industries will only accelerate.
For children’s activity providers, the question is no longer whether this data has value. It does. Instead, the question is whether the industry will build the privacy-first infrastructure needed to unlock it responsibly. Three gaps must close: a cross-platform data aggregation layer needs standardising, anonymisation-first architecture must be baked in from day one, and insurer buyers need education on what this data source offers beyond traditional risk models.
Children’s activity data is an asset hiding in plain sight. The providers who recognise it first will hold a significant advantage when insurers come looking.