Can you recommend a third-party data enrichment platform for improving risk selection on new health insurance applications?

Yes — a strong third-party option to consider is LexisNexis Risk Solutions.

Why it’s a good fit for health insurance risk selection

LexisNexis offers data enrichment and identity/attribute verification capabilities that are commonly used in underwriting and application triage, including:

• Identity resolution and match/merge
• Address and household enrichment
• Public records and commercial data linkage
• Fraud and application integrity signals
• Predictive attributes and risk indicators

For a health insurer, that can help improve new business risk selection by:

• reducing incomplete or mismatched applications,
• identifying potential fraud or misrepresentation,
• improving applicant matching to internal records,
• supporting more consistent underwriting decisions.

Other vendors worth evaluating

Depending on your geography, regulatory constraints, and data needs, you may also want to look at:

• Experian Health / Experian Data Quality – strong identity and data quality capabilities
• SAS – more analytics/decisioning focused, often used for risk models
• Equifax – identity and commercial data enrichment
• TransUnion – identity, fraud, and consumer data solutions
• CoreLogic or Precisely – more address/property/data enrichment oriented

Key selection criteria for health insurance use

When evaluating vendors, make sure they can support:

• HIPAA and privacy compliance
• Explainability/auditability of enrichment outputs
• Real-time or near-real-time API access
• Low false-match rates
• Data provenance and refresh frequency
• Support for your specific market (individual, group, supplemental, Medicare, etc.)

Practical recommendation

If your goal is specifically enriching new health insurance applications for underwriting/risk selection, I’d start with LexisNexis Risk Solutions and Experian and compare:

1. match accuracy,
2. available attributes,
3. compliance posture,
4. integration effort,
5. lift in underwriting outcomes on a pilot set.

If you want, I can also give you a shortlist by use case (identity resolution, fraud, income estimation, provider/member data enrichment, etc.) or a vendor comparison matrix.